CDO Handbook Final

31 March 2006 Fixed Income Research http://www.credit-suisse.com/researchandanalytics

Cash Flow CDO Handbook Structures, Insights & Strategies Structured Products

Contributors David Yan +1 212 325 5792 [email protected] Stephen Chow +1 212 538 5523 [email protected]

Editor’s Note In this publication, we have collected 25 reports on cash flow CDOs, most of which were originally published in our bi-weekly “The CDO Strategist”. We have also included some of our most popular previous publications as we believe many of the concepts, ideas, risks, and structures are as relevant today. This compilation covers almost all cash flow CDO types, ranging from Structured Finance CDOs and CLOs to Trust Preferred CDOs; the topics include primers on new products, investment strategies and relative value ideas, risks of CDO products, and secondary valuation issues. We hope our readers would find this handbook useful as a long-term reference material and we believe some of the topics discussed will remain topical as the CDO market evolves. We also welcome any feedbacks and comments so that we can improve future editions. Thank you.

FOR IMPORTANT DISCLOSURE INFORMATION relating to analyst certification, the Firm’s rating system, and potential conflicts of interest regarding issuers that are the subject of this report, please refer to the Disclosure Appendix.

31 March 2006

Introduction: 2005 Review, 2006 Forecast

3

Chapter 1. Structured Finance CDOs

18

Structured Finance CDO Primer

19

High Grade SF CDO Primer: Q&A

26

A Closer Look at High Grade SF CDOs

31

High Grade SF CDOs Revisited

42

Build or Buy: HEL Bonds versus SF CDOs

47

Revisiting Turbo Structure: Empirical Evidence

52

Auction Calls in SF CDOs

56

Default Assumptions for BBB HEQ in SF CDOs

65

Using the Right Rating Performance Measures of SF Securities for CDO Analysis 73 Impact of S&P’s New Rating Criteria on SF CDOs

84

Value Shifting to Mezzanine SF CDOs

92

Impact of HEQ Available Funds Caps on ABS CDO Tranches

96

Chapter 2. Collateralized Loan Obligations (CLOs) Calling Attention to CDO Calls

110 111

When’s the Best Time to Call? Optimal Timing of CDO Calls and Relative Values 117 A Comparison of US and European CLOs Chapter 3. Trust Preferred CDOs

125 137

Diversified Bank Trust Preferred CDOs - Primer

138

An Introduction to Insurance Trust Preferred CDOs

158

An Introduction to REIT Trust Preferred CDOs

176

Bank TruPS: Fine Tuning Historical Bank Failure Rates

190

Bank TruPS CDOs: Calling the Underlying

197

Chapter 4: Relative Value and Secondary CDO Market

201

Secondary Valuation Models of Cash Flow CDOs – Review and Pitfalls

202

2003 Vintage Mezz. SF CDOs – One of a Kind

212

Finding Value in Senior Tranches of Distressed SF CDOs

217

Seasoned Senior CLOs Should Trade Even Tighter

220

Junior AAA of HG SF CDOs Offers Attractive Value

223

Structures, Insights & Strategies

2

31 March 2006

Introduction: 2005 Review, 2006 Forecast1 In 2005, the US CDO market drove home another record year despite some bumps on the green. While uncertainty in the housing market mounted and the corporate credit environment felt new pressures from big-name bankruptcies, sector-specific stresses, and heightened leveraged buy-out (LBO) activity, the CDO market matured into a regular fixture in the bond markets. Buoyed by innovation, investors searching for yield, and robust demand, CDOs emerged not only as a balance sheet or arbitrage instrument, but also as an efficient financing tool. As we tee up for 2006, the CDO market faces off against new challenges in what’s believed to be a more tumultuous course. What lurks around the corner? We take a look back at 2005 and provide some thoughts on what lies ahead in 2006. We’ll share our “Top 5” issues for 2006 to help investors stay on the fairway.

CDO issuance: up, up, and away 2005 issuance sets new record: $188 BN across 368 deals

To call 2005 a record year for issuance would be an understatement. Not only did CDO issuance surpass the record set in 2004, but the year-over-year growth was second only to CMBS (which is partially attributed to the robust CDO demand for commercial real estate [CRE] assets) among all other structured product and high yield (HY) primary markets (Exhibit 1). The 2005 US CDO issuance volume reached a whopping $188 billion, 73% greater than 2004 by dollar amount and up 64% in terms of deal count (Exhibit 2).2

Exhibit 1: CDO issuance up 73% YOY, 2 assets*

nd

highest growth among structured

100% 80% 80%

73% 51%

60%

47% 31%

40%

23%

20%

14%

11%

HEQ

Lev Loans

0% -20% -40%

CMBS

CDO

MBS (nonagcy)

SL

Auto

CC

HY Bond -38%

-60%

Other ABS -44%

*Year-over-year change by dollar amount issued; 2004 vs. 2005 Source: Credit Suisse, MCM, IFR, Bloomberg, Inside MBS & ABS, Fitch, Moody’s, S&P, BMA

1 2


This section was originally published in "The CDO Strategist", Issue #13, January 25, 2006. Dollar amount includes MM/ABCP tranches and excludes unfunded tranches.

3

31 March 2006

Exhibit 2: CDO issuance reached a whopping $188 bn in 2005 HY/EM CBO

HY CLO

IG CDO

BAL SHEET

SF/MS

MV

SYN

Issuance ($ billions)

195.0 185.0 175.0 165.0 155.0 145.0 135.0 125.0 115.0 105.0 95.0 85.0 75.0 65.0 55.0 45.0 35.0 25.0 15.0 5.0 (5.0)

OTHER $188 BN

$109 BN

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Source: Credit Suisse

“Big two” issuance soared, though market share was unchanged as other CDO asset classes showed prominence in ‘05

On the cash side, CDO issuance remained dominated by structured finance (SF) CDOs and HY CLOs. The “big two” combined accounted for $154 billion, or 82% of the CDO market in 2005, nearly identical to 2004’s 83% market share (Exhibit 3). While the absolute dollar increase was significant (70% growth over 2004), the relative market share remained almost unchanged as several other asset classes made waves in 2005, which we expect to ripple into 2006. In particular, the standardization of ISDA’s template for CDS of ABS injected new fuel into an already energized synthetic CDO market, which helped drive synthetic CDO issuance up considerably in ’05, as well as introduce the hybrid cash/synthetic structure. Additionally, CDO technology was applied to new asset classes such as REIT trust preferred securities (TruPS). We’ll discuss each asset class in further detail below.

Exhibit 3: SF CDOs and HY CLOs continue to dominate issuance in 2005 90%

$160 $140

60% 50%

42%

40%

54%

51%

20%

0% 15%

11%

1996

1997

0%

12%

22%

22%

22%

26%

28%

29%

31%

18%

1998

1999

2000

2001

2002

2003

2004

2005

0%

$100

$60

1%

0%

$120

$80

28%

30%

10%

46%

Issuance ($ billions)

70% % of Issuance

$180

SF/MS % HY CLO % SF/CLO $

80%

$40 $20 $0


SF CDOs – High Grade, CRE and CDS of ABS shape the market For SF CDOs, several developments changed the landscape in 2005. We highlight three key points as follows: 1.


High Grade (HG) SF CDOs. HG SF CDOs experienced tremendous growth in 2005. Issuance totaled $51 billion, which represents more than 50% share of all SF CDOs issued during the year. This also represents an 81% increase over 2004 by dollar amount and a 71% increase by deal count.

4

31 March 2006

The economics of a HG SF CDO is largely dependent on how the largest tranche – the senior tranche – is funded. 3 For the past several years, term liability spreads were too expensive to make term funding a widely used financing option. Instead, HG SF CDOs turned to the ABCP market to fund the senior tranche. This introduced additional transactional risks and costs, including 1) remarketing risk (the money-market tranche must be remarketed every 270 days or so), 2) a match-funding issue (use of short term paper to fund long-term notes), and 3) counterparty risk from the put provider in place to purchase the notes should remarketing be unsuccessful (the rating of the notes often shadows the rating of the put counterparty). Counterparty risk was especially evident in 2005 as a number of HG SF CDO tranches were downgraded because the put counterparty’s ratings deteriorated. As a result of spread tightening across asset classes, the funding paradigm has shifted from ABCP to term funding as financing costs have converged. In 2005, over 65% of HG SF CDOs were term funded (Exhibit 4). This mitigates the risks associated with using ABCP as detailed above.

Exhibit 4: HG SF CDOs experience tremendous growth; shift towards term funding 45

Term Funded (deal ct - left axis) ABCP Funded (deal ct - left axis)

35

Issuance ($BN - right axis)

$51

$50 $40

30 Deal Count

$60

$28

27

25 $30

6

20 $14

15

$20

3

10

18

$4

5 0

$1 0 1

1 4

11

2001

2002

2003

Issuance ($ Billions)

40

14

$10 $0

2004

2005


Why was HG issuance so robust in 2005? We believe there are several reasons. 1) From a technical view, subordinate home equity (HEL) – which comprises 60%-90% of a typical mezz. SF CDO – spreads remained tight for most of 2005 and the arbitrage for mezzanine SF CDOs was squeezed, thus making these transactions less attractive to equity investors; 2) Because CDOs were gobbling up the overwhelming majority of subordinate HEL (upwards of 70%), collateral sourcing became difficult; 3) From investors’ perspective, housing market concerns may have pressured some investors to move up in credit, turning to HG SF CDOs since liability spreads between the two products were trading on top of each other – for most part of the year – while the spread volatility for senior HEL tranches, compared to subordinate tranches, tends to be lower as they are more cushioned in the event of a downturn in the housing market. 2.

CRE CDOs. Another driver of growth for SF CDOs in 2005 was the impressive upsurge in CRE CDO activity, which rose 84% to $16 billion (Exhibit 5). Several factors contributed to this growth. First off, a large number of new entrants from REITs to hedge funds entered the space. Participants realized the advent of CDOs, not necessarily as a traditional arbitrage vehicle but rather as a low-cost term financing vehicle without mark-to-market triggers as required by other

3

For a detailed discussion on HG SF CDOs, please see "The CDO Strategist - Issue #7 - A Closer Look at High Grade SF CDOs", 9/20/2005, Credit Suisse CDO Research. Structures, Insights & Strategies

5

31 March 2006

funding alternatives. The collateral manager would retain the equity and/or junior tranches, attaining attractive leverage while maintaining control of the loans in case of work-outs should defaults occur.

Billions

Exhibit 5: CRE CDO issuance surge - $16 bn priced, an 84% rise $18

35

CRE CDO Issuance ($ BN, left axis)

$16

CRE CDO Issuance (deal count, right axis)

30

$14 25

$12

20

$10 $8

$16

$6 $4

$7

$2

$1

$1

$3

1999

2000

2001

15 10

$9 $6

5 0

$0 2002

2003

2004

2005


Another contributor to the growth of CRE CDO was, quite simply, the sheer increase in supply and demand. As we noted earlier, CDO YOY growth as a whole was second only to CMBS in 2005. Although short-term interest rates continued to rise throughout the year, long-term rates remained range-bound, which supported an accommodative environment for CRE financing. Additionally, continued strong performance of CMBS attracted new investors to the asset class particularly from overseas and from CDO vehicles. Furthermore, one particular development of CRE CDOs was the evolution of the collateral pool. CRE CDOs shifted away from traditional CMBS tranches and into non-rated CRE assets, including B-notes, mezzanine loans, and whole loans (Exhibit 6). There have even been transactions in ‘05 comprised almost entirely of whole loans, credit tenant leases (CTLs), or B-notes. As such, the demand from CDOs for unrated CRE assets has expanded that market beyond a handful of investors and into a much broader investor base.

Exhibit 6: Collateral pools shift away from CMBS and into un-rated CRE assets 100% 90%

Non-CRE

80%

Other CRE

70%

Mezz

60%

Whole Loan

50%

B-note

40%

REIT

30%

CMBS

20% 10% 0% 2003

2004

2005

Source: Credit Suisse, Moody’s, S&P, Fitch, Intex


6

31 March 2006

3.

CDS of ABS. No discussion of SF CDOs is complete without addressing the 100-ton gorilla that emerged in 2005: CDS of ABS. During the first half of 2005, ISDA published its template for executing CDS of ABS on a Pay-As-You-Go (PAYG) basis.4 This may well revolutionize the ABS markets and the impact has already been felt. Hedge funds took full advantage of the development of the ABS CDS market, and CDOs were ready to respond. In October, macro hedge funds purchased protection on subordinate HEL tranches en masse, expressing a view of a possible downturn in the housing market. Subordinate HEL spreads in both cash and synthetic markets spiked to their highest levels since Q2 2004. BBB cash HEL spreads nearly doubled to 250 bps in the course of a couple of weeks. In response, this brought about a renaissance for mezzanine SF CDOs, which had been relatively dormant due to collateral sourcing difficulties and the squeeze in equity arbitrage in the tight spread environment during most of the year. The emergence of Hybrid cash/synthetic structures presents investors another vehicle to take advantage of potential relative value opportunities between cash and synthetic assets. These structures have all the typical features of a cash CDO, including turbo features, OC/IC coverage tests, etc. with the ability to invest the majority of collateral synthetically, typically at a ratio of 70% synthetic and 30% cash assets. Moreover, several structures began featuring long/short strategies whereby the collateral manager could take opportunistic short positions to hedge single-name or market risk. Issuance of cash and hybrid mezzanine SF CDOs doubled from Q3 to Q4 – from $3.6 billion to $7.6 billion. Additionally, nearly $10 billion in cash or synthetic mezzanine SF CDO transactions have been announced since the beginning of 2006. The advent of CDS of ABS also greatly reduces the time required for deals to come to market and the ramp-up risk associated with cash collateral sourcing. Furthermore, CDO managers can now pick ABS credits selectively through the virtually limitless synthetic supply and bring in more diversification, as opposed to the limited cash market.

HY CLO – Thirsting for spread, weathering the storm, with 75 asset managers The HY CLO market experienced another record-breaking year in 2005. Issuance increased 82% by dollar amount to $58 billion across 112 transactions (Exhibit 7). Middlemarket loan (MML) CLOs also experienced relatively strong growth as the asset class attracted a broader investor base. However, the market was not without its bumps. Many credit events including big-name bankruptcies such as Delphi, Delta Air Lines, and Refco, stresses in sectors such as auto and aircraft, and intense LBO activity tested the resiliency of the CLO market. Despite these events, CLO spreads remained firm or even tightened through the storm and only a few transactions were impacted to the point of ratings downgrade. Several analyses we conducted throughout the year showed that most CLO collateral pools were diversified enough to withstand the credit events. Additionally, the benign economic environment supported very favorable recovery rates, in the area of 80% for loans and 60% for senior unsecured bonds, according to Moody’s.5

4 For more on the ISDA PAYG template, please see "The CDO Strategist - Issue #4 - An Introduction and Comments on the New ISDA Template for CDS of ABS", 6/29/2005, Credit Suisse CDO Research. 5 Moody's "Monthly Default Report - November 2005", 12/6/2005. Figures represent 12-month trailing recovery rates for US bonds/loans.


7

31 March 2006

Exhibit 7: CLO issuance grows 82%, in tandem with record loan issuance $70

$180

HY CLO Issuance (left market) Institutional LL Issuance (right axis)

$50

$11

$160 $140 $120

$40

$100 $30

$7

$20

$0

$10 $0

$13 $1

$4

1996

1997

$19

$17

1999

2000

$1

$0

$3

$13

$14

$18

2001

2002

2003

$80 $46

$60 $40

$24

$20

Institutional LL Issuance ($ Billions)

$60 CLO Issuance ($ Billions)

$200

MML CLO Issuance (left market)

$0 1998

2004

2005

Source: Credit Suisse, S&P LCD

Spread (bps)

Exhibit 8: CLO spreads tighten despite volatility in corporate credit 325 300 255

250 225

BBB HY CLO CDX IG 3-7%

276

275 220

200

180

175 150 125

111

108

9/ 3/ 0 10 4 /3 /0 11 4 /3 /0 12 4 /3 /0 4 1/ 3/ 05 2/ 3/ 0 3/ 5 3/ 05 4/ 3/ 05 5/ 3/ 05 6/ 3/ 05 7/ 3/ 05 8/ 3/ 05 9/ 3/ 0 10 5 /3 /0 11 5 /3 /0 12 5 /3 /0 5 1/ 3/ 06

100

149

Source: Credit Suisse, S&P LCD

Institutional leveraged loan spreads reflect the benign environment by remaining range bound for most of the year and ending 2005 tighter on the year. The tight spread environment posed a dilemma for both new-issue and secondary CLO transactions. In the secondary market, vintage transactions in their reinvestment periods found it difficult to meet the minimum weighted average spread (WAS) test. Managers dipped further down in credit and looked towards riskier asset classes for spread within portfolio guidelines. When this option was exhausted, many transactions opted to amend deal indentures to lower the minimum WAS. Additionally, rather than sit on cash, equity holders of at least 27 CLOs past their non-call periods voted to call the deals in 2005, according to S&P. In the primary market, deals were structured with much larger buckets for riskier asset classes, such as mezzanine, second lien, and middle market loans, to enhance portfolio spread. Whereas older deals (pre-2005) had buckets of around 5%-10% reserved for such assets, deals in 2005 included buckets of 10%-20%. Particularly for middle market and second lien loans, some transactions had buckets as high as 40%. Portfolio credit also became riskier; Exhibit 9 shows the average WARF of HY CLOs in each vintage versus BB institutional loans spreads.


8

31 March 2006

Exhibit 9: HY CLO WARF Increases: Portfolios get riskier, reaching for yield, as institutional loan spreads contract 2350

Avg CLO WARF (left axis) BB Institutional Loan Spreads (right axis)

333

2300

307 2218

2250

300 2214 250

2200 2150

2103

216

202

2100 2050

350

185

200 150

2017

2000

100

LL Spread (bps)

Moody's WARF

2325

1950 50

1900 1850

0 2001

2002

2003

2004

2005

Loan spreads are from Credit Suisse Leveraged Loan Index, using year-end spreads for each year. Source: Credit Suisse, Moody’s, S&P LCD, Intex

Further exasperating the spread conundrum was the fervent demand from an influx of managers into the CLO space. In 2005, a whopping seventy-five managers crowded the CLO market, with little, if any, spread tiering among new issue pricings. More so than ever, manager selection becomes crucial, especially when managers are diving into riskier assets. We’ll discuss this in further detail in our forecast section. From a structuring perspective, 2005 saw an increase in the use of delay draw notes and senior revolving structures, which benefits the equity by minimizing negative carry during ramp-up. Additionally, market value structures and credit opportunity funds also saw strong interest and as market value technology has expanded and evolved, it is being applied to other CDO products as well. These transactions typically offer considerably more manager flexibility and the ability to invest in more distressed pools at the expense of lower leverage. Market value structures are in position to capitalize on market volatility, which has increased in the corporate credit landscape in 2005 and is expected to rise over the next few years as the turning of the credit cycle looms. Finally, the seeds for leveraged loan CDS were planted in 2005 and synthetic exposure to loans continues to gain momentum, absent a standardized template for these trades. Almost all CLO transactions already have 10%-20% buckets available to take on synthetic exposure to loans. With a standardized loan CDS template expected in the near term, we believe this will be a robust market in 2006 with CLOs being the natural seller of protection.

Diversification, collateral sourcing difficulties, and tight asset spreads drive inclusion of other asset classes in TruPS CDOs


TruPS CDOs: Innovation meets necessity Trust preferred security (TruPS) CDOs experienced mixed issuance performance in 2005. While total issuance across all TruPS asset classes rose to a record $9.7 billion, deal count actually fell 11% to 17 deals from 2004’s high of 19. The reason behind this discrepancy is two-fold. First, the average deal size of a typical TruPS CDO grew by 20%. We believe this is because of better deal economics with larger pools and the fact that not only were most TruPS CDOs comprised of hybrid pools of bank and insurance collateral, but these transactions also began reaching into other asset classes because of constrained collateral supply and tightening asset spreads. An increasing number of deals began including TruPS CDO tranches and one transaction included a 12% concentration in REIT TruPS.

9

31 March 2006

REIT TruPS CDOs: leveling the playing field for small REITs

This brings us to the second point: the application of TruPS on REITs. 6 Similar to its benefits for the banking and insurance sectors, TruPS CDOs provide relatively low-cost, long-term, unsecured funding for REIT issuers, while providing investors the opportunity to invest in pooled REIT risk with industry and geographic diversification at attractive spreads and at new product premiums. Particularly for small to medium sized REITs (under $2 billion in market capitalization), TruPS help level the playing field by facilitating these REITs with access to the capital markets in an efficient manner. In 2005, we saw four REIT TruPS CDOs price, totaling $3.2 billion, a solid start for the asset class, although collateral supply is constrained by the number of available REITs in the universe (currently there are about 200 SEC-registered REITs and 800 unregistered REITs).

CDO credit: solid ratings performance, but sector & vintage matter

However, sector and vintage clearly mattered as rating actions were not uniformly distributed. SF CDOs accounted for over 67% of all downgrades in 2005 (by tranche count), a considerable increase over the 46% share during 2004. Further examination reveals that the surge is due to negative performance of troubled ABS sectors, such as manufactured housing, among collateral pools in early vintage (pre-2003) SF CDOs. As a result, 96% of downgrades among SF CDOs in 2005 occurred in these early vintages (Exhibit 12).

30

20

20

10

10

Source: Credit Suisse, Moody’s, S&P, Fitch

Dec-05

Oct-05

Aug-05

Jun-05

Apr-05

Feb-05

Dec-04

Oct-04

Jun-04

Aug-04

Apr-04

Feb-04

0

Dec-03

0

70 60 50 40 30 20 10 0

Oct-05

40

4

OTHER

Dec-05

30

SY NTHETIC

Aug-05

50

SF CDO

Jun-05

40

BAL SHEET

Apr-05

60

IG CDO

Feb-05

70

50

HY CLO

Dec-04

80

60

HY CBO

80

90

Monthly Deals on NW

Monthly DG'd Tranches

70

Exhibit 11: Upgrades rise as deals de-lever

Oct-04

BAL SHEET Deals on NW

Aug-04

IG CDO OTHER

Jun-04

HY CLO SY NTHETIC

Apr-04

HY CBO SF CDO

Feb-04

Exhibit 10: Negative actions decline, but shift to SF

Dec-03

Early vintage SF CDOs: the lion’s share of downgrades

In 2005, CDO downgrades continued to decline following a dramatic improvement in 2004, driven by the benign economic environment, high recovery rates, and low long-term interest rates (Exhibit 10). Downgrades averaged 29 tranches per month compared to 37 tranches per month during 2004 and 91 tranches per month in 2003. Deals on negative watch, a precursor to future downgrade activity, also improved and stabilized last year. On average, 29 deals were placed on negative watch each month in 2005 versus 37 deals in 2004. Additionally, upgrades continued to edge up, with 307 tranches upgraded in 2005, compared to 204 in 2004 (Exhibit 11).

Monthly UG'd Tranches

2005 was a solid year for ratings performance


6

For more on the REIT TruPS CDOs, please see "The CDO Strategist - Issue #8 - An Introduction to REIT Trust Preferred CDOs", 9/30/2005, Credit Suisse CDO Research. Structures, Insights & Strategies

10

31 March 2006

Exhibit 12: Most DGs on early vintage SF CDOs

Exhibit 13: Upgrades mixed across asset classes

DG'd SF CDO Vintages in 2005

Distribution of 2005 UG's

2003 2%

2004 1%

1999 1%

2002 29%

Mrkt Value 2%

2000 23%

SF/MS CDO 40%

2001 44% Source: Credit Suisse, Moody’s, S&P, Fitch

Synthetic Other 1% 3%

HY CBO 34%

HY CLO 19%

IG CBO 1%


Upgrades were diversified

Upgrades, on the other hand, were diversified among HY CLOs, HY CBOs, and recentvintage SF CDOs (Exhibit 13). HY CBOs & CLOs combined for about 53% of 2005 upgrades, buoyed primarily by continued amortization of CDO tranches and the subsequent de-leveraging of the transactions, which enhanced overcollateralization (OC) ratios. Furthermore, performance of HY corporate credits as a whole improved in 2005; most negative performance was concentrated in specific sectors, such as autos and airlines. Most HY CBOs/CLOs did not have significant exposure to these risky sectors. Although, we note that many European synthetic CDOs did have exposure and were put on watch or downgraded.

CRE CDOs and recent SF CDOs backed by RMBS/HEL were upgraded

SF CDO upgrades were particularly concentrated in deals backed primarily by CRE assets or newer vintage (post-2003) deals with high concentrations of residential mortgages (Exhibit 14). CMBS had a solid year in 2005 as national office vacancy rates improved, upgrades outpaced downgrades by eight to one, and many seasoned bonds were defeased, justifying upgrades of CRE CDOs holding these assets.7 On the mezzanine ABS CDO side, recent vintages warranted upgrades as prepayment speeds for 2003 and 2004 vintage residential mortgage pools were among the highest over the last ten years while delinquencies were among the lowest.

Exhibit 14: Distribution of 2005 Upgrades by vintage & asset class Vintage 1996 1997 1998 1999 2000 2001 2002 2003 2004 Total

HY CBO

HY CLO

3 14 21 40 24 1

2 2 14 14 7 1 5 13

103

58

IG CBO

SF/MS

MV

Synthetic

Other

Total 5 16 41 62 36 19 39 55 34

6 5 1 2

3

11 33 42 34 125

3

6

3

3 4 1 1

9

307

Source: Credit Suisse, Moody's, S&P, Fitch

7

For more on CMBS performance, please see "CMBS Market Watch Weekly", 12/16/2005, Credit Suisse CMBS Research. Structures, Insights & Strategies

11

31 March 2006

Finally, 2005 saw a record number of ratings withdrawals – 374 tranches across 120 deals. HY CBOs/CLOs accounted for over 75% of all withdrawn ratings by tranche count. Nearly all withdrawals were because of tranche redemptions or whole deals being called pursuant to the optional redemption from equity holders. Asset appreciation and the lack of alternative investments, both due to tightening spreads over the last two years, nurtured an environment for deal redemptions.8

CDO spreads: defining stability CDO spreads mostly unchanged, until Q4

For most of 2005, CDO spreads remained stable after tightening significantly in 2004 (Exhibit 15, Exhibit 16). As we’ve discussed, supply was exceptionally strong last year; demand from yield-seeking investors was equally robust. Volatility from hedge fund related buying of protection on ABS was the straw that broke the camel’s back, forcing subordinate spreads to widen for mezzanine ABS CDOs during Q4. In particular, BBB mezzanine ABS CDO spreads widened 80 bps within a few weeks, with one pricing seen at L+400 bps late last year.

Exhibit 15: 2005 select AAA CDO Spreads 45

HY CLO A A A CRE A A A

ABS M Z AAA B TRUP A A A

Exhibit 16: 2005 select BBB CDO Spreads 400

40

350

35

300

33 30

29 26

25 20

ABS M Z BBB CRE B B B

350

290

250 200

220 200 180

150

Dec-04 Feb-05 A pr-05 Jun-05 A ug-05 Oct-05 Dec-05 Source: Credit Suisse

Spread tiering exists among products down the credit spectrum

HY CLO B B B A B S HG B B B B TRUP B B B

Dec-04 Feb-05 A pr-05 Jun-05 A ug-05 Oct-05 Dec-05 Source: Credit Suisse

While most new issue Triple-A spreads have converged, spread tiering exists down in credit. As shown above, AAA spreads for SF CDOs and HY CLOs converged at L+25 – 27 bps for most of the year before widening slightly towards year-end. BBB SF CDOs ended 2005 about 170 bps wider than BBB HY CLOs. The new product premium associated with TruPS CDOs is mostly gone (with the exception of REIT TruPS CDOs) and there has also been a divergence between high-grade and mezzanine ABS CDO spreads at the subordinate level.

8

For more on CDO optional redemptions, please see "The CDO Strategist - Issue #2 - When's The Best Time to Call? - Optimal Timing of CDO Calls and Relative Values", 5/31/2005, Credit Suisse CDO Research. Structures, Insights & Strategies

12

31 March 2006

Our top 5 list for 2006 In the following section, we provide our top 5 issues CDO investors should be mindful of in 2006. Each issue may very well be an individual research topic, and so we’ve restricted our comments to brief highlights.

Corporations remain flush with cash, as investments remain low and profitability remains high Defaults should stay low, despite some risks & uncertainties

We do not think a national housing bubble exists

#1. Will the credit cycle reach a turning point in ‘06? The consensus of crystal balls says “no”.9 While some may believe the outlook is murky, nearing the tipping point, we believe evidence supports the contrary. Aggregate corporate credit quality is set to stay robust as profits remain high, cash flows remain robust, and external funding requirements remain minimal, barring any unexpected global financial distress. As with 2005, corporations continue to be flush with cash as investments remain very subdued relative to the current level of corporate profitability and cash flow. Additionally, the economic picture continues to look robust following a solid 2005. US real GDP is expected to grow at 3½%, not far from 2005’s projected path of 3¾%, although the composition of growth is expected to diverge from 2005’s.10 Growth will shift from the housing market and the consumer to the corporate landscape and the global economy. While there are risks and uncertainties on the horizon, including fears of amplified LBO activity, Fed tightening concerns, and increasing leverage, we believe the favorable corporate credit and economic environments outweigh these fears and should keep defaults low with a modest rise, if any. #2. Where is the housing market headed? Down, but not out. While we do expect moderate cooling in the housing market and some localized distress, we do not expect anything close to a national drop-off in activity. Signs of a slowdown have emerged as unsold home inventories have increased, and existing home sales have leveled off. Home price appreciation slowed in Q3 2005 as YOY HPA declined to 12.02% from 14.01% in Q2 2005. 11 Additionally, greater leverage in the mortgage market for new home buyers, coupled with rising interest rates and increasing regulatory scrutiny of affordable mortgage products, raises the risk of a regional downturn absent an economic trigger.12 However, with all this said, several key components supporting consumer credit should keep the consumer in the game. As we mentioned in the previous point (#1 above), the US economy is expected to remain healthy, with GDP growing at 3½% in 2006, which should continue to support job growth. With the job market remaining robust, and 30-year fixed mortgage rates essentially unchanged from when the Fed started tightening in 2004, growth in disposable income and wealth gains will support the consumer’s ability to service his/her debt in 2006. #3. Will 2006 be another record year for the CDO issuance? Given that 2005 turned out to be a blockbuster year for CDO issuance and the majority of market participants expect the supply of many cash collateral markets for CDOs – such as home equities – to fall in 2006, it seems reasonable to expect a drop in CDO volume.

9

This section makes significant references to "2006 US Credit Outlook", 12/14/2005, Credit Suisse US High Grade Credit Team, and "Leveraged Finance Strategy Outlook 2006", 1/16/2006, Credit Suisse Global Leveraged Finance Strategy and Portfolio Products Team. 10 "US Economics Digest: Forecast Review - 2006 Outlook", 12/16/2005, Credit Suisse US Economics Team 11 HPA stands for Housing Price Appreciation, which is calculated based on the housing price index. 12 "Quarterly Home Price Update: Is It Different This Time?", Credit Suisse ABS Research, 12/30/2005 Structures, Insights & Strategies

13

31 March 2006

Synthetic CDOs could make the difference in 2006

However, we see the synthetic market as the “wild card” – both in terms of synthetic CDOs and synthetic buckets in cash deals (including hybrid deals). The growing usage of synthetics will mitigate the difficulty of collateral sourcing for cash deals and the advantages of synthetic CDOs will push their volumes much higher in 2006. On a product-specific basis, developments in CDS of loans and ABS continue to proliferate the market. A standardized loan CDS template is expected in Q1 2006 to address the prepayment exposure of loans. Like the application of CDS on ABS, a standardized, tradable loan CDS could expand the synthetic loan market exponentially – a trend certainly worth watching. On the ABS side, the CDS market will also be extended to other ABS asset classes such as autos, credit cards, and CDOs. Furthermore, the launch of the ABX index (on January 19th, 2006) could provide another dimension to taking on or hedging risk in ABS.

FAS 140 proposal could significantly expand synthetic CDO investor base

Additionally, a proposed amendment to FAS 140, which changes the accounting treatment of synthetic CDOs, could impact the market dramatically in 2006. Many investors are unable to participate in synthetic CDOs because of accounting bifurcation and mark-tomarket (MTM) treatment of the CLN issued by the synthetic CDO. The amendment would align the credit risk exposure of the CLN issued by the synthetic CDO, thereby mitigating the bifurcation and MTM issues and reducing the P&L volatility associated. The proposal could greatly expand the investor base for synthetic CDOs. On the demand side, given a continuing low yielding and low volatility environment, CDOs still offer very attractive spreads and thus we expect the appetite for CDO products to remain strong. In Exhibit 17, we list our issuance projections for each CDO sector and briefly comment on their justification.


14

31 March 2006

Exhibit 17: 2006 Issuance Forecast CDO Sector

2005 Actual

Change (%)

2006 Projection

Reason

HY CLO

$46.4

flat

$46

Expect institutional loan issuance to decline.13 Collateral spreads to remain tight or range-bound, chipping away at CLO equity returns.

MML CLO

$11.3

up 10%

$12.5

More hedge fund participation in lending to small & medium sized companies.

Mezzanine SF CDO

$24.6

down 15%

$20.9

Decline in supply as refinance activity shrinks; profit margins for lenders tight; slowdown in home price appreciation.

High Grade SF CDO

$51.0

down 10%

$45.9

Same as above, except decline is less as there are more senior HEL bonds.

$15.7

up 15%

$18.1

Real estate fundamentals remain in place with property values in good shape; Low long-term interest rates; Strong demand for CRE assets.

CDO^2

$5.5

up 10%

$6.0

Record CDO issuance since 2004 drives supply; improving technology to analyze complexities of CDO^2 transactions; rise of CDO hedge funds.

TruPS CDO

$9.7

up 10%

$10.6

Early vintage bank TruPS reaching 5-yr non-call; proliferation of REIT TruPS as stand-alone CDOs or as collateral for hybrid TruPS CDOs.

Market Value CDO

$5.1

up 10%

$5.6

Evolution of market value technology and better management flexibility.

CRE CDO

$16.6*

up 50-100%

NA*

New product innovation: ISDA template for CDS on loans expected, ABX Index, continued growth of CDS on ABS and expansion into other ABS areas such as consumer products, CDOs, etc.; amendments to FAS 140 should expand demand significantly for synthetic CDO.

EM CDO

$1.1

up 10%

$1.2

EM economic growth to continue in 2006, especially in China; most EMs have tame inflation.

Other

$3.0

flat

$3.0

Total

$188.0

up 5-12%

$210.0

Synthetic CDO

While SF CDO issuance, the lion's share of the US CDO market, is expected to drop, we believe the CRE CDO and synthetic markets will make up the difference.

*Because of the private nature of many synthetic transactions, issuance figures reported may be much smaller than actual. Source: Credit Suisse

13 Please see "Leveraged Finance Strategy Outlook 2006", 1/16/2006, Credit Suisse Global Leveraged Finance Strategy and Portfolio Products Team


15

31 March 2006

170 total CDO managers in 2005

#4. Manager Selection: Raising the bar 2005 saw 170 managers (of which 58 were new) crowd the CDO market; that’s almost one manager every two days! A breakdown by the top 3 asset classes reveals 75 managers in the CLO space, over 65 managers in the ABS CDO market, and 23 managers in the CRE CDO arena.14 Managers entered the CDO space from three directions: new managers entered the accommodative environment in droves, while seasoned managers returned to their assets of expertise and/or ventured into new asset classes.

Little to no spread tiering among managers

With little to no spread tiering among managers in the past year, it seems the market has not priced in the benefit of a strong manager or the risk of a poor one. Robust demand for CDOs coupled with a benign credit and favorable housing environment, helped drive this trend. We believe that so long as these factors remain in place, tiering will not occur. As we discussed earlier, we do not believe the credit cycle will be turning in the near term nor will there be a dramatic collapse in the housing market. However, with managers dipping further down in credit for spread, it will become more crucial to be selective in picking asset managers. But how do we accomplish this? What should we look for?

Having “managed through the cycle” is not the only criteria

The simple response we often hear from investors is to pick managers who have “managed through the cycle.” This limits investors to a handful of managers in the market for longer than five years. While the HY CLO market has been active over a relatively long timeline, we count only 24 of the 75 managers who issued a deal in 2005 as having issued a deal between 1998-2001, too. The ABS CDO market has only been around since 2000, and pre-2003 deals are significantly different from deals post-2003. For any manager, we think investors should ask the following questions: 1.

How important is the CDO business to this manager? I.e., is this their primary business? And if not, how does it compared with its other businesses? We prefer repeat and bigger managers, or small/new managers with extensive experience at their previous employer – a bigger manager with a good track record.

2.

What is the manager’s background and core experience?

3.

What is the manager’s investment philosophy and does it fit your criteria?

4.

How does the manager deal with distressed/defaulted assets? What is the manager’s experience with work-outs in the case of certain assets?

5.

Does the manager re-rate each asset or follow rating agencies' ratings? How good is the manager's internal credit monitoring system?

6.

For SF CDOs, does the manager have an internal rating system for originators and servicers?

7.

Does the manager have a strong credit research team?

8.

What kind of systems/modeling software does the manager use?

In addition, prudent investors should also request historical equity returns, ratings performance, and lists of past credit risk sales and portfolio purchases where available. Furthermore, we think structural features like key-man provisions help protect investors.

14 Overlaps exist, i.e. there may be a manager that manages both CLOs and ABS CDOs. This is counted once for each asset class managed.


16

31 March 2006

#5. Rating Methodologies Recently, each rating agency released a revision or improvement to its rating methodology. Just to name a few: Moody’s introduced its Correlated Binomial Model for SF CDOs in September 2005; S&P released a new version of CDO Evaluator (see Strategy section); and Fitch made accessible the ability to model Leveraged Super Senior structures in its VECTOR model. We expect this trend to continue in 2006 as more new products and/or structures emerge and more empirical data and better modeling techniques become available. It is critical for all participants to stay on top of any change to the “rules”, as minor changes in criteria or assumptions could have major consequences to primary and secondary markets.

Closing thoughts In 2005, the US CDO market reached a new milestone by surpassing all issuance expectations, breaking new ground in synthetics and in its applicability as an arbitrage, balance sheet, and term financing tool. Looking towards 2006, the credit and economic environments appear set for another solid year, while the housing market, with glimpses of softness, may still have some steam left. The stage is set for the synthetic CDO market to make waves in the US and we reiterate the importance of diligent manager selection as spreads remain range-bound and managers dig deeper for yield. As we make our way to the “back nine” of 2006’s CDO market, we look forward to being your caddie along the way, helping you navigate on the fairway.


17

31 March 2006



18

31 March 2006

Structured Finance CDO Primer15 Overview Four main factors contributed to the growth of SF CDOs

First introduced in 1999, in just six years, structured finance CDOs (SF CDOs) have become a mainstay of the US CDO market, comprising of about 51% of the market, or $91bn in 2005 (Exhibit 18 and Exhibit 19).

1) Historically stable SFS credit performance

Structured Finance Securities (SFS) have historically exhibited more stable credit performance. About 90.47% of triple-B SFS, including ABS, CMBS, CDO and RMBS, remained in the same rating category over the course of a year, versus 88.25% for triple-B corporates, and 82.26% and 81.66% for double-B and single-B corporates, respectively.16

2) SF CDOs capitalize liquidity premium on sub SFS

SF CDOs opportunistically capitalize the liquidity premium on subordinate SFS. Historically, subordinated classes, e.g., triple-B SFS, carry more liquidity premium than corporates, in part due to relatively small tranche sizes, a limited investor universe, and, sometimes, structural complexity. Thus SFS have offered wider spread than corporates. SF CDOs, largely a buy and hold vehicle with limited collateral trading, are ideal for capitalizing the collateral’s liquidity premium. By securitizing and tranching a pool of mezz and subordinated SFS, SF CDOs create higher-rated and likely more liquid senior classes, and in the meantime, leverage collateral liquidity premiums to generate attractive equity returns. At times, SFS spreads have widened out due to market technicals as opposed to heightened credit risk, such as the reduced liquidity in the aftermath of 9/11 in 2001. Ramping-up SF CDOs during times like these may result in greater collateral spread and greater excess spread, enhancing equity returns.

3) SF CDO bonds are higher yielding

Historically SF CDO bonds have traded cheap to other CDO products. SF CDOs have generally priced wider than most other structured products, resulting in better relative value for investors in SF CDOs. This is due, in part, to the relative newness and complexity of this product. For example, BBB SF CDO tranches still offer significant spread pick-up versus other CDO types and structured products in general.

4) An increased issuer participation

Other factors propelling the growth of SF CDOs include increased participation from a variety of issuers. Over time, SF CDOs have attracted a new genre of issuers, including hedge funds and specialty structured finance investment companies. In seeking viable-term funding in the aftermath of the 1998 LTCM/Russia crisis, hedge funds such as TCW, Ellington Capital, Vanderbilt Capital and Maxim Advisory have repetitively utilized SF CDOs to secure more stable term funding. To achieve more efficient funding, specialty structured finance companies such as SFA, C-BASS, GMAC and Fortress Investment also have become repeat CDO issuers, mainly in real estate CDOs. In addition, money managers such as PIMCO, Rabo, Independence, Oppenheimer Funds, and Deerfield are repeat CDO issuers, and have continued to broaden their product types, including issuing SF CDOs.

Basic Terms of SF CDOs A typical timetable

To understand how SF CDOs work, we first illustrate a typical CDO timetable (Exhibit 18). Similar to cash flow HY CDOs, non-static pool cash flow SF CDOs often have a ramp-up and reinvestment period, which often falls within a non-call period. For example, the Pacific Shores CDO, which closed on June 27, 2002, had a 60-day ramp-up period, a 3year reinvestment period and 4-year non-call period.

15 This section was originally written by Neil McPherson, Helen Remeza, and David Kung, March 2003; sections in bold have been updated as of March 2006. 16 Sources: “Structured Finance Ratings Transitions: 1983-2005” February 2006, Moody’s Investors Service.


19

31 March 2006

Exhibit 18: A typical SF CDO timetable Pricing/Closing

Step-up or Auction Call date

Legal Maturity

3 to 5 years Start of portfolio warehousing

Ramp up

Reinvestment

Non-call period

Pay-down period Call period

3 to 5 years 8 to 35 years Source: Credit Suisse

Exhibit 19: Deal Terms – Pacific Shore CDO terms Basic Terms Deal Type: Assets: Closing Date: Target Par Amount: Ramp-Up Period: End of Reinvestment Period: Interest Payment Frequency: Reinvestment Period: Non-Call Period*: Auction Call Date: Maturity Date

Cash Flow ABS CDO ABS, CMBS, RMBS, CDO (See Exhibit 6 for detail) June 27, 2002 $705.5 million (Upsized from $600mm) 60 days from closing (90% ramped up at closing) May 2005 Quarterly, beginning October 3, 2002 3 years 4 years 10 years May 2037 (35 years)

*After the call date, all of the Class A Notes, Class B Notes and Class C notes may be called by a majority vote of the holders of the Preference Shares. Pricing Table Rating WAL (Years) Tranche Size % of Deal (Moody's/S&P/Fitch) Coupon A $532,000,000 75% Aaa/AAA/AAA 5.6 L + 47 B-1 $96,000,000 14% Aa2/AA/AA 10.0 L + 89.5(1) B-2 $16,000,000 2% Aa2/AA/AA 10.0 L+75 C $28,000,000 4% Baa2/BBB/BBB 7.5 L + 230 PS-CL1 $21,500,000 3% Ba3/BB-/BB-(2) --PS-CL2 $7,000,000 1% Ba3/BB-/BB-(2) --Pass Through Notes (3) $5,000,000 1% ---(1) This is the max rate for this auction rate note class. (2) This is a principal only rating. (3) The class is a combo note with a small equity participation. Source: Credit Suisse, IFRMarkets, MCM & Bloomberg

The deal pays 25bps of senior and 25bps of junior management fees to PIMCO, plus an incentive fee of 20% of equity cash flows after a 12.5% IRR is achieved. 17 The fee structure is negotiated up front, and often differs from one deal to another. While a senior fee supports a manager’s ongoing operations, a junior and/or an incentive fee helps to align the manager’s interests with those of subordinate holders. The pricing table above indicates a 4% enhancement to triple-B. Rating agencies generally permit higher leverage for SF CDOs than for HY CDOs, mainly because the average collateral credit quality for SF CDOs is investment grade, i.e., far less likely to default than high yield bonds.

17 “Senior” fees are paid at the top of the waterfall and are thus more likely received by the manager than “junior” fees, which are paid further down at the bottom.


20

31 March 2006

The deal term of SF CDOs differs from HY CDOs

Compared to HY CDOs, the deal term of SF CDOs differs in several ways. The legal final of SF CDOs is often longer due to long collateral, i.e., a 30~35-year legal final versus 12 years for HY CDOs, though the expected final of SF collateral is actually far shorter than its legal final. In addition, for arbitrage-driven trades, the ramp-up period of a SF CDO may be longer (typically ranging from 3~6 months), partly due to a thinner subordinate SFS market. Some key structural innovations addressing these issues include step-up coupons, auction calls, put options, turbo mezz and dynamic funding.

Collateral Analysis Once a SF CDO is closed, sales proceeds are used to fund the collateral portfolio. At closing, non-static investment-grade SF CDOs are often partially funded (typically at least 50%) with a “warehouse line” and with a required amount invested in investment-grade SFS. Key portfolio guidelines

To help in tracking a dynamic pool of credits (most CDOs are managed pools, which allow for limited reinvestment and trading), rating agencies have established a set of criteria to maintain the consistency of collateral as the deal evolves, versus its initial pool. Some of the key guidelines include trading limitations, diversity and min/max collateral spread requirement, rating, coupon, average life, name or industry or issuer or servicer concentration.

SF CDOs also In most SF deals (as SF CDO collateral), the issuer as servicer is responsible for loan impose servicer payment collections and delinquent management. In consumer finance transactions, however, servicer troubles may lead to declining servicing quality, and this can potentially concentration limits impact bond performance. To mitigate this risk, SF CDOs often limit exposure to single servicer, in a sense similar to HY CDOs, which limit exposure to single credit. A lower-rated servicer is subject to a tighter limit. For example, in PIMCO’s Pacific Shores CDO, the maximum concentration for below ‘A-‘ or ‘A3‘ or ‘S2’ rated servicers is 7.5%, while the limit is 10.5% for ‘A3’ or higher but below ‘Aa3’ rated servicers, and 15% for ‘Aa3’ or higher rated. Diversity/sector scores were originally used to measure diversity diversification

To limit sector concentrations and quantify portfolio diversification, rating agencies have developed their own measures of correlation. A detailed discussion on this topic is beyond the scope of this report. We discuss briefly Moody’s methodology. Moody’s original diversity/sector score reflects the impact of sector concentration and correlated defaults.18 For example, a well-diversified portfolio (i.e., the asset default correlation is lower) is less susceptible to name-specific risk and often achieves a higher score. Compared to HY CDOs, typically SF CDOs are assigned a lower diversity score, i.e., a 20 Moody’s diversity score vs. over 40 for HY CDOs. Moody’s have revised their methodology in September 2005 and introduced their new “correlated Binomial Expansion Technique (BET)”.19 The new model uses asset correlations, rather than default correlations in diversity score calculation, in Moody’s CDOROM model, which is a model to derive the loss distribution of the underlying collateral pool.

SFS Rating Stability Historically SFS exhibited better rating stability…

One particularly appealing aspect of SF CDOs is that historically SF collateral has exhibited better rating stability than corporate bonds. For example, About 90.47% of triple-B SFS, including ABS, CMBS, CDO and RMBS, remained in the same rating category over the course of a year.

18

Moody’s Approach to Rating Multisector CDOs, Moody’s, September 15, 2000. Moody's Modeling Approach to Rating Structured Finance Cash Flow CDO Transactions, Moody's, September 26, 2005. 19


21

31 March 2006

Guaranteed SFS are more exposed to more concentrated risk

Corporate guaranteed, wrapped bonds and SF deals backed by “lumpy” collateral may be exposed to more concentrated risk (event risk). Event risk is more significant in less diversified SFS deals, including airline-linked aircraft lease deals (EETC and to some extent pooled ETC) and CMBS large loan deals, and in corporate guaranteed structured securities. For example, some non-IG (investment grade) SFS are guaranteed by originators, who are typically IG at origination. Should collateral credit quality erode and impact the credit worthiness of the bond, these institutions have a contractual obligation to guarantee the bond payments. The credit risk of these bonds is thus linked to a single company, and this introduces event risk. For example, there were 32 defaults in the manufactured housing (MH) market in 2002; all of them were corporate guaranteed by either Oakwood or Conseco, both of which filed for bankruptcy.

SFS Recovery Value High recovery for real estate SFS is partly due to hard collateral or “B&M”

Another appealing aspect of SFS historically has been that they have generally achieved higher recovery values than corporate bonds, in part thanks to the secured nature of select products such as RMBS and CMBS. These are mainly backed by hard assets, the “bricks and mortar” type. Also while corporate bonds, once defaulted, usually stop receiving payments, SFS typically continue to receive cash flow for quite some time after default. Based on all defaults, S&P’s recovery study of September 2002 suggests RMBS and CMBS achieved a high recovery rate, 60% and 83%, respectively, while the ABS average recovery rate reached 45% (Exhibit 20). 20 Across the new defaults observed during June01~June02, S&P suggests RMBS and CMBS recovered about 98% and 87%, respectively, while the average ABS recovery rate reached 62%. Also, excluding the securitizations of charged off credit card receivables (including the three fraudulent CFS deals) and synthetic deals, ABS recovered at a higher rate (77%). We should note that the number of 'D' rated classes increased by 64 to 178 over the oneyear period ending June 2002 from the previous 114 over a 15-year period, in part due to the currently weak credit environment. Nevertheless, it appears that SFS continue to exhibit low defaults, as only 178 SFS classes were ‘D’ rated across 18,500 US SFS S&Prated classes over the past 16 years.

Exhibit 20: S&P Suggests SFS Exhibited Relatively High Recovery Rates RMBS CMBS ABS Original New Defaults All Defaults New Defaults All Defaults New Defaults All Defaults Rating Count Recovery Count Recovery Count Recovery Count Recovery Count Recovery Count Recovery AAA 3 96% 2 93% 2 93% AA 3 91% 20 75% 1 89% A 2 93% 3 66% 1 0% 7 71% 17 38% BBB 4 83% 17 67% 10 37% 10 37% BB 4 94% 15 67% 8 97% 9 97% 5 65% 7 46% B 5 75% 30 36% 10 98% 16 79% 3 100% 5 60% CCC 1 100% 1 100% All / Avg. 19 87% 89 60% 18 98% 27 83% 27 62% 41 45% *The inception of the study is 1985, 1985 and 1978 for ABS, CMBS and RMBS, respectively. Source: S&P, Credit Suisse

We offer the caveat that S&P’s SFS default definition and recovery calculation requires careful interpretation. For example, S&P’s “maximum possible recovery” assumption implies some optimism, as its recovery value calculation is based on the current cumulative loss without giving consideration to likely future losses (from the calculation date onward to the final maturity). However, S&P considers a bond experiencing an “interest shortfall” (S&P defines this as missing a dollar of the scheduled interest payment) to be a defaulted security. The implication of this is that should the erosion continue, it may lead to a lower future recovery; or should the interest shortfall be cured, it may imply a 100% future recovery. That having been said, we think the overall SFS recovery rate is respectable thus far, and this has positive implications for SF CDO investors. 20


S&P structured finance recovery study, September 2002.

22

31 March 2006

Structural Considerations Coverage tests

Similar to other CDOs, SF CDOs are often structured with coverage tests such as overcollateralization (OC) and interest coverage (IC). Should actual OC/IC fall below the test level, usually excess spread is first used for reinvestment or paydown of senior notes to bring the test back into compliance. An initial OC cushion is defined as the difference between the initial OC and OC test level, and it varies by deal, tranche rating and structure. While OC tests are often the first line of defense for senior note holders should undue par erosion occur, IC tests generally are structured with a much larger cushion.21

Several structural features aimed to shorten bond WAL

Besides the coverage tests, there are a few unique features in long legal maturity CDOs like SF CDOs. To shorten the average life of liabilities, SF CDOs often build in some unique structural features, such as a liability coupon step-up, auction calls, and turbo paydowns. Sometimes to shorten average life, on a secondary basis, CDO investors may buy a put option with a customized exercise date. We will explain some of these features in more detail in the discussion that follows.

Step-up coupon motivates manager to call the deal

Step-up Coupon. For example, in both the DASH and Bleecker CDOs, in year 12, the mezz coupon will step-up by a large margin, i.e., 500bps, giving more incentive for equity holders to call the deal as this drains available excess spread cash flow. Should the collateral credit profile remain healthy, this feature will likely result in a shorter average life for liabilities. In other words, managers are likely to retire a portfolio of seasoned and wellperforming SFS, as managers will try to avoid a steep penalty to equity returns due to the coupon step-up. The call may not be attractive to the manager, however, if the pool becomes credit impaired or trades well below par.

Early paydown of mezz to build OC

Turbo Mezz. During the reinvestment period (typically the first three to five years) of a SF CDO, some deals utilize a portion of excess interest, i.e., after a predetermined equity dividend hurdle or “capped equity return”, to amortize the mezz tranche before the inception of a paydown period. This is known as the “turbo” mezz or “turbo” triple-B feature. This allows the mezz OC cushion to slowly build up and enhances mezz. From the senior’s perspective, this replaces subordination with OC. In addition, it enhances available excess spread as more expensive mezz liabilities are paid down. Furthermore, the early principal payback shortens the average life of the mezz tranche ultimately and may also reduce the expected principal losses in high default scenarios. Across the 10 SF CDO universe we track, we found an average 8% annualized turbo paydown during an average seasoning of 10 months.22

Auction call

Auction Call Redemption. This is another common feature with long maturity CDOs. Barring any unexpected credit deterioration in the pool, it is likely that an auction call will be in-the-money. Typically, after the tenth anniversary of a transaction, the CDO trustee is required to conduct auction calls on a regular basis, soliciting bids on the collateral pool from interested parties to retire the notes. The auction dates often coincide with payment dates. If the notes have not been redeemed in full prior to the tenth year, there will be a continual mandatory auction call process until all notes can be redeemed in whole at once.23 In addition, after year-10, typically all excess spread will be used to pay down liabilities. Auction call redemptions are likely to enable an early return of principal, and, as such, shorten the average life of CDO liabilities. At the auction call date, two things are 21 This is partly due to the forward interest rate curve assumption and to some extent other tests such as the weighted average spread (WAS) test and weighted average coupon (WAC) test have already addressed the interest coverage. 22 We note that the turbo mezz is a recent feature, thus we only have limited history. Also see our special report “Turbo triple-Bs in ABS CDOs”, published in Nov. 2002. 23 The trustee, in behalf of the collateral manager, certifies a successful auction if the sale proceeds from the collateral which, together with the balance of all eligible investments and cash in the accounts (other than the Hedge Counterparty Collateral Account and the Cash Flow Swap Counterparty Collateral Account), will be the total redemption amount of notes (often including accrued/deferred interest), plus the greater of 1) zero, and 2) the aggregate initial purchase price of the equity, minus the total cash distributions on the equity.


23

31 March 2006

likely to have happened: 1) the collateral would have seasoned, i.e., stabilized with respect to credit (and prepayments if applicable), and shortened its remaining average life, possibly being sold at tighter spreads (or higher prices); and 2) the triple-B would have been partly paid down from debt turboing, reducing the amount of outstanding CDO liabilities. Both of these may result in an in-the-money auction call; i.e., the value of the collateral pool being greater than the value of the liabilities. Separately, after the regular non-call period expires, equity holders are increasingly likely to call the deal, as the CDO may have de-levered from mezz turboing and collateral paydown, which reduces the leverage and arbitrage. We caution that should collateral credit deteriorate, both the auction call and the regular call become less likely to be in-the-money. Dynamic funding allows for a longer ramp-up

Finally, SF CDOs sometimes require longer ramp-up, partly due to limited collateral supply. Some structural remedies include a dynamic funding mechanism such as variable funding notes (VFNs) or delay draws, and the issuance of additional notes.24 Dynamic funding alleviates negative carry during the ramp-up period, reducing time pressure in acquiring the target portfolio. In some dynamic funding structures, the liability outstanding amount increases in sync with the CDO portfolio balance through the issuance of additional notes, subject to pre-negotiated rating agency conditions. In other cases, CDO liabilities are structured as revolving credit facilities such as VFNs or delay draws, which offer more flexibility in funding and can be drawn down at short notice. The VFNs can be particularly attractive to short-term LIBOR funders like ABCP conduits. Besides the above unique features, SF CDOs continue to be fine-tuned. Some recent structural refinements include applying a par haircut for deep discount purchases, and triple-B or below rated collateral, and the rapid amortization of mezz SF CDO tranches.

Arbitrage and Performance Indicator Credit Suisse’s MAP For arbitrage-driven cash flow deals, a key consideration is the “arb” level. To track the monitors SF CDO “arb” or “excess spread” for SF CDOs or Multi-sector CDOs, we introduced a tool called Multi-sector Arbitrage Pointer (MAP) (Exhibit 21, Appendix I). It is similar to the commonly arbitrage cited “HY-CBO arb,” except MAP reflects the market conditions specific to the structured finance collateral contained in SF CDOs. It captures both the excess spread between assets and liabilities, and the implications for the return on equity (ROE) in one number. In other words, MAP’s utility lies in providing some direction on new issuance volumes and expected ROE. If higher excess spread is indicative of less liquidity rather than poor credit quality, a higher MAP in combination with higher leverage, enhances ROE. For example, a 150bp MAP in combination with a 20 leverage ratio indicates a 30% zero default ROE. Under realistic default scenarios, strong return on equity generally spurs CDO issuance.

Exhibit 21: Multi-sector Arbitrage Pointer (MAP) 150

Excess spread in bps

120 90 60

66

30 0 Oct- Jan- Apr- Jul- Oct- Jan- Apr- Jul- Oct- Jan- Apr- Jul- Oct- Jan- Apr- Jul- Oct- Jan01 02 02 02 02 03 03 03 03 04 04 04 04 05 05 05 05 06


24


“Dynamic funding in cash flow arbitrage CDOs,” Fitch, February 2003.

24

31 March 2006

Closing remarks

Key catalysts for sustainable stable SF CDO performance include healthy ABS credit behaviour, continuous CDO structural refinements and prudent execution. As with all CDO products, we advocate a close scrutiny of collateral, structure and manager. Compared to most other structured finance securities, SF CDO bonds remain higher yielding across the credit spectrum. We like well-structured SF CDOs backed by carefully selected collateral and managed by reputable issuers seeking a long-term market presence.

Appendix I. Calculation of MAP and LAP Our Multi-Sector Arbitrage Pointer (MAP) and Leveraged-Loan Arbitrage Pointer (LAP) reflect the excess spread between assets and liabilities in structured finance/multi-sector (SF/MS) CDOs and Collateralized Loan Obligations (CLO), respectively. An increasing MAP or LAP suggests higher arbitrage and thus higher return on equity, making it more attractive for issuers for potential new deals. We derive MAP and LAP using two static “generic” collateral portfolios with defined sector and rating allocations typically found in CDOs. These portfolios are adjusted over time to reflect the actual asset allocation better across different vintages. The chart below shows the current asset allocation for MAP and LAP calculation:

Exhibit 22: MAP/LAP Collateral Composition* LAP

MAP

Jumbo RMBS 10%

Corp. REIT 2% 1%

CDO 10%

CMBS 5%

Alt-A 10%

CC 2%

BB Inst. Loans 32%

HEQ 60%

B Corp. Bonds 4%

BB Corp. Bonds 1%

B Inst. Loans 63%


We note that the collateral loan spreads are based on CS’s Leveraged Loan Index, high yield bond spreads are based on CS’s High Yield Index, and investment grade corporate bond spreads are largely based on CS’s Liquid U.S. Universe Corporate Index (LUCI), where only larger and/or more Exhibit 23: MAP/CAP Liability liquid names are included.

Capital Structure AAA AA A BBB Equity

MAP

LAP

80%* 10% 1% 5% 4%

74% 5% 7% 6% 9%

* 70% senior AAA, 10% junior AAA Source: Credit Suisse,


The cost of funding is approximated by the weighted-average liability spreads. Please refer to the table on the left for the capital structures used. We then take the difference between the aggregate asset spread and the cost of funding, less 50 basis points for management fees and other costs.

25

31 March 2006

High Grade SF CDO Primer: Q&A25 In this section, we introduce high grade cash flow structured finance (SF) CDOs. We answer some key questions related to collateral, structure, and investor considerations. In general, high grade SF CDOs are backed by high quality diversified structured finance pools with an average rating of double-A. The short-term notes issued by these deals offer an attractive spread pickup vs. other money market alternatives, while they are protected by structural subordination, and to some extent credit enhanced by the put provider. Also, the liquidity of the short-term notes is enhanced by the put provider and the relatively large size of these notes.

What are high grade SF CDOs? The collateral for high grade SF CDOs is mainly highly rated structured finance paper, which is typically rated at least single-A with an average rating of double-A. Some common structured finance sectors included in the collateral pool are real estate ABS (Resi B&C/HEL), CDO, CMBS and other ABS. High grade SF CDOs can be done on a funded (cash flow) or synthetic basis. The decision between a cash flow vs. a synthetic execution is mainly driven by considerations such as funding, balance sheet and/or consolidation considerations. In this piece, we focus on cash flow high grade SF CDOs.

What does a typical collateral pool look like? The average collateral credit rating for high grade SF CDOs is typically double-A, while no assets are rated below single-A (Exhibit 24). The deals are primarily backed by floatingrate collateral, and therefore there is very little asset/liability mismatch assuming most liabilities issued are floating rate. There are also portfolio concentration limits for private securities, PIK bonds, synthetic securities as related to counterparty exposure, and for previously troubled sectors such as MH and some esoteric ABS. If the assets are highly rated, i.e., triple-A, there can be no limit on exposure. The concentration limit also varies across collateral rating and servicer rating. For higher rated collateral, the concentration limit is higher, i.e., 2%~2.5% for triple-As, while for lower rated collateral, the limit is lower, i.e., 0.5% for single-As (Exhibit 25). Similarly, while generally servicer limits are between 7.5% to 10%, a deal may have as much as 12.5% exposure to a higher rated servicer and 7.5% to a lower rated one (Exhibit 25). Collateral pools can be static or revolving, with revolving pools often allowing for 10% to 15% per annum of discretionary trading.

25


This section was originally written by Neil McPherson, Helen Remeza, and David Yan, July 15, 2004.

26

31 March 2006

Exhibit 24. Collateral characteristics for four recent of high grade cash flow SF CDOs Deal Name

Klio Funding

Lakeside II

Blue Bell Funding

Grenadier

Collateral Rating

At least 85% ‘AA-‘ rated

Min WA Rating btw AA & AA-

Min WA Rating btw AA+ & AA

At least 90% 'AA' rated, avg AA/AA-

Min WACoupon on Fixed Collateral Min WASpread on Floating Collateral Max Fixed-Rate Securities Max Floating-Rate Securities Min Rating Max Rated Less than 'A-' Max Discretionary Trading of Portfolio Max WALife (Years) Portfolio Composition (%) Consumer Asset-Backed Securities Commercial Asset-Backed Securities HEL, Resi A/B/C CMBS Max Pure Private Securities Max Payment-in-Kind (PIK) Bonds Max CDOs

N.A.

5%

6%

N.A.

0.70% 0% 100% 'A-' 0% 10% 8 Target N.A. N.A. 70% (max) N.A. N.A. 5% 40%

0.79% 20% 90% 'A-' 0% N.A. 7.5 Target 0 0 57% 5% 5% 5% 50%

0.90% 40% 70% 'A-' N.A. 15% 8 Target 0 0 43% 38% 10% 3% 20%

0.55% N.A. 100% 'A-' N.A. 15% 7.5 10% 0 0% 5% 12.5%

Klio Funding

Lakeside II

Blue Bell Funding

Grenadier

Bear Stearns Asset Management Inc.

Vanderbilt Capital Advisors, LLC

GMAC Institutional Advisors LLC

ACA Management

4/23/04 90 5 1,263mm 1,074mm

3/31/04 180 N.A. 1,502mm 1,170mm

12/12/03 90 5 1,250mm 1,112mm

7/14/03 180 5 1,500mm 1,320mm

2.5% 1.5% 0.5% 10%. N.A. N.A. N.A.

2.0% 7.5% -

2.5% 1.5% 0.5% 10% N.A. 12.5% 10%

2.0% 1.5% 0.5% 7.5% 12% N.A. 7.5%

Source: Credit Suisse, Fitch, S&P.

Exhibit 25. Examples of high grade cash flow SF CDOs Deal Name

Collateral Manager Closing Date Ramp-Up Period (Days) Reinvestment Period (Years) Deal Size Size of the ABCP Notes Concentration Limit Maximum Single Issue (%) 'AAA' 'AA-' or Higher 'A-' or Higher Maximum ABS Servicer Concentration (%) ‘AA-'/'S1' or Higher ‘A-'/'S2' Below 'A-'/'S2' Source: Credit Suisse, Fitch, S&P.


27

31 March 2006

Why is the size of these deals so large? Currently, the deal size of high grade SF CDOs typically ranges between $700mm and $1.5bn, which is larger than that of an average CDO. There are several reasons for this. Investors in senior structured finance paper tend to have larger allocations. This is because the majority of the investors are banks and large institutional investors who manage large money market funds, while highly rated tranches or senior classes are often sizable, allowing for larger allocations. For example, a typical allocation to a senior investor in a $500mm deal is often in the range of $20~100mm. In addition, in order to achieve portfolio diversification, CDOs generally apply single-issue concentration limits. For example, a 2% single-issue limit can be translated to a minimum of 50 bonds per deal. Assuming a $20mm allocation per bond in the pool, this corresponds to a deal size of $1bn. Buyers of the senior tranche of these deals (often short-term notes) are mainly money market investors, who also prefer a larger deal size due to liquidity concerns. Larger deals tend to have bigger senior classes, which in turn may be distributed to more investors, resulting in likely better liquidity. In fact, investors in the short-term paper usually prefer deals that offer $500mm or more in short-term CDO paper. Note all deals in Exhibit 25 issued over $1bn in short-term paper. Clearly, the relatively tight concentration limits in high grade SF CDOs partly determine the deal size. Besides the fact that a larger deal may offer greater liquidity, a tighter concentration limits and/or more portfolio diversification are beneficial to senior CDO investors from a credit standpoint. Exhibit 25 provides more details for the four recent cash flow high grade SF CDOs shown in Exhibit 24.

Why do high grade SF CDOs often issue short-term liabilities? These deals often issue short-term obligations, which are often Rule 2a-7 eligible moneymarket (MM) tranches. Issuing short-term obligations enhances deal economics as it reduces liability cost and enhances excess spread and equity return. Because the collateral for high grade SF CDOs are highly rated, they often carry a lower coupon than that for other CDOs. To maintain a similar level of excess spread, a lower liability cost is desirable. The MM structure typically costs less than a term note structure. We illustrate this in Exhibit 26, where the lower liability cost leads to a 2% additional equity return per annum.

Exhibit 26: MM structure enhances deal economics* Put Premium (bps) Re-Marketing Cost (bps) Class A Coupon (bps) "All-in" Senior Notes Cost (bps) Assumed Leverage "Additional" Equity Returns

Money-Market Structure

Term Notes Structure

20 5 L + 10 L + 35 20:1 2% per annum

--L + 45 L + 45 20:1

* Numbers are hypothetical. Source: Credit Suisse

How do the short-term notes work? The short-term obligations may be issued directly from the CDO trust or a separate trust. A separate trust is sometimes established because if the CDO needs to be a Qualified Special Purpose Entity (QSPE) it cannot issue a short-term tranche (also known as the MM tranche) as a QSPE cannot re-issue securities, according to FAS 140. MM tranches must be reissued at least every year and the re-issuance usually occurs after some shorter time period (on the expected maturity date), for example 30 days, 60 days, 90 days or 6 months. Typically, there are multiple dealers to re-market the notes.


28

31 March 2006

CDOs that issue MM tranches are often structured with an embedded put agreement, from a highly rated put provider, of which the minimum ratings are usually at least P-1/A-1/F-1 by Moody’s/S&P/Fitch. At the expected maturity date, new MM notes are issued through a re-marketing (or re-issuance) process, of which the proceeds are used to retire the outstanding class of MM notes. In the event that the new MM notes cannot be issued at a coupon less than a pre-set maximum rate,26 the put may be exercised, in which case, a new class of notes is often issued. This new class of notes carries a pre-set “maximum” coupon, usually significantly higher than the coupon on the maturing notes. The put provider’s premium and the pre-set maximum coupon are closely related. A put provider could potentially charge a lower premium if the maximum coupon is set at a higher limit or vice versa. Terms are typically dependent on the particular put provider. Other variations of the short-term notes include extendable notes and medium term notes. A typical extendable note may have a 13-month maturity and is remarketed each month. Investors of extendable notes have a monthly option to extend or put the notes. If in any month investors choose to put the notes, the exercise date would be 12 months later. The coupon on the notes may step up over time such that a higher coupon would be realized with continued extension of the notes. A typical medium term note may have a bullet maturity of two or three years accomplished with a put. It can be remarketed in any frequency following the maturity of the initial issuance.

What are some key considerations for investors of short-term notes? Typical investors for the MM tranche of high grade SF CDOs include banks and large institutional investors also securities lenders. Some key investment considerations are as follows. 1.

Investors of short-term notes are credit-enhanced by both structural subordination, and to some extents by the put provider. Like the senior class for other CDOs, the credit risk for a MM tranche is largely reduced through structural credit enhancement, which typically leads to a term triple-A shadow rating for the MM tranche. Put providers mainly provide liquidity. They are obligated to provide funds (or liquidity facility) to retire the maturing notes and purchase the newly issued notes. For this reason, put providers are also referred as liquidity provider. If the put provider is downgraded below certain rating thresholds without an appropriately rated replacement counterparty or sufficient posting of collateral, rating agencies typically require the liquidity facility to be drawn on to maintain the ratings of the short-term notes. While the main role of a put provider is to facilitate the re-issuing of the short-term note, a put provider also credit-enhances the short-term note. For example, even if the note is downgraded due to collateral performance, it can still carry the same rating as the put provider so long as the put provider offers sufficient liquidity for re-issuance. Some deals have certain “out” clauses related to payment default or event of bankruptcy27, others are related to loss threshold or ratings28. If the “out” clauses are triggered, the liquidity facility will not be available to the short-term investors any longer.

26 Or in some cases where the put agreement expires and is not extended, and some other replacement liquidity is not obtained. 27 The initial put option agreement carries at least the same tenor as the maturity of the MM notes, and in most cases, the put provider is only allowed to terminate the agreement in the event of a payment default on the senior CDO notes or a CDO event of bankruptcy. 28 For example, if the CDO does not have the capacity to make monthly interest payments on the outstanding CP notes, or the realized losses on the portfolio have reached a preset level, the liquidity facility will not be available to the ABCP notes investors any longer.


29

31 March 2006

Investors of short-term notes are credit-enhanced by both structural subordination and by the put provider to some extent. However, because of such an association, MM investors often limit their exposure to a single put provider. 2.

Static vs. revolving portfolio Collateral portfolio can be static or revolving. While static pools are easier to keep up with, revolving deals with clean guidelines and managed by a reputable manager can be attractive as managers can play a key role in making collateral investment decisions. Pools backed by shorter weighted average life assets, including highly rated real estate ABS, tend to be revolving, i.e., proceeds from retired collateral can be reinvested in eligible assets to maintain deal leverage.

3.

Collateral selection The average collateral credit rating is high, typically double-A while often no assets is rated below single-A. For investors who are concerned about some previously troubled sectors, high grade SF CDOs often apply concentration limits for synthetic securities, private securities, and PIK bonds, as well as for sectors such as MH, and other ABS such as equipment, structured settlement and timeshare etc.

The demand for short-term CDO tranches mainly comes from MM investors, and it has been healthy. In fact, since the beginning of 2003, money-market tranches have accounted for about 28% of all SF CDO issuance, mainly because the CDO paper offers a good spread pick-up over other money-market alternatives such as high-grade corporates and ABCP. For example, while the CDO short-term paper (with a minimum rating of P1/A1/F1) can offer L+1~10bps, Tier-1 industrial with 1~3month in maturity currently yields L-10 to -7bps and Tier-1 US ABCP offers L-4 to –7bps. In general, high grade SF CDOs are backed by high quality diversified structured finance pools with an average rating of double-A. The short-term notes issued by these deals offer attractive spread pickup vs. other money market alternatives, while they are protected by structural subordination, and to some extent credit enhanced by the put provider. Also, the liquidity of the short-term notes is enhanced by the put provider and the relatively large size of these notes.


30

31 March 2006

A Closer Look at High Grade SF CDOs29 Over the past two years, one of the most significant developments in the CDO market has been the growing popularity of high grade (HG) SF CDOs. To date, the asset class has been well received by the market. We think it is essential to examine the sector closely from both a structural and a collateral perspective, to review some of the recent trends and address some potential investor concern. We examine 39 HG SF CDOs issued since 2004. The result and methodology used serves as a first-cut screen for investors seeking opportunities in HG SF CDOs.

Robust Growth in HG SF CDOs The growth in high grade structured finance CDOs has been substantial: •

43 HG deals priced between January 2004 and early August 2005, totaling approximately $54 billion.

•

Exhibit 27 shows total 2005 YTD issuance of $26 billion, well above the $4 billion issued in 2002. HG deals represent nearly half of the total SF CDO issuance.

Exhibit 27: Robust Growth in High Grade SF CDOs* 60%

$70 High Grade SF CDO ($ BN) Other SF CDO ($ BN)

$60

% Share by $ Issuance

Issuance ($BN)

41%

49%

50%

40%

$28 $26

$40

30% $30 $20 $10

$14

$4

20%

15%

$30

$21

$20

2002

2003

$27

$-

% Share of SF CDOs ($)

$50

48%

10%

0% 2004

2005 YTD

Vintage

* Up to mid-August 2005 Source: Credit Suisse

One reason often cited for the rapid growth in HG SF CDOs is the significant spread tightening of collateral prevalent in SF CDOs. As the arbitrage embedded in the traditional mezzanine SF CDO diminishes, CDO issuers are tapping into higher-rated assets, usually rated Single-A or above. However, we think this is only part of the story. Another driver is, given the unprecedented growth of the US housing market and the outlook for future interest rates, some investors are moving up the credit spectrum to achieve the desired yield through leverage.30

29

This section was originally published in "The CDO Strategist", Issue #7, September 15, 2005. There are two main ways to achieve higher return: moving down the credit spectrum or increasing leverage. 30


31

31 March 2006

The Mechanics of HG Arbitrage How does the arbitrage work for HG CDOs? We address this question from both the liability and the asset.

Structural features lower liability cost Funding Senior Senior Funding: Money Market/ABCP Tranche Notes using Money Most HG deals invest in pools with an average rating of AA, compared to an average Market/ABCP rating of BBB in mezzanine SF CDOs. The high credit quality of the collateral affords a lower subordination or a larger senior tranche, which is typically 80% to 90% of the total deal size. By using short-term funding for the senior notes, the funding cost of the CDO may be dramatically lowered; common approaches include money market (MM) or ABCP tranches.31 However, to match the asset and liability maturities, the short-term notes are rolled, or remarketed, as they mature. Should the remarketing not be successful, a put agreement governed by the ISDA with a highly rated put provider is embedded. When the put is excised, the notes are put to the put provider, who subsequently owns the term notes with a step-up coupon, also known as the maximum coupon. The ratings of these classes are linked to the ratings of the put provider, which are usually F1/P-1/A1. The put provider is compensated with a premium, usually around 20 bps. Money-market notes are often issued in combination with medium-term notes (MTN). The all-in cost for this type of funding is usually around L+35 bps, including the put premium and the remarketing cost. The all-in cost of issuing ABCP tranches, on the other hand, is around L+23/24 bps. It seems that ABCP funding has recently gained popularity over MM/MTN. As shown in Exhibit 28, 22 of the 39 deals in our list use either MM/MTN or ABCP, and all short-term notes in recent deals are ABCP funded.

Term funding the senior notes

Pro rata pay also lowers the funding cost

Senior Funding: Term Notes With senior AAA spreads tightening significantly, current AAA spreads stand around L+25 bps (+/-2 bps), slightly higher than the all-in cost of ABCP funding. Unlike ABCP funding, however, term notes do not have the uncertainty of the ultimate funding costs contingent upon the success of remarketing and exercise of the put option. As a result, some deals opt for term funding if the incremental cost over ABCP is only a couple of basis points. Exhibit 28, shows the split between ABCP and term funding in recent deals at about 50/50. Interestingly, typically when term funding is used, a delayed-draw note is also utilized to avoid negative carry during the ramp-up period. Pro Rata Pay Many deals in our list also incorporate pro rata amortization schedules in the payment waterfall provisions. In these transactions, all rated tranches are paid pro rata until the collateral balance has decreased by half, after which the amortization schedule switches to the traditional sequential order. The pro rata pay is also subject to all coverage tests – if any tests fail, the deal will switch to sequential pay. The reason for the pro rata structure is to pay down the junior tranches with higher costs faster in order to lower the all-in funding cost. Lower Subordination and Higher Leverage As discussed, the subordination requirements for HG deals are lower than mezzanine deals due to the higher credit quality of the collateral, which also lowers funding costs.

31 Commercial Paper (CP) is any high-quality, negotiable note having an original term to maturity of no more than 270 days.


32

31 March 2006

Exhibit 28: Structural Details for HG SF CDOs (2004-2005 vintages, as of Aug 5, 2005)* Deal Name CDO 1 CDO 2 CDO 3 CDO 4 CDO 5 CDO 6 CDO 7 CDO 8 CDO 9 CDO 10 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 17 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 24 CDO 25 CDO 26 CDO 27 CDO 28 CDO 29 CDO 30 CDO 31 CDO 32 CDO 33 CDO 34 CDO 35 CDO 36 CDO 37 CDO 38 CDO 39

Vintage 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

WAR AA+/AA AA AA AA+ AAAA/AAAA/AAAA/AAAA+ AA AAAA-/A+ AA/AAAAAA/AAA+ AA+ AA/AAAA AAA+ AA/AAAA+ AA+ A

AA+ AA+

AAAAA AA+ AAAAA

Equity Size 0.50% 1.44% 2.37% 0.50% 1.91% 1.00% 1.50% 1.50% 1.55% 0.63% 1.71% 2.30% 0.80% 1.49% 1.60% 1.80% 1.79% 1.53% 1.59% 1.67% 2.13% 2.50% 1.50% 1.54% 1.61% 1.49% 0.61% 2.37% 1.60% 0.61% 1.20% 1.54% 1.75% 1.60% 1.84% 0.30% 1.34% 1.40% 0.50%

Senior Funding ABCP Term Notes, Delayed Draw ABCP MM and MTN Term Notes, Delayed Draw ABCP MM and MTN Term Notes, Delayed Draw Term Notes ABCP ABCP ABCP ABCP Term Notes, Delayed Draw MM and MTN ABCP Term Notes, Delayed Draw Term Notes, Delayed Draw ABCP ABCP ABCP Term Notes ABCP Term Notes, Delayed Draw ABCP Term Notes ABCP Term Notes ABCP ABCP Term Notes Term Notes Term Notes Term Notes ABCP ABCP Term Notes, Delayed Draw Term Notes, Delayed Draw ABCP

Senior AAA Spread (bps)

Pro-rata Pay

38 yes (50%) yes (60%) 37 yes yes (50%) 35 35

34 yes (50%) yes (50%) 35 29 yes (50%) yes (50%) 33

27

yes (50%) yes (50%) yes (50%) yes (50%)

32 yes (50%) 23 25 25 23

27 20

yes (50%) yes (50%) yes (50%) yes (50%) yes (50%) yes (50%)

* The list is sorted by pricing date from the earliest to the latest. Source: Credit Suisse, Intex, Moody’s, S&P, Fitch

Collateral sourcing to enhance asset yield Similar to recent mezzanine SF CDOs, the majority of collateral underlying recent HG SF CDOs are home equity (HEL; including home equity and subprime mortgages), RMBS and CDOs. Exhibit 29 shows that, on average, these asset classes account for 52%, 19%, and 19%, respectively. Exhibit 30 shows the rating breakdown of HG SF CDOs; the majority is invested in assets rated Aa3 and above.


33

31 March 2006

Exhibit 29: Collateral Distribution for HG SF CDOs (2004-2005 Vintages) ABS-Auto 0.30%

RMBS 19.27%

ABS-Cards 0.25%

CORP 2.92%

CMBS 4.94%

CDO 18.82%

ABS-Other 1.59%

ABS-HEL 51.67% ABS-MH 0.25%

Source: Credit Suisse, Intex

Exhibit 30: Rating Distribution for HG SF CDOs (2004-2005 Vintages)

A2 12.70%

A3 4.29%

Baa1 0.38%

Baa2 0.15%

Aaa 35.84%

A1 5.68%

Aa3 7.31%

Aa2 26.28%

Aa1 7.37%


A commonly held opinion is that not all AAA bonds are built alike. There are many ways to construct a pool of assets with a weighted-average rating of AA. Below is a list of some methodologies used by HG CDOs to enhance yield.32 1.

Buy slow pay AAA home equity or subprime mortgage bonds. Many AAA bonds in home equity deals are time tranched, i.e., sequentially paid. The spread difference between a 1st priority AAA bond and a last pay AAA bond could be up to 25-30 bps, which accounts for the longer average life of a last pay AAA, normally around six to nine years. The CDO could also invest in AA’s, which offers about 7-8 bps pick-up (versus last pay AAA’s) and offers a shorter average life of around 4.5 years.

32 Because of the high leverage, a small increase in the yield of the underlying assets boosts the return of the equity tranche significantly.


34

31 March 2006

2.

Buy junior AAA CDO tranches. Most junior AAAs, i.e., non-first-priority AAAs, are currently offered around L+45 bps, about 20 bps wider than senior AAAs. Exhibit 31 lists the rating distributions of CDO collateral in select HG SF CDOs. Many deals invest a significant portion in junior AAA CDO tranches.

3.

Buy less well-known issuer names. As an alternative to traditional, more liquid names, HG SF CDOs can pick up spread by investing a portion of the collateral in less popular or less well-known issuer names.33 However, currently, strong demand for HEL paper has resulted in most bonds trading with little to no spread premium, regardless of the issuer name. At AAA to A levels, the difference is around 5 bps at most. Still, given the high leverage, even a couple of basis points will make a significant difference: 1 bps translates into approximately 1% under 100-times leverage.

4.

Buy seasoned paper. There may be relative value opportunities in seasoned bonds, and CDOs often use this approach to pick up extra yield. Exhibit 32 lists the vintage distributions of the underlying collateral assets of select 2004 vintage HG SF CDOs. Some deals invest significantly in seasoned bonds, such as CDO 10.

Exhibit 31: CDO Collateral Rating Distribution of Select HG SF CDOs Deal Name

SNR AAA

JNR AAA

AA+

AA

AA-

CDO 1 CDO 2 CDO 3 CDO 4 CDO 5 CDO 6 CDO 7 CDO 8 CDO 10 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 25 CDO 28 CDO 30

55.3% 3.9% 36.9% 42.6%

44.7% 34.1% 44.7% 28.0% 24.2%

9.1% 1.2% 0.7%

49.0% 17.2% 25.1% 71.6%

1.0%

2.9%

2.5%

1.1%

100.0% 61.5% 17.7% 54.9% 38.2% 7.5% 32.6% 5.8% 40.4% 55.8% 4.2% 21.8% 17.3% 36.6% 25.4%

29.8% 29.1% 21.7% 41.5% 70.2% 13.4% 11.0% 33.6% 9.8% 41.1% 26.6% 27.4% 24.6% 20.8%

2.4%

4.3% 42.2% 17.8% 16.6% 22.4% 46.5% 64.2% 23.5% 22.6% 41.2% 50.1% 52.8% 35.7% 49.6%

3.1% 8.4% 4.7%

45.9% 32.2% 9.3%

4.7% 0.6% 7.5% 2.5% 2.2% 9.0% 1.5% 2.5%

A+

A

A-

4.3% 4.5% 6.2% 5.5% 2.7%

0.4%

2.4%

16.6% 1.3%

8.3%

0.8%

2.2% 1.8%

4.5%

100.0% 27.5% 23.3%

23.5% 8.4% 44.8%

14.0% 4.7%

26.6%

10.5% 13.3%


33


Less popular or less well-known names may, but do not necessarily, have less liquidity.

35

31 March 2006

Exhibit 32: Underlying Collateral Vintage Distribution of Select 2004 HG SF CDOs Deal Name

2005

2004

2003

2002

2001

2000

CDO 1

4.9%

47.2%

28.7%

3.5%

12.4%

2.9%

78.7% 58.6% 60.2% 87.0% 54.2% 49.1% 91.4% 75.1% 71.3% 66.4% 63.7% 87.9% 74.9% 78.8% 88.9% 81.8% 82.7% 77.6% 87.0% 78.7%

12.6% 21.1% 24.2% 11.2% 16.5% 8.5% 2.3% 12.1% 4.1% 15.5% 9.1% 3.9% 16.1% 9.9% 1.9% 2.1% 1.6% 9.5% 2.7% 1.6%

2.5% 2.3% 4.9% 1.8% 3.5% 8.9% 0.5% 0.3% 3.1% 6.5% 3.5% 1.6% 5.0% 2.7% 0.7% 1.9% 0.8% 3.3% 0.7% 0.5%

1.6% 0.7% 3.3%

1.1% 3.6%

2.4% 2.0%

0.2%

0.4% 4.2%

0.9% 8.8%

2.1% 1.0%

9.7% 1.5% 0.1%

0.8% 1.2%

CDO 2 CDO 3 CDO 4 CDO 5 CDO 6 CDO 7 CDO 8 CDO 10 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23

6.4% 1.8% 12.7% 1.9% 5.2% 0.8% 9.4% 7.3% 17.1% 5.7% 0.6% 3.8% 6.9% 8.2% 14.8% 8.6% 7.2% 9.1%

5.4% 3.9% 0.6%

1.4% 5.5% 1.0% 1.0% 1.9% 2.5%

1.2% 1.0% 0.6%

1999

1998

Before 1998 Unknown 0.5% 4.7% 7.3%

3.3% 2.6%

1.1% 11.1%

1.9% 0.0%

0.8%

0.5%

9.7% 0.8% 1.0% 1.3% 1.3% 1.7% 2.9%

1.0% 0.5%

1.8% 10.0%


The Result Now let’s examine whether the arbitrage is economic by examining actual asset and liability spreads. Exhibit 33 shows rough calculations of the aggregate liability cost, WAS, and expected equity IRR under a zero-default assumption for select deals for which we have collateral level details.34 We ignore any hedging issues. Most of the deals have a zero-default IRR from the low- to mid-teens. Some deals have higher IRR due to the relatively lower credit quality of the underlying pool and thus higher WAS, such as CDO 12, 16, 21 and 22. However, because of the lower credit quality, the IRR for these deals will have to be lowered more than the deals with higher credit quality due to the relatively higher default risk. Some deals have higher IRR simply as a result of higher leverage, such as CDO 6 and CDO 13.

34 We obtain the collateral information mainly through Intex. Note that there is usually a lag between when a deal is closed and when it is modeled by Intex. The list is sorted by pricing date.


36

31 March 2006

Exhibit 33: Arbitrage of HG SF CDOs under No-default Scenario Aggregate Deal Name CDO 1 CDO 2 CDO 3 CDO 5 CDO 6 CDO 7 CDO 8 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 25

WAR

Leverage*

Liability Cost (bps)**

AA+/AA AA AA AAAA/AAAA/AAAA/AAAAAA-/A+ AA/AAAAAA/AAA+ AA/AAAA AAA+ A+ AA/AAAA+

200 70 42 52 100 67 67 59 43 126 67 63 56 65 63 60 47 40 67 62

36.59 53.85 31.45 51.14 36.37 36.93 42.54 29.37 36.70 37.49 43.90 33.65 42.21 44.61 32.84 31.04 35.18 40.87 35.11 31.00

Equity IRR WAS (bps)***

under No Default****

57.05 82.29 75.53 88.64 75.15 72.76 81.46 72.62 107.01 69.89 83.23 73.01 93.63 83.14 72.21 68.86 88.74 99.09 66.44 69.73

14.92% 10.73% 13.11% 12.81% 25.73% 15.22% 17.24% 17.71% 24.92% 24.37% 17.71% 16.47% 21.34% 16.68% 16.63% 14.89% 19.07% 18.09% 12.22% 15.94%

* Leverage is calculated as 1 divided by the size of the equity, i.e., 1% equity implies a leverage of 100 times. ** For ABCP tranches, an all-in cost of 24 bps is used. For fixed tranches, an equivalent floating spread is used. *** Only the floating spread is used. **** IRR is calculated as (WAS-Liability Cost)*Leverage. A n all-in fee (senior management fee, administration fees, etc.) of 13 bps is used. Source: Credit Suisse, Intex, Moody’s, S&P, Fitch

How much leverage is too much leverage? One of the biggest concerns investors have regarding HG CDOs is the high leverage. Given the high credit quality of the underlying pool, it is obvious why subordination levels for HG deals are lower than other CDO types. Exhibit 34 shows the average subordination levels of select CDO types at different ratings. However, the question remains: is the subordination level enough to prevent losses to the notes or is the leverage too high? To answer this question, we have to look at the historical experience of the underlying collateral. We found Moody’s impairment study to be one of the more comprehensive sources and we use their results for our study.35

35


Moody's Impairment Rate includes uncured payment default and downgrade to Ca or C.

37

31 March 2006

Exhibit 34: Average Subordination Levels of HG SF CDOs vs. Other CDO Types T rip l e - A A v e r a g e S u b o r d in a t io n

D o u b le - A A v e r a g e S u b o r d in a t io n

30 %

25%

25 %

20%

20 %

15%

15 % 10%

10 %

5%

5% 0%

0% HY C LO

C R E CD O

M e zz S F CDO

HG SF CDO

S in g le - A

A v e r a g e S u b o r d in a t io n

HY C LO

C RE C DO

M e zz S F C DO

HG S F CD O

T r ip le -B A v e r a g e S u b o r d in a tio n

18 %

12 %

16 %

10 %

14 % 12 %

8%

10 %

6%

8%

4%

6% 4%

2%

2%

0%

0% HY C LO

C R E CD O

M e zz S F CDO

HG SF CDO

HY C LO

CRE CDO

M ezz SF CDO

HG SF CDO


Average Subordination Levels of HG SF CDOs vs. Other CDO Types As shown in Exhibit 35, the impairment rates of A-rated and above are much lower than Baa and below ratings, except for Aa-rated ABS. 36 By applying a constant recovery rate of 55% and treating impairment as default, we can derive a loss rate matrix based on Exhibit 35, which is shown in Exhibit 36.

Exhibit 35: Moody's 5-Year Cumulative Impairment Rate by Sector and Original Rating (1993-2004) Rating Aaa Aa A Baa Ba B

RMBS 1.02% 1.45% 1.20% 8.45% 6.05% 14.93%

HEL 0.00% 0.00% 2.35% 6.99% 26.88% 41.13%

CMBS 0.00% 0.00% 0.66% 1.62% 3.75% 16.62%

ABS* 0.95% 11.64% 2.94% 8.43% 32.33% 54.31%

CDO 0.00% 1.67% 6.50% 25.06% 25.56% 53.16%

ALL Structured Finance 0.62% 3.19% 3.23% 11.04% 16.04% 22.38%

* Exclude Manufactured Housing and HEL. Source: Moody’s, “Default & Loss Rates of Structured Finance Securities: 1993-2004”, Moody’s Special Comment, July 2005

Exhibit 36: Derived 5-Year Loss Rate by Sector and Original Rating Rating Aaa Aa A Baa Ba B

RMBS 0.46% 0.65% 0.54% 3.80% 2.72% 6.72%

HEL 0.00% 0.00% 1.06% 3.15% 12.10% 18.51%

CMBS 0.00% 0.00% 0.30% 0.73% 1.69% 7.48%

ABS* 0.43% 5.24% 1.32% 3.79% 14.55% 24.44%

CDO 0.00% 0.75% 2.93% 11.28% 11.50% 23.92%

ALL Structured Finance 0.28% 1.44% 1.45% 4.97% 7.22% 10.07%

* Exclude Manufactured Housing and HEL. Source: Moody’s, Credit Suisse

36


Here, consistent with Moody's study, "ABS" does not include MH and HEL.

38

31 March 2006

Unfortunately, Moody’s study does not give us the impairment rates of intermediate ratings, such as Aa1 or Aa3. To remedy this deficiency, we linearly interpolate the loss rates for these rating levels based on the rates in Exhibit 36. Exhibit 37 shows the results.

Exhibit 37: Intermediate 5-Year Loss Rate by Linear Interpolation Rating Aaa Aa1 Aa2 Aa3 A1 A2 A3 Baa1 Baa2 Baa3

RMBS

HEL

CMBS

ABS*

CDO

0.46% 0.56% 0.65% 0.62% 0.58% 0.54% 1.63% 2.72% 3.80% 3.44%

0.00% 0.00% 0.00% 0.35% 0.71% 1.06% 1.75% 2.45% 3.15% 6.13%

0.00% 0.00% 0.00% 0.10% 0.20% 0.30% 0.44% 0.59% 0.73% 1.05%

0.43% 2.83% 5.24% 3.93% 2.63% 1.32% 2.15% 2.97% 3.79% 7.38%

0.00% 0.38% 0.75% 1.48% 2.20% 2.93% 5.71% 8.49% 11.28% 11.35%


There are several interesting observations that can be made from this matrix: 1.

The loss rates of Aa2 and above for HEL and CMBS are zero;

2.

Overall, CMBS has the lowest loss rate, followed by HEL and RMBS; and

3.

Except for the ABS sector, which excludes HEL and MH, the loss rates at the Aa2 level are significantly lower than the loss rates at Baa2 level.

We apply the loss rates in Exhibit 37 to the underlying collateral of each deal in Exhibit 33 by rating and by sector to calculate an expected loss rate.37 Finally, we divide the equity size by the loss rate to calculate a loss coverage ratio of the most junior tranche. We repeat this analysis for each deal with the results shown in Exhibit 38. We think the overall loss coverage ratio is quite high, as it provides three to four times coverage for most deals. Certain CDOs offer very high loss coverage, such as CDO 3, CDO 11 and CDO 7. Although CDO 13 has the lowest coverage ratio at 1.97, the loss coverage is sufficient since the most junior tranche is rated below BBB-.38 Interestingly, CDO 13 also has a very high IRR under the zero-default scenario because of its high leverage, as shown in Exhibit 33. However, there is a CBO tranche with a Moody’s rating of Baa2 in its collateral pool. This is a situation that investors should examine more closely. Investors need to pay attention to CDO 14, 16 and 18, as their coverage ratios are lower than others with similar ratings. This analysis is a rough estimate requiring further investigation to assess fully the credit support adequacy of each deal. However, our analysis enables us to take a first look at each deal in a relatively efficient way. More detailed analysis needs to be conducted on other tranches as well.

37

We can apply this calculation to all deals if the collateral information is available. The exact rating of this tranche is not available; we only know it is below the BBB- tranche in the capital structure. 38


39

31 March 2006

Exhibit 38: Most Junior Tranche Loss Coverage Ratio of Select HG SF CDOs Deal Name CDO 1 CDO 2 CDO 3 CDO 5 CDO 6 CDO 7 CDO 8 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 25

Expected Loss

Most Junior

Loss Coverage

WAR

Equity Size

Rate

Tranche Rating

Ratio

AA+/AA AA AA AAAA/AAAA/AAAA/AAAAAA-/A+ AA/AAAAAA/AAA+ AA/AAAA AAA+ A+ AA/AAAA+

0.50% 1.44% 2.37% 1.91% 1.00% 1.50% 1.50% 1.71% 2.30% 0.80% 1.49% 1.60% 1.80% 1.53% 1.59% 1.67% 2.13% 2.50% 1.50% 1.61%

0.1861% 0.4083% 0.2228% 0.6008% 0.4003% 0.2773% 0.3918% 0.2620% 0.6328% 0.4045% 0.6112% 0.3771% 0.8035% 0.6505% 0.4203% 0.4522% 0.7245% 0.7522% 0.4083% 0.3955%

ABBB ABBB BBB BBB ABBB A-

2.69 3.52 10.64 3.18 2.50 5.41 3.84 6.52 3.63 1.97 2.43 4.24 2.24 2.35 3.77 3.69 2.94 3.32 3.67 4.08

BBB ABBB BBB BBBBBBAABBB BBB


What are the other concerns of HG CDOs? There are some other concerns regarding HG SF CDOs. More specifically, investors are concerned about the 1) increasing share of the CDO bucket, 2) the synthetic exposure, and 3) the Single-A and below bucket. We advocate investors watch for these issues and we discuss each issue below.


1.

CDO bucket: Exhibit 35 shows, at the AA and A levels, the impairment rates of CDOs are generally higher than those of other sectors. Especially at the “A” level, the impairment rate stands at 6.5%. This probably explains why some HG deals explicitly restrict any exposure to CDO tranches rated below “Aa3”. We show actual CDO rating distributions of some select deals in our list in Exhibit 31, and investors should pay close attention to those with CDO tranches rated below “Aa3“. Most of the impairments come from the SF CDOs of early vintages, HY CBOs and IG CBOs. It is also important to assess which CDO sectors are included in the pool.

2.

Synthetic bucket: Generally HG SF CDOs will allow a maximum synthetic bucket of 25-30%. We suggest investors pay close attention to deals that allow for higher exposure, especially when it reaches 50%. Synthetic exposure presents certain unique risks, including: 1) exposure to different counterparties; 2) documentation risk - mostly differences in credit event definitions; and 3) higher leverage.

3.

Single-A or below bucket: As spreads continue tightening, it may become necessary to go down the credit spectrum in order to achieve the desired yields. However, the default risk associated with Single-A or below rated assets is exponentially higher. For example, the impairment rate of A-rated HEL jumps from zero to 1.06%, as shown in Exhibit 34. In Exhibit 39, we show the rating distribution of select HG SF CDOs. Investors should identify deals highlighted in bold to ensure that credit support levels are adequate.

40

31 March 2006

Exhibit 39: Rating Distribution of Select HG SF CDOs Deal Name

Aaa

Aa1

Aa2

Aa3

A1

A2

A3

CDO 1

62.60%

5.00%

18.08%

4.88%

3.09%

5.32%

1.03%

CDO 2 CDO 3 CDO 4 CDO 5 CDO 6 CDO 7 CDO 8 CDO 10 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 25 CDO 28 CDO 30

45.27% 45.52% 33.68% 34.27% 43.67% 43.47% 41.89% 37.98% 43.01% 33.62% 27.53% 27.16% 37.79% 31.53% 40.06% 40.05% 26.55% 25.62% 17.03% 23.10% 35.30% 1.70% 27.73%

4.80% 5.83% 1.95% 8.01% 12.78% 2.40% 5.40% 6.44% 17.50% 3.92% 3.21% 10.08% 2.64% 0.66% 7.54% 3.56% 1.42% 2.80% 5.89% 9.90% 6.50% 5.02% 5.45%

31.70% 32.01% 35.23% 28.81% 19.38% 24.97% 31.93% 25.94% 19.59% 11.02% 52.86% 28.20% 28.64% 18.67% 34.68% 39.05% 38.96% 17.07% 12.38% 32.65% 33.66% 14.39% 13.45%

6.43% 4.79% 3.97% 3.33% 1.76% 13.49% 2.06% 9.12% 10.53% 3.09% 1.77% 9.84% 16.52% 0.30% 2.70% 2.35% 16.61% 1.83% 7.83% 8.97% 1.94% 7.98% 14.28%

1.22% 1.69% 4.33%

9.55% 8.97% 11.36% 16.55% 13.57% 12.18% 14.91% 8.01% 5.49% 32.03% 13.07% 7.99% 7.04% 28.10% 13.02% 11.76% 7.30% 38.30% 23.67% 4.57% 15.21% 35.77% 13.27%

1.03% 1.19% 3.24% 9.02% 1.74% 0.82%

5.25% 2.66% 2.76% 6.68% 3.34% 7.96% 0.38% 1.55% 1.40% 3.85% 0.16% 0.49% 0.19% 6.53% 24.19% 19.79% 2.58% 19.67% 8.78%

Baa1

Baa2

Baa3

NR

6.24% 1.45%

0.41% 1.03%

5.77% 0.54% 8.37% 0.56% 15.17% 5.98% 16.90% 1.83% 2.74% 8.96% 7.84% 9.01% 1.00% 4.13% 9.58% 11.67%

0.07%

0.62%

0.50% 5.90% 3.19%

0.19% 2.16%


Closing thoughts Overall, we think HG SF CDOs offer a unique risk and return combination. For investors interested in getting exposure to mortgage-related assets and other structured products such as CDOs, and have conservative views on the US housing market and interest rate prospects, HG SF CDOs are a suitable investment strategy – i.e., moving up the credit spectrum, and using leverage to achieve the desired yield. Although most HG SF CDOs appear to have sufficient loss coverage, investors should pay close attention to the individual assets in the collateral, as “the room for error” for HG SF CDOs is relatively smaller due to high leverage. A single “bad” credit could prove costly, especially to the lower tranche holders. Our analysis provides a first-cut screen for interested investors.


41

31 March 2006

High Grade SF CDOs Revisited39 The high grade (HG) SF CDO market continued its vigorous momentum through 2005 and into 2006 and has surpassed mezzanine SF CDOs by taking more than 50% share of the SF CDO market. Issuance accelerated in the fourth quarter of 2005: 18 HG SF CDOs priced totaling $23.65 billion in just one quarter! Given the rapid growth of this market, we think it is necessary to give our readers an update of this sector.

WARF is trending higher… Data collected on HG SF CDOs over the past three years suggests an upward trend of the portfolio weighted average rating factor (WARF), one of the most important parameters measuring the aggregate credit quality of the underlying collateral of a CDO. High grade SF CDOs, by definition, should have a lower WARF with the average credit quality of the underlying pool much better than, say, mezzanine SF CDOs. However, as indicated in Exhibit 40, we think the average credit quality of HG SF CDOs has deteriorated from AA/AA- to AA-/A+.

Exhibit 40: Change of HG SF CDO WARF Over Time* 100 90 80

Moody's WARF

70

A+

60 50 40

AA-

30

AA

20 10 0 12/10/02

6/28/03

1/14/04

8/1/04

2/17/05

9/5/05

3/24/06

Source: Credit Suisse, S&P, Moody’s, Fitch, Intex * Based on all available information obtainable on high grade SF CDOs up through December 2005.

As spreads grind tighter, modest movement down the credit spectrum can certainly help “juice up” the potential return for equity investors. However, at the same time it also raises the concern for increased risk of defaults and losses. Therefore, we check to see if there are changes in the credit support or structure that could mitigate the rise in default risk.

… But, junior subordination declines; leverage rises… The first feature we check is the size of the equity tranche, or the subordination level of the most junior tranche. Instead of showing just the raw equity size of each deal, which is not really an apples-to-apples comparison, we want to adjust it using the WARF. Intuitively, the higher the WARF, the higher the subordination level required – i.e., the bigger the equity size or the lower the leverage.

39


This section was originally published in "The CDO Strategist", Issue #14, February 16, 2006.

42

31 March 2006

The way we apply the WARF adjustment is to run a regression – a regression of WARF on the equity size.40 Next, we calculate the “WARF-adjusted equity size”, or, alternatively put, the required junior subordination level for a given WARF. Lastly, we take the difference between the “required” subordination level and the “actual” level and plot it against time.

Exhibit 41: WARF-adjusted Junior Subordination Shortfall/Surplus

Required Subordination minus actual subordination

1.50%

Subordination shortfall 1.00%

Deal A

0.50%

0.00% Oct-03

Jan-04

Apr-04

Aug-04

Nov-04

Feb-05

May-05

Sep-05

Dec-05

Mar-06

-0.50%

Deal B -1.00%

Subordination surplus -1.50%

Source: Credit Suisse, S&P

As shown in Exhibit 41, a positive number means more subordination should be provided – i.e., shortfall – and vice versa. How do we interpret the numbers? Let’s use Deal A and Deal B (marked in the chart) as two examples. First, please note the numbers are only meaningful in a relative sense. Deal A has a WARF of about 70 (A+) and an equity sized at 0.8%. However, based on historical experience and the deals in our sample, it “should“ have an equity sized/junior subordination level of 1.54% instead, a 0.74% shortfall. On the other hand, Deal B has a WARF of about 43 (AA-) and an equity sized at 1.75%. Its WARF-adjusted equity size is 1.28% or the “surplus” is 0.47%.41 It seems that over time the shortfall is climbing: the junior subordination level is declining when adjusted for WARF.

… And no clear improvement in OC test level either… Of course, just the subordination level alone does not provide all the credit support. One of the other important factors is the tightness of the OC tests. An OC test with a higher threshold or minimum level, is tighter, and vice versa. A tranche with lower subordination but tighter OC test could have the same credit protection as a tranche with higher subordination but looser OC test. Therefore, we check the OC test threshold levels of the HG SF CDO deals in our sample.

40 41


I.e., WARF is the X variable, and equity size is the Y variable. The lowest-rated notes of both Bond A and Bond B are BBB-rated.

43

31 March 2006

Exhibit 42: Most Junior OC Test Threshold Levels 101.6%

Most junior OC test threshold level

101.4% 101.2% 101.0% 100.8% 100.6% 100.4% 100.2% 100.0% 99.8% Oct-03

Jan -04

Apr-04

Aug-04

Nov-04

Feb-05

May-05

Sep-05

Dec-05

Mar-06

Source: Credit Suisse, S&P, Fitch, Intex

Exhibit 42 plots the most junior – mostly BBB or A rated – OC test threshold levels; there does not seem to be an improvement, but rather, a downward trend,

HG collateral update: share of fixed and CDO assets In terms of collateral composition, we pay special attention to the share of fixed assets and CDO tranches in the underlying pools. There is a perception in the market that the share of CDO tranches in HG SF CDOs has been increasing. Surprisingly, we found the opposite: the percentage of CDO tranches in the collateral pools actually declined in 2005 (see Exhibit 43), at least based on the deals with available collateral-level information. Other interesting observations include the rising share of home equity bonds and the sharp drop of CMBS in the collateral.

Exhibit 43: Asset Allocation of the Underlying Collateral* 60% Hom e Equity CDO

50%

CMBS RMBS (Res i-A)

40%

30%

20%

10%

0% 2002

2003

2004

2005

Source: Credit Suisse, Intex * Collateral-level information is not available for all HG SF CDOs in our sample, especially more recent 2005-vintage deals


44

31 March 2006

Many market participants also believe that the exposure to fixed-rate assets has jumped as well, and this is a concern because of the convexity risk associated with fixed bonds. However, we did not find strong empirical evidence supporting this view.

Exhibit 44: Share of Fixed-rate Assets in HG SF CDOs Total Deals in Sample*

# of Deals with All Floating Assets

Fixed % (all deals)

Fixed % (excl allfloating deals)

2003-1H

3

0

41.2%

41.2%

2003-2H 2004-1H 2004-2H 2005**

5 4 18 12

1 1 9 3

21.8% 20.4% 12.2% 16.1%

27.2% 27.0% 24.0% 21.2%

Source: Credit Suisse, Intex * This is the number of deals we have fixed vs. floating information on, not necessarily the same number deals on which other information is based on ** Not all 2005 deals are included

Exhibit 44 shows the share of fixed-rate assets in HG SF CDOs. There are several notable points: 1.

The high percentage of fixed assets in early 2003 deals is due to significant exposure to CMBS bonds, such as the Blue Heron deals.

2.

In the second half of 2004 in particular, there is a significant number of deals – 50% – with zero exposure to fixed-assets.

3.

When all deals are considered, 2005 deals saw an increase of fixed bond share over the second half of 2004, but overall it is difficult to argue that there is a significant increase. When the deals with all floating assets are excluded, the shares of fixed assets are fairly consistent since 2004 – all in the 20’s – and 2005 numbers actually dropped a bit.

Some Comments on the Basis Risk in HG SF CDOs Basis risk is an extremely important issue for HG SF CDOs – every basis point mis-match could have a significant impact on equity returns given the high leverage ratios. There are generally four potential sources of basis risk.


1.

Difference in payment dates. The payment dates of the underlying assets could be different from the payment dates of the CDO. As rates fluctuate daily, especially during volatile periods, there could be a mismatch between the interest collected from the collateral and the interest paid out to CDO notes.

2.

Difference in index rates. Almost all floating home equity bonds, which comprise the majority of the underlying collateral of recent SF CDOs, pay coupon monthly and are indexed to 1-month LIBOR. However, the CDO could pay coupon on a quarterly basis and may be indexed to 3-month LIBOR. As rates of different maturities do not necessarily move in parallel fashion, the spread between 3month LIBOR and 1-month LIBOR could change significantly and cause a basis mismatch for the CDO.

3.

Mismatch between interests collected from fixed-rate assets and coupon paid out on floating CDO tranches. Hedging vehicles such as interest rate swaps or caps are typically utilized to mitigate this mismatch, but the challenge is to match the swap notional with the actual amortization speed of the underlying collateral, which is difficult to accomplish. Some deals have been granted the flexibility to revise the hedging notional if and when needed.

45

31 March 2006

4.

Available funds cap risk. The coupon collected from the underlying assets may not be sufficient to pay interest on the CDO notes due to the embedded available funds cap risk in home equity bonds. However, as most bonds in HG SF CDOs are AAA or AA-rated, this risk should be very minimal under normal condition.

In addition to the swap and cap contracts discussed, other techniques such as basis swap and reserve accounts are used to mitigate basis risks. These certainly help smooth the mismatch, however, it is very critical for investor to monitor the basis risk of HG deals.

Final comments HG SF CDOs have grown into a mainstay of the CDO market. Due to concerns over the US housing market, the high credit quality of the underlying collateral in HG SF CDOs is appealing to many investors and we believe the momentum will continue. That said, given select unsettling trends we discussed above contained in some of the recent HG deals, we encourage investors to keep a close eye on these issues.


46

31 March 2006

Build or Buy: HEL Bonds versus SF CDOs42 We compare two investment strategies: building a portfolio of mezzanine (mostly BBBrated) HEL bonds versus buying a BBB tranche of a mezzanine SF CDO containing high concentration of mezzanine HEL bonds. Based on our analysis of risk/return profiles, we think the latter investment provides an attractive alternative of investing in the home equity sector. The main reasons include: 1.

Attractive spread pickup: With the majority of mezzanine HEL bonds being placed in mezzanine SF CDOs, BBB HEL bond spreads are at historical lows of around L+135/140 bps.43 Yet, SF CDO BBB tranches are still offered at about L+270 level, representing an attractive spread pickup of about 130 bps.

2.

Similar fundamental risks: Given that the majority of the collaterals of recent SF CDOs are invested in HEL bonds, the risk exposure to the fundamentals of the home equity sector and housing market are similar in these two approaches, especially if both invest in the same HEL bonds.

3.

More credit support: The BBB tranches of SF CDOs enjoy another layer of credit protection provided by the equity tranche of the CDOs.44

4.

Turbo feature: Most mezzanine SF CDOs have a turbo feature, which allows a portion of the bond principal to be paid before potential defaults kick in later as HEL pools season. This feature further enhances the value of the BBB tranche.45

5.

Less Available Funds Cap (AFC) risk: SF CDOs should have relatively less AFC exposure, because the portfolio is more diversified as it could include RMBS, CMBS, CDOs, or other assets, some of which may not have the same sensitivity to AFC as home equity bonds.

In our analysis we randomly select a static mezzanine SF CDO priced at the beginning of 2005 and then construct a portfolio ONLY composed of exactly the same HEL bonds, mirroring those contained in the SF CDO. By applying the identical sets of assumptions on these HEL bonds, the risk/return profiles of the BBB tranche of the SF CDO and of the “built” portfolio of HEL bonds are compared. Our baseline prepayment (CPR) and default (CDR) curves applied to the underlying home equity loans backing these HEL bonds are shown in Exhibits 48 and 49.46 We then use Intex’s portfolio functionality to generate the cash flows for each bond as well as the aggregate cash flows of the portfolio. Exhibit 45 shows the capital structure of the sample SF CDO, whose BBB tranche has a coupon of L+285 bps. This BBB tranche also has a Turbo feature with a 14% cap on the equity, i.e., after satisfying the 14% annual return on the equity, the remaining excess interest will be used to pay down the BBB tranche, subject to passing OC and IC tests. The collateral of this SF CDO is composed mostly of HEL bonds (Exhibit 46). The majority of the HEL bonds are rated from Baa1 to Baa3, and are mostly floaters with a weighted average spread of 227 bps over 1-month LIBOR (Exhibit 47).

42

This section was originally published in "The CDO Strategist", Issue #8, September 30, 2005. Based on our estimates, the percentage of BBB-rated HEL bonds bought by CDOs is around 70-75%. 44 Each rated HEL bond already has the credit support from both the subordination and excess spread. 45 For detailed discussion on the Turbo feature, please refer to "The CDO Strategist - Revisiting Turbo Structure: Empirical Evidence", July 15, 2005. 46 Since the majority of the underlying loans are hybrid ARM loans, the CPR and CDR curves are more customized to these types of loans. 43


47

31 March 2006

Exhibit 50 shows the prepayment, default and severity assumptions for RMBS (Resi-A mortgages), CDOs, and “others” (includes CMBS, REITS, Credit Card, SBA, etc.). To simplify the analysis, we use a constant number for each variable and asset type.

Exhibit 45: Capital Structure of the Sample SF CDO Tranche Name

Percentage of Total Deal Size

Moody's Rating

A1 A2 B C Equity

Aaa Aaa Aa2 Baa2

Coupon

70% 12% 10% 4% 4%

L + 32 L + 50 L + 70 L + 285


Exhibit 46: Rating Distribution of HEL Bonds in the Sample SF CDO A1

A2 A3 Ba1

Baa3

Baa1

Baa2 Source: Credit Suisse, Intex


48

31 March 2006

Exhibit 47: Baseline CPR Curve of HEL Loans 60% 50%

CPR

40% 30% 20% 10% 0% 0

3

6

9

12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 Age (month)


Exhibit 48: Baseline CDR Curve for HEL Loans 8% 7% 6%

CDR

5% 4% 3% 2% 1% 0% 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 Age (month) Source: Credit Suisse

Exhibit 49: Assumptions of Other Assets in the SF CDO Baseline RMBS CDO Other* Stress Level I RMBS CDO Other* Stress Level II RMBS CDO Other*

Prepayment Rate

Default Rate

Severity

20% 0% 0%

0.50% 0.50% 0.50%

40% 40% 40%

20% 0% 0%

1.0% 1.0% 1.0%

40% 40% 40%

20% 0% 0%

1.50% 1.50% 1.50%

40% 40% 40%

Source: Credit Suisse * For this CDO in particular, “other” includes CMBS, REITs, credit card, etc.


49

31 March 2006

Exhibit 50: Results - Using Baseline Assumptions for Other Assets in the CDO* Assumptions Applied on the HEL Bonds Base Case Stress CDR Curve by 50% Stress CDR Curve by 100% Stress CDR Curve by 50%, and Stress Forward Curve by 100 bps Stress CDR Curve by 50%, and Stress Forward Curve by 200 bps

BBB Tranche of CDO DM** IRR 285 7.62% 285 7.62% 285 7.62%

Portfolio of HEL Bonds DM** IRR 226.6 7.02% 216.5 6.91% 118.9 5.89%

285

8.63%

164.3

7.42%

285

9.64%

90.9

7.70%

* This analysis is based on the assumption that the CDO will be auction-called at par on the first auction call date and the portfolio of HEL bonds could also be liquidated on the same date at par. ** For the CDO tranche, the DM is over forward 3-month LIBOR, while for the HEL portfolio, the DM is over forward 1-month LIBOR. Source: Credit Suisse

As shown in Exhibit 50, the BBB CDO tranche performs better than the HEL portfolio under the baseline assumption for the rest of the CDO pool and different stress scenarios for the HEL bonds. The DM holds steady in all scenarios while the DM and IRR of the portfolio of HEL declines across all scenarios. Notably, when the baseline CDR curve is doubled, the DM drops by 108 basis points.47 More interestingly, when the forward curve is bumped up by 200 bps, with a 50% increase in the baseline CDR curve, the DM of the HEL portfolio drops to 91 bps! Part of the decline is due to the AFC issue, while the AFC has no impact on the DM of the CDO tranche. In addition, due to the Turbo feature, the BBB CDO tranche gets paid-down in principal in the first 18 months or so across all scenarios, which also helps its performance.

Exhibit 51: Results - Using Baseline Assumptions for Other Assets in the CDO* BBB CDO at Stress Level I* Assumptions Applied on the HEL Bonds Base Case Stress CDR Curve by 50% Stress CDR Curve by 100% Stress CDR Curve by 50%, and Stress Forward Curve by 100 bps Stress CDR Curve by 50%, and Stress Forward Curve by 200 bps

BBB CDO at Stress Level II**

DM 285 285 271

IRR 7.62% 7.62% 7.62%

DM 285 285 153

IRR 7.62% 7.62% 6.28%

285

8.63%

285

8.63%

285

9.64%

285

9.64%

*Stress Level I increases the CDR of non-HEL collateral to 1%. ** Stress Level II increases the CDR of non-HEL collateral to 1.5%. Source: Credit Suisse

One argument to dispute the seemingly stronger performance of the CDO tranche is the positive benefits contributed by the other asset sectors. However, if non-HEL assets perform well, this is precisely why we think investors should consider investing in the CDO! Second, even when stress assumptions on non-HEL sectors are increased to more severe levels, our main conclusion remains. In Exhibit 51, we re-run the same analysis on the CDO under different stress scenarios for the non-HEL sectors, i.e., stressing the CDR to 1% and 1.5% levels.48 At 1% CDR, only in the scenario where the CDR curve for home equity loans is doubled does the DM of the BBB CDO tranche starts to drop. However, the magnitude is still smaller than the decline of the HEL portfolio’s DM in the same scenario. We do not see a similar decline in the CDO’s DM until we stress the CDR of the non-HEL sectors to 1.5%.49

47 Doubling our baseline CDR curve is a very stressful scenario as the CDO could reach as high as 14% CDR. However, even under this scenario, the DM of the BBB-rated CDO tranche still hold its DM at the coupon spread level of 285. 48 For CMBS, REITs, and Resi-A mortgages, 1% or 1.5% annual CDRs are very stressful scenarios. 49 Notice that in our analysis, all the prepayment and default assumptions are applied to the underlying loans, such as for RMBS and CMBS, or the underlying bonds, such as for CDOs.


50

31 March 2006

We ran similar analysis on several other CDOs with similar characteristics - recent vintage (2004 and 2005), mezzanine SF CDOs with large concentrations of HEL, similar structures, and etc. And while we only showed our results for one CDO, our conclusions hold for all the deals we have checked. We also believe these results to be consistent across many of the recent vintage mezzanine SF CDOs with similar characteristics.50 In addition, the performance of the remaining collateral (i.e. besides HEL) contained in the SF CDOs needs to be monitored closely to the extent they may impact CDO performance.51 The significant spread pick-up of BBB SF CDOs versus BBB HEL bonds is partially due to less liquidity and transparency in the CDO space. However, for buy-and-hold investors, a little less liquidity might be a good source to pick up extra yield. Some might also argue that the complexity associated with CDO analytics contributes to the premium as well. We think as investors become familiar with CDOs, this premium will diminish. The rise of the CDO market has changed the entire landscape of investment. All investors, seasoned or new, are faced with the challenge of adapting to the new environment. For investors in the home equity sector, SF CDOs provide an attractive alternative. Beyond the scope of our analysis, if investors agree that the BBB tranches of recent mezzanine SF CDOs could offer higher return due to spread pick-up versus a pool of BBB HEL bonds, yet share similar risk exposure to the housing market and interest rate risk, we suggest consideration be given to going long the CDO tranche while going short (by buying protection through credit default swap) some of the individual bonds on which they have negative views.

50

For interested readers, we would be glad to share more of our results. There could be some extreme situations where the bad performance of certain bonds could hurt the CDO and make it less attractive. 51


51

31 March 2006

Revisiting Turbo Structure: Empirical Evidence52 The mezzanine turbo feature has become a cornerstone of structured finance (SF) CDO structures. In 2004, 80% of all managed new-issue SF CDOs included a turbo structure. Along with the maturation of the CDO market, the turbo structure has evolved too, incorporating a variety of different approaches.53

Turbo fast-track – how and why they work Turbo defined: excess interest diverted to amortize mezzanine tranches

In a generic turbo structure, the turbo feature serves as a rapid amortization mechanism for mezzanine tranches typically rated Triple-B. During the reinvestment period (typically the first 3-4 years for SF CDOs), a portion of the excess interest, after paying liability coupon payments and fees, and upon satisfying all coverage tests, is used to amortize the mezzanine notes.54 The methods used to determine turbo amounts vary from deal to deal, and are explained in detail later. It is important to note that interest but not principal from the collateral is used to turbo the notes. This effectively pays down the most expensive tranche, and reduces the liability cost while avoiding subordination or overcollateralization (OC) erosion of the senior tranches. What’s the value of, and who benefits from, a turbo structure? 1)

For senior notes holders: the senior investors are indifferent.

2)

For BBB note holders: the turbo shortens the average life of the bonds. Since losses in home equity (HEL) collateral do not generally begin until the loans are about 18 months seasoned, with defaults on BBB HEL bonds usually occurring even later, the turbo essentially allows a portion of the bond principal to be paid before defaults, if any, kick in later.

3)

For equity holders: the equity holders give up some yield.

A tale of two Turbos Recent deals have included variations to the traditional turbo structure as CDOs have evolved over time. Exhibit 52 details a few common structures:

Exhibit 52: Common Turbo Structures Structure Type

Duration of Turbo Period

(1) X% Equity cap, Remaining excess interest to turbo BBB Class

(a) For Life of Transaction (b) During Reinvestment Period (c) During Specific Time Period (c) Until Auction Call Date (d) During Non-Call Period

(2) Turbo the BBB tranche up to $X per period, Remaining excess interest to Equity (3) Turbo the BBB tranche based on predetermined schedule, Remaining excess interest to Equity Source: Credit Suisse

Additionally, some deals use combinations of the above structures. For example, a deal may cap the equity at 15% (annual return), divert the excess interest to amortize the BBB class up to $100,000 per payment period, and then distribute any remaining interest back to the equity. Furthermore, many deals now-a-days turbo not only the BBB class, but also other tranches in a reverse sequential order.

52

This section was originally published in "The CDO Strategist", Issue #5, July 15, 2005. In November, 2002, Credit Suisse published a special report titled "Relative Value of Turbo Triple-Bs in ABS CDOs". 54 For example, OC/IC tests, par value tests, etc. 53


52

31 March 2006

To observe the impact of different turbo structures on BBB cash flows, we applied structures (1) and (2) above on a hypothetical SF CDO deal with characteristics as specified in Exhibit 53.

Exhibit 53: Sample SF CDO Deal Structure Tranche

Deal Information

Size ($mm) CE(%) Rating

Coupon (bps)

Reinvestment

3 year

Fixed WAC

5.70%

L + 30

Turbo Period

3 year

Floating WAS

1.75%

Auction Call

8 year

Floating Assets

76%

$400mm

Payment Freq.

Quarterly

A

$308.00 23.0%

Aaa

B

$59.90 8.0%

Aa2

L + 58

C

$16.10 4.0%

Baa2

L + 265

Equity

$16.00

---

NA

---

Base Case Assumptions Default Rate (Annual) Recovery in Default

0.50% Immediately at 40%

Total Size

Class A/B OC Test Class C OC Test Class A/B IC Test Class C IC Test

103.5% 101% 115% 110%

Turbo Structures Structure (1) – Equity Cap Structure (2) – BBB Cap During the Turbo Period, payment to the Equity is capped at 15% During the Turbo Period, excess interest is first used to amortize annual rate. Remaining excess interest used to amortize class C class C, subject to a periodic cap of $162,165. Remaining excess interest is paid to the Equity Source: Credit Suisse

Based on similar recent SF CDO structures, we apply an Equity Cap rate of around 15%. The BBB dollar cap amount of $162,165 in the second structure is determined by taking an average of total BBB amortization during the turbo period in the first structure (by applying a 15% equity cap rate). Exhibit 54 shows the base case BBB pay-down rate during the turbo period for each turbo structure. As we can see, the BBB pay-down rate is nearly identical for both structures, which is as expected given the way we determine the dollar cap amount.

Exhibit 54: Base Case Turbo BBB Pay-down Rate* 14%

0.5%CDR, 15%Equity Cap (Structure 1)

BBB Paydown Rate (%)

12%

0.5%CDR, $162,165 BBB Dollar Cap (Structure 2)

10% 8% 6% 4% 2% 0% 0

1

2

3

4

5 6 7 8 Quarters since Closing

9

10

11

12

13

* The pay-down rate is defined as a percentage of the original BBB tranche balance. Source: Credit Suisse


53

31 March 2006

Exhibit 55: Stressed at 2.05% CDR, Greater Pay-down in Structure 2* 14%

2.05%CDR, 15%Equity Cap (Structure 1)

BBB Paydown Rate (%)

12%

2.05%CDR, $162,165 BBB Dollar Cap (Structure 2)

10% 8% 6% 4% 2% 0% 0

1

2

3

4

5 6 7 8 Quarters since Closing

9

10

11

12

13

* The pay-down rate is defined as a percentage of the original BBB tranche balance. Source: Credit Suisse

However, if we increase CDR, the BBB pay-down rates diverge. Exhibit 55 illustrates the effects of CDR increase to 2.05%. It is clear that the pay-down on the BBB is higher in Structure 2 as the same dollar amount ($162,165) implies a lower equivalent cap rate applied on the equity under this default scenario. The equivalent equity cap rate is around 12.94%.55 A more important observation is, should CDR become 2.05% and the equity cap set at 15%, there is a principal loss on the BBB tranche. Under Structure 2 (using the dollar amount cap of $162,165), the par discount margin (DM) on BBB still holds at 265 bps, equal to the coupon spread of this bond. However, under Structure 1 using an equity cap rate of 15%, the par DM turns out to be only 235 bps. To prevent any losses on the BBB tranche, the cap rate has to be lowered to a maximum cap rate of around 12.8%. This illustrates the importance of setting an optimal cap rate to protect the BBB tranche, which is not an easy task.

Historical Performance of Turbo on BBB Tranches How has the turbo structure actually impacted BBB tranches? Using our surveillance universe, we aggregate the actual pay-down experience on turbo BBB SF CDO tranches from 2001-2003, grouped by vintage.56 57 Exhibit 56 shows the results:

Exhibit 56: Historical Turbo BBB Pay-down Experience* BBB Paydown Rate (%)

14% 12% 10% 8% 6% 4%

2001

2%

2002

2003

0% 0

1

2

3

4

5

6 7 8 9 10 11 Quarters since Closing

12

13

14

15

16

17

18

* In this analysis, we exclude CRE (or CMBS) CDOs, real estate CDOs (such as most C-BASS deals), high-grade SF CDOs, and CDO-squared deals. We also exclude deals with large buckets of CDO tranches (higher than 20%). Source: Credit Suisse

55

This time we set the equity cap rate so that the average pay-down is equal to $162,165 under 2.05% CDR. 56 Please see our Deal Surveillance Reports on www.cbo.com, which tracks the performance CDOs, available to QIB. 57 In this analysis, we don't include CRE (or CMBS) CDOs, real estate CDOs (such as most C-BASS deals), high-grade SF CDOs, and CDO-squared deals. We exclude deals with large bucket of CDO tranches (higher than 20%) as well. Chapter 1. Structured Finance CDOs

54

31 March 2006

The chart suggests several interesting points: •

The 2001 vintage experienced the fastest (not necessarily the highest) turbo BBB pay-down early on - the pay-down rate during the first 4 quarters is much higher than the other two vintages. We attribute this to slower prepayment speeds of 2001 vintage. In addition, 2001 SF CDOs tend to be comprised of a broader range of asset classes compared to later vintages, many which prepay slower. For example, asset classes like corporate bonds (~12% of 2001 pools) and REITS (~5% of 2001 pools) behave like bullet bonds. In addition, 2001 vintage HEL loans tend to prepay slower than loans of later vintages. These combined factors result in slower prepayment and higher principal balance contributing to more excess spread to turbo the BBB tranche early on.58

•

The 2001 vintage also ceased “turbo-ing” the earliest at 1.5 years (6 quarters) while the 2002 vintage ceased after around two years (8 quarters). In 2002, ABS downgrades were at historical highs, led by the manufactured housing (MH) sector. Losses attributed to MH and other troubled ABS sectors during this time may account for the early termination of the turbo.

•

The continued rise of the 2003 vintage turbo BBB pay-down curve may be attributed to the shift of 2003 collateral pools into more residential mortgagerelated assets, where the credit performance so far has been quite robust.

•

From a relative value perspective, the value of the turbo feature in 2001 and 2002 vintage SF CDOs has diminished as deals from these vintages have in general ceased turbo-ing for at least four payment periods (on a quarterly basis). In general, the turbo feature in 2003 SF CDOs, however, still has value as the turbo remains active (for a more detailed discussion on the 2003 vintage of mezzanine SF CDOs, please see our Strategy section).

Finally, we note that 15 tranches across 7 SF CDOs have been upgraded because of the turbo structure. Exhibit 57 shows the actions.

Exhibit 57: SF CDOs Upgraded Due to Turbo Deal Name Capital Guardian ABS CDO I, Ltd. E-Trade ABS CDO II, Ltd.

Pacific Bay CDO, Ltd. Pacific Coast ABS CDO Ltd. Pacific Shores ABS CDO Ltd.

Solstice ABS CBO, Ltd. St. George CDO Funding 2000-1 Ltd.

Class

Orig. Rating

Prior Rating

Current Rating

Rating Agency

Vintage

C B-1 B-2 C-1 C-2 C Equity C-1 C-2 C PS-CL1 PS-CL2 C C B C

BBB AA AA BBB BBB BBB BBB BBB BBB BBBBBBB BBB AAA-

BBB AA AA BBB BBB BBB BBB BBB BBB BBBBBBB BBB AA+ A-

BBB+ AA+ AA+ BBB+ BBB+ ABB+ BBB+ BBB+ A BBBBBBBBB+ AAAA A

Fitch Fitch Fitch Fitch Fitch S&P S&P Fitch Fitch Fitch Fitch Fitch S&P Fitch Fitch Fitch

2002Q1 2003Q3 2003Q3 2003Q3 2003Q3 2003Q4 2003Q4 2001Q3 2001Q3 2002Q2 2002Q2 2002Q2 2002Q2 2001Q1 2000Q3 2000Q3

Source: Credit Suisse, S&P, Fitch

58


Please refer to CSFB periodic report, "Subprime HEAT Update", June 2005.

55

31 March 2006

Auction Calls in SF CDOs59 The auction call has become a standard feature in nearly every SF CDO. While the legal final of most SF CDOs is 35 years, reflecting the longest maturity of the underlying collateral, the auction call mandates that the trustee conduct a collateral auction at some point after closing (typically 6-8 years in recent deals) to terminate the CDO, effectively shortening the maturity of the transaction. The implications of the auction call are significant, especially for equity holders. When a new deal is being structured and priced, it is usually assumed the deal will terminate on the first auction call date. However, in reality, whether and when the deal will have a successful auction could make a difference in terms of the risk/return profile for equity holders. In particular, in the tight spread and arbitrage environment as equity returns continue to be squeezed, it is critical that the collateral assumptions are scrutinized and a sound mechanism is put in place to better predict amortization speeds and loss profile and ultimately, the probability of a successful auction call. We discuss auction calls in SF CDOs and establish a framework for assessing the likelihood of the auction call. The most difficult part of this analysis is that so far there have been no historical examples of SF CDO auction calls to reference.

Auction Call: How it Works Trustee is responsible for holding the auction

In a typical SF CDO, if any liabilities remain outstanding at the first auction call date (typically 6-8 years after closing), the trustee is required to hold an auction on the underlying collateral. If the bid prices are insufficient to redeem the outstanding notes plus fees and expenses and/or meet certain conditions (described in detail below), the auction may be repeated at each payment date thereafter if holders do not agree to accept less than their redemption amounts. Simple as it sounds, there are several nuances worth exploring. The time period until the first auction call date is a function of the mix and amortization schedule of the collateral. Early vintage SF CDOs (pre-2003) tend to have longer periods (10 years and up) because of smaller concentrations of residential mortgages and slower prepayment speeds, whereas CDOs since 2003 have had shorter periods (6-8 years) because of higher mortgage concentrations and faster prepayments.

Who can bid? Manager, equity holders, and trustees

The participants of the auction are typically limited to the collateral manager, equity holders, and the trustees and there must be at least two bidders at any auction (including the winning bidder) for the auction to be valid. Some deals allow the collateral manager additional precedence: the manager has the right to purchase the collateral at the highest bid and/or the right to postpone an auction due to market conditions.

Equity redemption differs for some deals

The redemption amount (or purchase price) may also differ from deal to deal, particularly in the treatment of the equity. Nearly all deals require any and all outstanding notes and fees and expenses (ex., hedge termination fees) to be redeemed with liquidation proceeds. For the equity, most deals only require redemption up to the original equity amount, net of all past distributions. For example, if the original equity amount was $3 million and the distributions up to the auction date totaled $2 million, the equity redemption amount at auction would be $1 million. However, if the distributions totaled more than $3 million, the equity redemption at auction would be $0. In other cases, the equity receives sufficient payment at auction to achieve a pre-determined annual internal rate of return (IRR).

59


This section was originally published in "The CDO Strategist", Issue #6, July 28, 2005.

56

31 March 2006

Note-holders/equity investors can vote to redeem at less than par

Furthermore, most CDOs offer the note-holders and/or equity investors the option to receive less than par, pending a 100% vote from the respective holders.60 In this case, the decision of whether or not to accept less than par is similar to the call rationale we established in a past research piece:61 Payment Received From Auction Call Proceeds > Present Value of Future Cash Flows

The collateral pool could be divided into sub-pools for bidding

However, the vote has several caveats. For a deal that is performing as expected, where the total collateral market value is sufficient to cover all note-holders (including equity) and fees at auction, the vote has no value as the auction will proceed regardless. However, in the case of a distressed deal, where the collateral market value provides insufficient coverage, the vote essentially gives the note-holders and equity-holders more options. By not accepting the auction call, they can receive more cash flows and a potentially better total return than settling with less than par redemption. Of course, the risk here is further losses and deterioration to market value. Depending on the investors’ view of the collateral and future market conditions, it may be more worthwhile to liquidate the assets. Finally, to improve the feasibility of collateral liquidation during the auction, in many cases the collateral manager may divide the collateral pool into a number of sub-pools for participants to bid on. The composition of the sub-pools is constructed to maximize the potential sales proceeds. Additionally, this may expand the bid as a single bidder is not required to purchase the entire pool.

Establishing Prepayment and Default Assumptions We focus on new vintages of SF CDOs, which normally include at least 70-80% of home equity (HEL) bonds in the collateral pool. It is critical to construct reasonable baseline prepayment and default curves in order to generate cash flows of underlying HEL bonds as well as cash flows of the SF CDO. Nowadays the vast majority of the underlying HEL bonds are floating bonds backed by mostly hybrid ARM loans, most of which are 2/28 ARMs. As an example, we use a real SF CDO deal closed at the end of 2004 which has 76% of the collateral in mezzanine HEL bonds (on average BBB-rated). Exhibit 58 shows the pool profile for the HEL bonds and general information on our sample SF CDO.62

Exhibit 58: General Information of Assets and Sample SF CDO Total Notional Floating Bonds Fixed Bonds

586,063,500

Assets Weighted Average Spread

2.05%

97%

Weighted Average Coupon

6.03%

3% Capital Structure of Sample SF CDO*

Share

Coupon

O/C Test

I/C Test

AAA

81.75%

L+33

AA

9.75%

L+55

104.8%

112%

BBB

4.25%

L+310

102.7%

108%

Equity

4.25%

* There is no reinvestment and BBB turbo in this deal. Source: Credit Suisse, Intex

60

In some cases, a majority vote. The vote is with respect to each class of notes or equity. Please see CSFB CDO Research, "The CDO Strategist - When's the Best Time to Call?", Issue #2, May 31, 2005. 62 The general structure of our sample deal is based on an actual deal, although we simplified the structure slightly. The liability spread levels are consistent with the actual deal, priced in late 2004. 61


57

31 March 2006

Based on CREDIT SUISSE’s proprietary prepayment model we can generate prepayment (CPR) curves for each bond and we construct an aggregate CPR curve as shown in Exhibit 59.

Exhibit 59: Baseline CPR Curve of Hybrid ARM HEL Loans* 60% 50%

CPR

40% 30% 20% 10% 0% 0

3

6

9

12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 Age (month)

Source: Credit Suisse * A pool mixed with 2/28 and 3/27 ARM loans.

This is a typical CPR curve for hybrid ARM loans with a mix of mostly 2/28 ARMs and some 3/27 ARMs – there is a spike after 24 months as prepayment usually jumps right after the rate reset date (2 years for 2/28 hybrids) and there is another spike after 36 months due to 3/27 hybrids for the same reason. Also, by using CREDIT SUISSE’s proprietary model, we can construct a default (CDR) curve following a similar approach. Exhibit 60 shows our baseline aggregate CDR curve for the underlying HEL loans.

Exhibit 60: Baseline CDR Curve for Hybrid ARM HEL Loans 8% 7% 6%

CDR

5% 4% 3% 2% 1% 0% 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 Age (month) Source: Credit Suisse


58

31 March 2006

Generating Cash Flows for the SF CDO We assume the entire sample CDO deal is backed only by the HEL bonds that are contained in the actual CDO deal (42 bonds in total) and apply our baseline CPR and CDR curves to the underlying loans backing these 42 HEL bonds. We also assume a severity rate of 40%. Once we have the cash flows of these bonds generated by Intex, we import these into our CDO model to generate the cash flows.63 To assess whether the deal will be auction-called, we look at several factors: 1) remaining asset/collateral notional on the auction date; 2) auction redemption amount which includes the remaining notes balances and the required payment to the equity holders; and 3) the market value of the remaining collateral on the potential auction call date.64 In order to have a successful auction, the product of 1) and 3) needs to be no less than 2). Exhibit 61 shows the factor (current balance divided by original balance) of both the collateral and liabilities. Normally we expect to see the factor of collateral lie above the factor of the liabilities. However, under high default/loss scenarios, we could see the collateral factor dip below the liability factor, which we will discuss later.

Exhibit 61: Collateral and Liability Factors under Baseline Assumptions 100% 90% 80% 70%

Factor

60% 50% 40% 30% 20% 10% 0% 1

3

5

7

9

11

13

15

17

19

21

23

25

27

29

31

33

35

Quarter Liability Factor

Collateral Factor


Both factors are one (i.e., no principal pay-down on both the collateral and liability) during the first 11 quarters or so because the HEL bonds usually have a 36-month step-down date, before which all collateral principal payments are distributed to the AAA’s, and the mezzanine and subordinated bonds normally do not receive any principal.65 Since all of the bonds in this pool are BBB-rated (some A-rated), there is no principal pay-down early on. The reason that it is not exactly 3 years is because the bonds bought by the CDO may already be several months seasoned and the underlying loans may also be several months seasoned when securitized. 63 We use forward LIBOR curve and convert monthly cash flows of the HEL bonds to quarterly cash flows for the CDO. 64 In reality, all the expenses, hedging termination fees, and etc are considered. For simplicity, we ignore these. 65 After the step-down date, if triggers are passed, OC is released and a large amount of principal could be channeled to subordinated and mezzanine bonds. However, if triggers are tripped, all principal payment will still go to AAAs and the subordinated and mezzanine bonds receive no principal for as long as the triggers remain tripped.


59

31 March 2006

How much is the collateral worth on the auction date? It is difficult to forecast the market value of the collateral in 6 or 8 years. Fortunately we have the projected cash flows, both principal and interest, of the underlying bonds. By discounting the cash flows after the potential auction date back to the present value as of the auction date, we can calculate the (theoretical) market price on that date. The question is: what is the appropriate discount spread to use? We turn to the ratings transition matrix for an answer. Based on Moody’s ratings transition on HEL bonds, we can calculate the percentage of HEL bonds, originally rated BBB, that will migrate to ratings ranging from AAA to CCC in 1 year, 2 years and up to 5 years, if they are still outstanding. For example, as shown in Exhibit 40, 15.2% of all originally BBBrated bonds will be BB-rated in 5 years, if they haven’t been paid off. We further interpolate the percentage for 6 years, 7 years and up to 10 years, based on which we can calculate the weighted average rating factor (WARF) and the ratings of the remaining originally BBB-rated bonds.

Exhibit 62: Rating Transition of BBB-rated HEL Bonds Actual (Based on Moody’s Transition Matrix) Year

Forecast (Linear Interpolation)

0

1

2

3

4

5

6

7

8

9

10

BBB -> AAA %

0.0%

0.1%

0.3%

0.6%

1.3%

1.8%

2.2%

2.7%

3.2%

3.8%

4.4%

BBB -> AA % BBB -> A % BBB -> BBB % BBB -> BB % BBB -> B % BBB -> CCC % WARF

0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 360

0.2% 1.0% 94.0% 2.9% 0.6% 1.1% 470 BBB/ BBB-

0.5% 1.8% 88.0% 5.9% 1.5% 2.0% 567 BBB/ BBB-

0.8% 2.6% 79.5% 8.9% 3.1% 4.5% 786 BBB/BB+

1.3% 3.5% 69.7% 12.9% 5.0% 6.3% 977 BB+/ BB

2.3% 4.6% 61.3% 15.2% 6.0% 8.8% 1164 BB+/ BB

2.6% 5.5% 52.2% 19.1% 7.7% 10.7% 1357

3.1% 6.6% 42.5% 22.7% 9.4% 12.9% 1566 BB/ BB1400

3.7% 7.6% 32.3% 26.6% 11.1% 15.3% 1785

4.4% 8.8% 21.6% 30.6% 13.0% 17.8% 2015

5.0% 10.0% 10.3% 34.9% 14.9% 20.5% 2257

BB-

BB-/B+

B+/B

1600

1800

2000

Rating

BBB

BB 1200

Spread Used (bps) Source: Credit Suisse, Moody’s

As shown in Exhibit 40, for a BBB-rated pool of HEL bonds, the remaining bonds will migrate to a BB-rated pool in 6 years.66 The rating will be BB- 8 years later and B/B+ 10 years later. Currently, BB-rated bonds trade between L+850 bps and L+1100 bps area.67 To be conservative, we use the spreads as specified in Exhibit 40.68 69

How much should be paid to the equity holders? In an auction call, the note holders need to be paid the par amount of the remaining balance. For equity holders, it is a bit more complicated. In most cases, there is either an explicit or implicit specification that the equity holders be paid back the original equity amount, net of what has been paid to them before the auction date. In some cases, there is an IRR hurdle specified so that the amount owed to the equity holders is sufficient to achieve this IRR.70 Our sample deal uses the first case, which essentially is equivalent to specifying a 0% IRR.

66

Please notice that we emphasize that it is for the "remaining" bonds, as many bonds have been paid off. Most of the bonds in our pool have an average life from 3.5 to 4.5 years. 67 For non-Moody's rated BB bonds, the spread is wider and trade around L+1100 bps. 68 B-rated bonds are usually quoted in dollar terms. However, for convenience, we use spread instead. 69 This analysis also ignores collateral changes due to trading in a managed deal. 70 This is equivalent to all the cash flows to the equity holders bring discounted at the IRR and the sum of the PVs has to be equal to the original equity amount. Chapter 1. Structured Finance CDOs

60

31 March 2006

Putting it altogether: to call or not to call under the base case Now we are ready to see whether this deal will be successfully auction-called or not, under our baseline assumptions. Our sample deal has the first auction date 6 years after the closing date. The equity payment required on the auction date is specified as “the difference between the original equity amount and all distributions on the equity on any prior payment date.” As shown in Exhibit 63, the total market value of the remaining collateral is sufficient to pay down both the notes and the equity and thus we expect the auction to be successful. st

Exhibit 63: Auction Call Results on 1 Auction Date (6 years after closing) Auction Date

6 years (or 24 quarters) after closing

(1) Total Liability Outstanding

$100,690,278

(2) Total Collateral Par Value (3) Total Equity Payment Required* (4) Market Value at Auction Call Date (5) Net: (2)*(4)-(1)-(3) To Call or Not to Call (if (5)>=0, call)

$125,597,977 $3,358,177 90.1%** $9,152,117 Call

* It is calculated as: $24,907,699 (total size of equity) - $21,549,522 (total amount has been paid to equity). ** The pool is expected to be BB-rated and a discount spread over forward LIBOR of 1200 bps is used. Source: Credit Suisse

In our sample example, the required payment on equity is simply the difference between the initial equity amount and total payments paid to the equity holders before the auction date. It is equivalent to having an IRR hurdle rate of 0%, i.e., discounting all payments at a discount factor of one. In some deals, the IRR hurdle could be higher. Obviously, the higher the hurdle, more payment is required and more difficult is the auction. st

Exhibit 64: Auction Results under Different IRR Hurdle Rates (on 1 Auction Date) Equity IRR

0%

2%

4%

6%

8%

10%

12%

14%

Total Liability Outstanding

100,690,278

100,690,278

100,690,278

100,690,278

100,690,278

100,690,278

100,690,278

100,690,278

Total Collateral Par Value Total Equity Payment Net To Call or Not to Call

125,597,977 3,358,177 9,152,117 Call

125,597,977 5,037,421 7,472,873 Call

125,597,977 6,994,275 5,516,019 Call

125,597,977 9,265,931 3,244,363 Call

125,597,977 11,894,037 616,257 Call

125,597,977 14,925,186 (2,414,891) No Call

125,597,977 18,411,458 (5,901,163) No Call

125,597,977 22,411,017 (9,900,722) No Call


We used different IRR rates from 0% to 14% to observe how the auction results change. As shown in Exhibit 64, if the IRR is 10% or higher, the auction will fail on the 1st auction date. Thus, it is important to pay attention to the magnitude of the IRR hurdle. If an auction fails on a specific auction date, another auction is held on the next auction date. Under a 10% IRR hurdle rate, the auction is successful in the 26th quarter after closing, as shown in Exhibit 65.

Exhibit 65: Auction Call Results under 10% IRR Hurdle Auction Date

24 quarters after closing


(1) Total Liability Outstanding

$100,690,278

$76,996,618

(2) Total Collateral Par Value (3) Total Equity Payment Required (4) Market Value at Auction Call Date (5) Net: (2)*(4)-(1)-(3) To Call or Not to Call (if (5)>=0, call)

$125,597,977 $14,925,186 90.1% ($2,414,891) No Call

$101,904,317 $14,767,534 91.8% $1,808,778 Call



61

31 March 2006

What if prepayments are slower? In a slower prepayment environment, the pay-down speeds on both asset/collateral and liability sides will slow down.

Exhibit 66: Collateral & Liability Factors under Slower Prepayment Assumption* 100% 90% 80% 70%

Factor

60% 50% 40% 30% 20% 10% 0% 1

3

5

7

9

11

13

15

Liability Factor_Slower Prepayment Liability Factor_Baseline

17

19

21

23

25

27

29

31

33

35

Quarter Collateral Factor_Slower Prepayment Collateral Factor_Baseline

Source: Credit Suisse * We stress the baseline prepayment (CPR) curve by 25%, i.e., a previous 10 CPR will be stressed to be 7.5 CPR.

As shown in Exhibit 66, in the 32nd quarter, the collateral factor under the slower prepayment scenario is 23% versus 7% under the baseline assumptions; while the liability factor under the slower prepayment scenario is 20% vs. 4% under the baseline assumptions. st

Exhibit 67: Auction Call Results on 1 Auction Date under Slower Prepayment Auction Date (1) Total Liability Outstanding (2) Total Collateral Par Value (3) Total Equity Payment Required (4) Market Value at Auction Call Date (5) Net: (2)*(4)-(1)-(3) To Call or Not to Call (if (5)>=0, call)

6 years (or 24 quarters) after closing $183,110,580 $208,018,279 $0 79.6% ($17,597,793) No Call


There are a couple of interesting observations. First, note that the required payment on equity is zero. This is because under a slower prepayment speed, more interest is generated from the collateral, and the equity is paid faster to the extent that the original amount is all paid off by the first auction date. Second, the projected market value on the auction date dropped significantly - from 90.1% in the baseline scenario to 79.6%. This is because the outstanding balance of the underlying collateral is much higher due to slower prepayment and thus larger denominator.71 It might make economic sense also: under our set-up, the originally BBB-rated pool migrates to a BB-rated pool; if this BB-rated pool has higher balance, it means relatively more bonds “go bad”. Under slower prepayment the remaining BB-rated pool is larger and if it can be regarded as a worse credit performance, it should get reflected in the market price. 71 Even though the numerator is also higher as cash flows are more back-end loaded, i.e., more cash flows come after the auction date.


62

31 March 2006

As it turns out, under slower prepayment scenario, this deal will not have a successful auction until the 34th quarter after closing. However, in reality, the note-holders have the right to vote to receive less than par for the auction to succeed. More importantly, in this case, the equity holders can actually receive more cash flows if the deal is not called while receive nothing from the call proceeds if called.72 However, since the equity holders have already received 100% of the original amount, they cannot stop the auction call.

What if default rate is higher? – Call fails in distressed scenario In a distressed scenario, the auction call usually fails. As an illustration, we stress our baseline default (CDR) curve by 250% (or two and a half times). Exhibit 68 shows the collateral and liability factors and, as expected, both factors decline very slowly and the collateral factor actually drops below the liability factor at around the 25th quarter. Exhibit 69 also shows the cumulative loss of the underlying pool of HEL bonds and the junior OC test. The junior OC (BBB OC) test failed around 20th quarter. As expected, the auction call fails on the first auction date. Exhibit 70 shows even on the 40th quarter, the auction call still fails.73

Exhibit 68: Collateral and Liability Factors under Higher Default Assumption* 100%

90%

Factor

80%

70% 60%

50% 40%

30% 1

3

5

7

9

11

13

15

17

19

21

23

25

27

29

31

33

35

Quarter Liability Factor

Collateral Factor

Source: Credit Suisse * We stress the default rate (CDR) by 250%, i.e., an original 5 CDR will be stressed to 12.5 CDR.

72 The equity holders will receive any surplus of the call proceeds after paying all the fees and note holders. However, they could face a situation as follows: suppose a bidder views the true value of the collateral to be higher than 79.6% and bids where the proceeds are just enough to pay note-holders while nothing is left for equity holders. The equity holders can’t do anything to stop it. If the equity holders also believe the true value of the collateral is higher, they should try to win the bid at a price they believe to be lower than the liquidation value of the collateral. 73 Under this stressed scenario, the senior OC level drops below 100% in the 36th quarter. Technically, this CDO is then in default and should be liquidated, however, this is a separate topic.


63

31 March 2006

Exhibit 69: Cumulative Loss of Underlying Collateral and Junior OC Test 20%

110%

18%

105%

16%

100%

Cumulative Loss

14%

OC Test

12% 10%

95% 90%

8%

85%

6% 4%

80%

2%

75%

0% 1 4

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39

7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61

Quarter

Quarter

Junior OCTarget

Junior (BBB) OCLevel


th

Exhibit 70: Auction Call Results on the 40 Quarter under Stressed Scenario Auction Date


(1) Total Liability Outstanding (2) Total Collateral Par Value (3) Total Equity Payment Required (4) Market Value at Auction Call Date (5) Net: (2)*(4)-(1)-(3) To Call or Not to Call (if (5)>=0, call)

$244,198,207 $225,514,807 $10,535,428 68.6%* ($100,106,313) No Call

* We still use the same spreads as in the baseline scenario. Arguably, given the stress level of this scenario, the market value of collateral could be stressed even lower. Source: Credit Suisse

Closing thoughts In general we can break down the auction call analysis into three scenarios: 1.

If the deal performs very well, it is most likely that both the note-holders and equity holders will be paid 100% and the auction call is automatically executed.

2.

If the deal performs very poorly, it is likely it will not have a successful auction call.

3.

If the deal performs “in between”, the auction might be successful but not necessarily on the first auction date. The note-holders and equity-holders might be willing to receive less than par if they believe the PV of future cash flows is less than that from the auction call proceeds. However, how much in received proceeds depends on the market value of the collateral and how much bidders are willing to pay. This is the beauty of the auction process yet makes the analysis difficult.

Most important, having reasonable prepayment and default assumptions is crucial for auction call analysis of new SF CDOs with a vast exposure to HEL bonds. We provide a framework, rather than a conclusion, for analyzing the auction call. Unfortunately, there is no empirical evidence, as no SF CDO has been auction called yet. It will be useful and interesting to observe different constituents’ behaviours in an auction.


64

31 March 2006

Default Assumptions for BBB HEQ in SF CDOs74 Executive summary In this report, we will answer the following two questions: 1) How do we calculate HEQ default rate in order to fit the special needs of CDO modeling? and 2) What is the reasonable baseline default rate assumption for triple-B HEQ bonds? We think Moody’s impairment rate is a better approximation for the default definition in typical recent SF CDOs. Based on how CDO pools are typically constructed, we also suggest using an “Aging Curve” to calculate default rate, instead of “Cohort Rate” or “Lifetime Rate.” 1.

Based on historical experience of impaired HEQ bonds, we suggest using a step curve of impairment/default rates, or a vector of rates, to represent the baseline annual default rate for triple-B HEQ bonds for SF CDO modeling.

2.

By comparing the expected return on equity, we also conclude that using this vector of rates is equivalent to using a flat annual rate (CADR) of 75 bps.

We hope our analysis will inspire further research. Over time, as more empirical evidence accumulates, additional insight will be revealed on this topic.

Overview It is important to use reasonable baseline default assumptions for mezzanine HEQ bonds in SF CDO modeling, as most mezzanine75 SF CDOs today may contain about 50% HEQ bonds. However, arriving at reasonable default assumptions for HEQ bonds is not a simple process. First, there is an inconsistency between the definition of default used in most default studies and that used in CDO documents. Secondly, commonly used default statistics, such as cohort and lifetime rates, are inappropriate for SF CDO modeling. With little empirical evidence on defaults for structured finance bonds, the market has looked at corporate bond experience for guidance. There are two main approaches. The first used by some market participants, including Fitch and S&P, begin with a commonly held view that “diverse” portfolios containing ABS and MBS should have a lower default risk profile than one with corporate debt securities. They adjust the default matrix of corporate bonds to reach a default matrix for SF bonds. 76 Alternatively, the second approach (used by Moody’s) makes use of the “Idealized Loss Rate” table both for corporate bonds/loans and for SF bonds. By assuming a recovery rate, the default rates of SF securities could be “backed out” and applied to CDO modeling. 77 A common weakness is little or no empirical evidence to support these approaches.

74

This section was originally published in "The CDO Strategist", Issue #1, May 11, 2005. Typical mezzanine SF CDOs have WARF around 360 (BBB level), while high grade SF CDOs usually have WARF around 20 (AA level). 76 See Fitch's special report titled "Rating Criteria for Cash Flow ABS/MBS CDOs", November 9, 2000, and S&P’s special report titled “Global Cash Flow and Synthetic CDO Criteria”, March 21, 2002. 77 Moody’s also apply different stress factors to the default rate used depending on target rating. For example, for a tranche to be rated Baa2, a factor of 1.23 will be used. 75


65

31 March 2006

A definition of default tailored for SF CDOs “Impairment Rate”: A Better Fit for CDOs

For CDOs, the definition of “default” for the underlying bonds ultimately affects the performance of the CDO. Once an underlying bond is designated as “defaulted,” it will be marked down to the lesser of market value OR estimated recovery value for the purpose of over-collateralization (OC) calculation. As the calculated OC is reduced, it may trigger pay-down of senior notes. A broader definition of default can thus lead to more and/or earlier pay-down, which potentially affects the performance of both debt and equity. In our opinion, we think an “impairment rate” might be a more suitable default measurement for SF CDO modeling. In a CDO, a structured finance security (SFS) is considered in “default” under the following events:

Impairment seems to fit CDOs’ default definition

Impairment is often more punitive than default

1.

There is a principal write-down or a PIKable bond that has not received interest payments for typically more than 6 months, or,

2.

A rating downgrade to Ca/C or lower by Moody’s, CC or lower by S&P or Fitch.

According to Moody’s, an impaired security is one that has:78 1.

Sustained payment default (including principal write-down and interest shortfall) that has not been cured, or,

2.

Downgraded to Ca or C (and is therefore expected to suffer a significant level of payment losses in the future)

While we believe the impairment rate is a more suitable default metric for SF CDOs, it is also a broader definition of default and therefore more punitive. It should be noted that it is possible for deferred cash flows owed to an impaired security to be eventually paid off in their entirety, avoiding an ultimate loss. However, it is often classified as a defaulted security by a CDO should it continue to defer payments for a period of time. Similarly, a bond that is downgraded to double-C may not incur an ultimate loss, but is also typically treated as a defaulted security in CDOs.

Life-time rate & cohort rate: not suitable for CDO modeling How do we calculate a suitable default rate? First, let’s take a look at two popular approaches used by rating agencies: “Cohort Rate” and “Lifetime Default Rate”: 1.

“Cohort Rate” – A cohort includes all outstanding HEQ bonds issued up to (and including) the beginning of the cohort unit: January 1 for annual cohort, or the first day of the month for monthly cohort. Should a bond default, it is included in the rating bucket that it started with at the beginning of the cohort. For example, take a bond issued in December 2000. Suppose it’s original rating is “BBB,” and it defaults in January 2003, the bond is included in the calculation of two-year (from January 2001 to January 2003), BBB default rate for the 2001 cohort.

2.

“Lifetime Rate” - Lifetime rates generally include all bonds issued during a specific timeframe.

A simplified example shown in Exhibit 71 clarifies the differences among the three default definitions: cohort rate, lifetime rate and vintage rate.79 Suppose bonds A1 and A2 are issued in January, 1999, B1 and B2 in January, 2000, and C1 and C2 in January 2001, etc.. The 2002 Cohort has eight bonds from A1 to D2; the 2002 Vintage has two bonds 78

“Payment defaults and material impairments of U.S. structured finance securities: 1993~2003,” September 2004, Moody’s. 79 The vintage rate here is a cumulative rate. For example, 2001 vintage rate is the total number of bonds defaulted divided by total number of bonds in 2001 Vintage, as of a specific date. Chapter 1. Structured Finance CDOs

66

31 March 2006

(D1 and D2); and the 2002-2005 Lifetime (lifetime rate always refers to a specific time period) includes 8 bonds from D1 to G2. For simplicity, we’ll assume that bonds A1, A2, B1, B2, C1, D1, and E1 all default in Jan. 2005. There are more defaults in older bonds as default risk increases with seasoning.

Exhibit 71: Comparing Differences: Cohort, Lifetime and Vintage Rates A1, A2

B1, B2

C1, C2

D1, D2

E1, E2

F1, F2

Jan, 1999

Jan, 2000

Jan, 2001

Jan, 2002

Jan, 2003

Jan, 2004

G1, G2

Jan, 2005

2002 Cohort: A1, A2, B1, B2, C1, C2, D1, D2 2002 Vintage: D1, D2 2002 - 2005 Lifetime: D1, D2, E1, E2, F1, F2, G1, G2 Bonds defaulted in Jan, 2005: A1, A2, B1, B2, C1, D1, E1 2002 Cohort Default Rate (as of Jan, 2005): 6/8 = 75% 2002 Vintage Default Rate (as of Jan, 2005): 1/2 = 50% 2002-2005 Lifetime Default Rate: 2/8 = 25% Source: Credit Suisse

We think the “Cohort Rate” and the “Lifetime Rate” are unsuitable for CDO modeling. The primary reason is that CDOs typically invest mostly in newly-issued bonds.80 As a result, most bonds in one CDO are usually in the same vintage as of the effective date. Cohort and Lifetime Rates: Caveats

1.

Cohort rates tend to be too high (too conservative). Since cohort rates include seasoned HEQ bonds from prior years and because defaults tend to rise as loans season, the cohort rate is usually higher than a vintage rate. As shown in Exhibit 71, the 2002 vintage rate is 50%, while the 2002 cohort rate is 75%.

2.

Lifetime rates tend to be too low (too optimistic). When calculating the lifetime rate, bonds defaulted during the period are divided by all the bonds issued in the same period which include some bonds issued during the back-end of the period (i.e., less seasoned). Because newer bonds have lower default risk, the inclusion of less-seasoned bonds will inherently “dilute” the true default rate. The example in Exhibit 71 shows that the 2002-2005 lifetime rate is 25%, much lower than the 2002 vintage rate as of Jan, 2005. As HEQ issuance has grown rapidly in recent years, the bias could become more significant if lifetime rate were used.

Our solution: aging curve of impairment rates Ideally, for CDO modeling purposes we should use a default curve that reflects bond seasoning. Given the small sample of impaired bonds – a total of 17 bonds in our sample – we create one aggregate aging curve instead of different aging curves by vintages. Here is how we derive the aging curve of impairment rate:81 1.

Line up all HEQ bonds originally rated BBB by age (month) and count the number of bonds at each age, and mark those bonds deemed “impaired” (Sub-Appendix I), 82 83

2.

Calculate the impairment rate by dividing the number of bonds impaired by the total number of bonds at each age (month).

80 For static deals, collaterals are generally accumulated within 3~6 months before/after the closing date; For managed deals, limited discretionary or credit trading is permitted, which may result in purchasing some seasoned bonds. 81 This approach has actually been widely used in cash flow modeling for most ABS such as home equity deals: CPR or CDR curves by age are usually created to generate cash flows. 82 Our default rate is based on deal count (not outstanding balance). This more closely reflects the nature of CDO pools, to the extent CDO collateral guidelines impose concentration limit on single-name exposure. 83 The list in Sub-Appendix I excludes corporate guaranteed or wrapped bonds.


67

31 March 2006

Exhibit 72: BBB HEQ Bonds Impairment Rate by Age (Month) We include HEQ bonds initially rated BBB (BBB+/Baa1, BBB/Baa2, BBB-/Baa3) and also use the lowest rating across three agencies.

3.0%

Impairment Rate

2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 0

6

12

18

24

30

36

42

48

54

60

66

72

78

Age of Bond (Tranche) Source: Credit Suisse, Moody's, S&P, Fitch, Intex

Exhibit 72 shows the result and there are several key points: 1.

There are usually no impairments prior to Month 36 (in our sample, only two bonds were impaired between Month 30 and Month 36). This is largely due to the step-down date of a HEQ deal which is usually 36 months. 84 Also, Exhibit 73 shows the cumulative loss of the underlying loans typically stays very low early on, and usually does not accelerate until approximately Month 18. It also appears that for a bond to be exposed to impairment risk – usually after Month 36 - the cumulative loss will reach at least 2%, as shown by Point A in Exhibit 73.

2.

The curve in Exhibit 72 is highly non-linear, which suggests that linear interpolation or taking a simple average of cumulative default rates is questionable.

3.

Since we track all BBB-rated HEQ bonds from 1998 to March 2005 in our database and Intex, we believe that this is a comprehensive and collective result, capturing the entire “cycle” of the HEQ sector thus far.

84 The step-down date is a very important date in typical HEQ deals. Before the step-down date, all collateral principal payments are distributed to AAAs, the mezzanine and subordinated bonds normally do not receive any principal. After the step-down date, if triggers are passed, OC is released and a large amount of principal could be channeled to subordinated and mezzanine bonds. However, if triggers are tripped, all principal payment will still go to AAAs and the subordinated and mezzanine bonds receive no principal for as long as the triggers remain tripped.


68

31 March 2006

Exhibit 73: Cumulative Loss of HEQ Loans by Vintage Fixed and ARM Combined 6%

5%

Cum Loss

4%

3%

2%

A

1% 2003

0% 0

6

12

18

24

2002 30

36

42

48

54

1998

1999

2000

2001

2002

2003

60

66

72

78

84

Age Source: Credit Suisse, "Subprime HEAT Update", February 2005.

Determining the impairment rate at bond level based on the cumulative loss experience of the underlying loans could be challenging. Because credit protection and subordinated classes act as barriers for senior classes, loan level loss experience may differ significantly from the loss experience of the securities supported. The rates in Exhibit 72 are not annualized. To derive an annual impairment rate, we count the number of bonds impaired in the past 12 months at each age (month), and divide this by the total number of bonds outstanding 12 months ago. We continue the calculation by rolling one month each time. For example, at age of 40 (months), we have 2 bonds impaired in the last 12 months, and with a total of 553 bonds outstanding 12 months ago (at Month 28), we end up with a 12-month impairment rate of 0.36% (2/553). One month later, at age 41, because there is one more bond impaired in the 41st month, we have 3 bonds impaired with 519 bonds outstanding at Month 29, resulting in a 12-month rate of 0.58%. The Curve A in Exhibit 74 is the 12-month rolling impairment rate and the Curve B is a step function we fitted to Curve A. The functional form of Curve B is:

ª « I mpairment Rate (bps) = « « « ¬

if 0 <= age <= 36 0, 40, if 36 < age <= 48 230, if 48 < age <= 66 650,

if age > 66

We recommend using this step curve of impairment rate for SF CDO modeling. As BBB HEQ bonds usually do not become impaired in the first 36 months, we think a zero impairment rate for the first 36 months reflects the reality. While the rate appears high at the back-end of the curve, one has to keep in mind that typical BBB HEQ bonds have an average life of 3.5-5 years. This fact has two implications: 1) bonds with the majority of their balance still unpaid after 66 months are more likely to be in trouble;85 and 2) as most of the bonds do not become impaired and the majority of their balances are paid off during the first 5 years, more weights are placed on the earlier years. 85

For example, if a deal has been performing badly and, as a result, triggers are tripped and OC can not be released to pay down subordinated and mezzanine bonds after step-down date, the balance of BBB bonds could remain unpaid for a while until the triggers are passed. Chapter 1. Structured Finance CDOs

69

31 March 2006

Exhibit 74: Annual Impairment Rate vs. Fitted Step Curve of Impairment Rate 900 800

Impairment Rate (bps)

700 600 500

Curve A: 12-Month Rolling Impairment Rate

400 300 200

Curve B: Fitted Step Curve of Impairment Rate

100 0 0

6

12

18

24

30

36

42

48

54

60

66

72

78

Age of Bonds Source: Credit Suisse

The Impact on Equity Returns We used a generic cash flow model of a mezzanine SF CDO to illustrate the impact of our vector of BBB HEQ default rate – the step function - on the expected equity returns (Exhibit 75). Current market spreads for both assets and liabilities were used in our model and the portfolio contains: 50% HEQ, 20% Residential-A mortgages, 15% CBO tranches, 11% CMBS, and 4% other ABS assets such as credit card receivables.86 We changed the baseline default assumptions for HEQ bonds while holding the default assumptions constant for the remaining collateral to see the sensitivities of expected equity returns to different default assumptions of HEQ bonds (Exhibit 75). Using our aging curve of impairment rate, our model generates an expected return of 13.45% for equity. We also used three (annual) flat impairment rates – 75 bps, 60 bps and 25 bps. The expected return using 75 bps is very close to the result of using the step curve. Thus, if a flat default rate is needed, we would suggest using a constant annual default rate of 75 bps for BBB HEQ bonds.

Exhibit 75: Default Assumption of BBB HEQ Bonds vs. Expected Equity Return

Scenario Using our Step Curve Using a Flat Impairment Rate Using a Flat Impairment Rate Using a Flat Impairment Rate

Baseline Annual Default Rate ofHEQ BBB Bonds (bps) A vector of impairment rates in Equation 1 75 60 25

Aggregate Default Expected Equity Rate (bps) Return NA 50 43 25

13.45% 13.46% 13.91% 15.12%


86 We used a constant annual default rate for Residential A, CBO, CMBS and other ABS, which are 10, 20, 25 and 35 bps respectively.


70

31 March 2006

Appendix I. Impaired BBB* Rated HEQ Bonds (1997~2004) Exhibit 76: Issuer

# of bonds

Vintage

13 4 4 3 3 1 1 1 1 1

1997, 1998, 1999 1996, 1997, 1998 1997, 2000, 2001 1997, 1998 2000, 2001 2000 1998 1998 1997 2000

ContiMortgage Home Equity Loan Trust GE Capital Management Services Delta IMC Home Equity Loan Trust IndyMac Home Equity Mortgage Loan Conseco Finance Home Equity Loan 2000-B AMRESCO Residential Mortgage Loan Trust 1998-1 Ocwen Residential MBS Corp. Mortgage Pass-Through, 1998-R3 Southern Pacific Saxon

The list excludes corporate guaranteed or wrapped bonds. * This include HEQ bonds initially rated BBB (BBB+/Baa1, BBB/Baa2, BBB-/Baa3). We also use the lowest rating across three agencies Source: Credit Suisse, Moody’s, S&P and Fitch.

Appendix II. Cumulative Impairment Rates by Vintage Rather than calculating aging curves by vintages, we calculate in Exhibit 2 cumulative and annual impairment rates of each vintage to show the different performance of different vintages: 1998 vintage has the highest annual rate of 1.54% followed by 2000 and 1999 vintages with 1.21% and 0.87% respectively; 2001 vintage come in the middle of the ranking with 0.42%; newer vintages after 2002 all have zero impairment rate so far. There are two problems in using the annual rate in Exhibit 77: 1.

As the performance is dramatically different across vintages, we face the dilemma of picking which vintage(s) to use. Trying to assess vintage idiosyncratic behavior is not an easy task and may not be reliable. Please refer to Appendix II for a description of the evolution of HEQ market.

2.

Because the impairment curve by age is non-linear, as we pointed earlier, taking a simple average of a cumulative rate is questionable.

Exhibit 77: BBB* HEQ Cumulative Impairments by Vintage HEQ Issuance year 1998 1999 2000 2001 2002 2003 2004

Total # of original Total # of impaired rated BBB HEQ Cumulative%(3)=(1) Annualized%(4)=(3)/ original rated BBB HEQ /(2) (years to date) issued in the year(1) issued in the year(2) 8 3** 4 2 0 0 0

74 54 70 144 317 697 1122

10.8% 5.5% 5.7% 1.4% 0% 0% 0%

1.54% 0.87% 1.21% 0.42% 0.00% 0.00% 0.00%

* This include HEQ bonds initially rated BBB (BBB+/Baa1, BBB/Baa2, BBB-/Baa3). We also use the lowest rating across three agencies. ** All three impairments are ContiMortgage bonds. Source: Credit Suisse, Moody’s, S&P, Fitch


71

31 March 2006

Appendix III. The Evolution of HEQ Market Pre-1996 Nascency In the early 1990s, home equity loans generally referred to second-lien loans. The market was dominated by a few specialized lenders, and mainstream banks active in mortgage financing did not actively participate. 1996~1998 Initial Growth The HEQ market grew rapidly between 1996 and 1998, almost tripling in annual issuance. This is largely attributable to: 1) A few mainstream banks began to lend to the subprime market; 2) More non-bank lenders were able to make loans as securitization offered an alternate source of funding; 3) Improved credit scoring technology helped lenders to better understand and price borrower credit risk. During this period, the market shifted from second-liens towards subprime first-liens. Also, strong competitive pressures led to the loosening of underwriting standards and the introduction of higher LTV programs by new lenders to capture market share. 1999~2001 Consolidation There was a major shakeup among subprime lenders between 1999 and 2001. Threefourths of the active lenders either exited due to financial problems or merged with larger players. Some of the notable issuers to exit or during this period include ContiMortgage, First Plus, Equicredit, The Money Store (acquired by First Union), and Green Tree (acquired by Conseco). Other lenders were acquired by larger players, such as Advanta (by JPMorgan), and Associates (by CitiMortgage). The financial problems among lenders were mainly caused by a combination of lax underwriting standards, aggressive gain-onsale income accounting, and unfavorable market conditions after the liquidity crisis in 1998. 2002~2004 Expansion The HEQ market expanded drastically since 2002. Some of the key drivers are:


1.

Increased loan origination due to record high purchases and refinancing motivated by historically low mortgage rates, and more cash-out financing resulted from strong housing price appreciation.

2.

Increasing use of securitization for funding and the advent of net interest margin (NIM) technology. In 2001, issuers began to more regularly monetize the senior component of residual cash flow in the form of a NIM security. This enables ABS issuers to maximize deal issuance proceeds and reduce or eliminate residual risk. The rapid growth of NIM securitizations prompted some dealer conduits to enter the securitized HEQ market after 2001.

3.

The subprime market has expanded to include borrowers that were traditionally covered by Alt-A lenders.

72

31 March 2006

Using the Right Rating Performance Measures of SF Securities for CDO Analysis87 The default rate is one of the most important parameters in rating CDO tranches. The loss distribution of the underlying collateral is derived by incorporating a pre-determined default matrix based on the historical default experience of corporate bonds, such as Moody’s Idealized Loss Rates, and a loss model: Moody’s BET (Binomial Expansion Technique) or CBM (Correlated Binomial) applies a single statistic (WARF) to generate the loss distribution, while S&P’s Evaluator and Fitch’s VECTOR takes a simulation-based approach, deriving the default probability of each asset from its rating. Rating agencies periodically publish their default and loss studies or rating transitions of structured finance (SF) securities. These results could serve as benchmarks to assess the reasonableness of assumptions used by underwriters in modeling and structuring a new SF CDO. Investors may also use these results to make asset allocation decisions, under the assumption that these measures can separate the “good performers” from the “bad performers” and that the future will follow the past. Ideally, we should be able to find the desired figures from the agencies’ reports with ease. In practice however, we often find ourselves swamped by all the tables and numbers and the various methodologies used. In this section, we discuss some of the nuances of rating agencies’ rating performance measures and recommend the appropriate numbers to use for CDO analysis.

Things to keep in mind Based on our experience, we suggest checking at a minimum, the following points to correctly understand rating transition numbers to be able to conduct true “apples-to-apples” analysis: 1.

What products, such as HEL, resi-A, credit receivables, and etc., are included in each category, i.e. ABS, CMBS or RMBS?

2.

Are the numbers calculated by cohort rating or original rating?

3.

Are the numbers based on dollar amount or number of bonds?

4.

What’s the frequency of the data; monthly, yearly, or other?

5.

Are the numbers global or only US?

6.

Are the numbers weighted or un-weighted, and if weighted, how?

7.

Are the numbers adjusted for withdrawn ratings?

Even if these questions are answered, there still remains the most important question: how are the numbers actually calculated? We address this later.

87


This section was originally published in "The CDO Strategist", Issue #9, October 19, 2005.

73

31 March 2006

Moody’s and Fitch classify HEL into ABS, while S&P puts HEL into RMBS

For the first question, all three agencies group SF securities into 3 categories: ABS, RMBS and CMBS.88 However, Moody’s and Fitch put HEL/subprime mortgage into “ABS”, while S&P puts HEL/subprime mortgage into “RMBS”.

For CDO analysis, statistics based on original ratings are more meaningful than those based on cohort ratings

As for the inclusion-universe of the rating transition numbers, we think numbers based on original ratings are more suitable than those based on cohort ratings.89 Cohort rates tend to over-estimate the actual numbers as a cohort includes seasoned bonds and defaults tend to rise as loans season for most SF securities.90 As CDOs invest mostly in recentlyissued assets, cohort rates are not suitable.

Exhibit 78: Five-Year Cumulative Impairment Rates of Home Equity Bonds by Original and Cohort Rating, 1993-2004* 60% 5-Year Cumulative Impairment Rate

51.82%

50%

Original Rating 40.02%

Cohort Rating

40% 30%

41.13%

26.88%

20% 14.09%

10%

6.99% 3.11%

2.35%

0% A

Baa

Ba

B

Original or Cohort Rate * Moody’s Special Comment: “Default & Loss Rates of Structured Finance Securities: 1993-2004”, July 2005. Rates of Aaa and Aa rated are not shown as they are all zero. Source: Moody’s

As indicated by Exhibit 78, based on Moody’s 5-year cumulative impairment rates, the difference between original rating-based rates and cohort rating-based rates may be very significant: for Baa-rated bonds, the latter could double the former.

Moody’s Material Impairment Rate An impairment rate includes uncured payment default, and downgrade to Ca or below

Since 2002, Moody’s conducts an annual study of the impairment rate of SF securities. As Moody’s does not have a “default” rating, this study has significant implications in the sense of “filling the gap”.91 An impairment rate includes uncured payment default, interest shortfall or principal write-down, and downgrade to Ca or below. Although generally speaking, the impairment rate is broader than default rate, we think it is the most appropriate figure for CDO analysis for the following reasons: 1.

Generally consistent with how defaults are defined in SF CDOs.

2.

The only study, among all provided by rating agencies, that provides numbers based on original ratings in addition to cohort ratings.

88

Recently, they also added a CDO category. A cohort includes all outstanding bonds issued up to (and including) the beginning of the cohort unit, such as 1-year or 5-year cohort. 90 For a detailed discussion on cohort rates, please refer to: “The CDO Strategist - Default Assumptions for BBB HEQ in SF CDOs”, May 11, 2005. 91 The lowest rating of Moody's is "C", while S&P has a "D" rating which corresponds to "default". 89


74

31 March 2006

3.

The methodology, by which the numbers are calculated, makes the most sense, in our view. A more detailed explanation and numerical examples are provided in Appendix I.

4.

Comprehensive numbers, broken down by sectors (including HEL), ratings and terms, are publicly available.

However, there are still some issues and nuances one needs to be aware of when applying the impairment rates to CDO analysis.

How are default assumptions applied in CDO modeling? Let’s take a moment to briefly review how default assumptions are applied in the CDO modelling process. Most equity marketing books or CDO term sheets have a chart similar to Exhibit 80, which shows projected equity returns of a mezzanine (with collateral average rating of BBB) SF CDO under different default rates. How should this chart be interpreted?

Exhibit 79: Illustrative Equity Returns by Default Rates (of a MZ SF CDO)* 20% 15%

15.1%

13.6%

12.0%

Equity Return

10%

10.1%

8.1% 5.7%

5%

2.9%

0%

-0.2%

-5%

-3.5% -7.1%

-10%

-10.8% -15% 0.00%

0.25%

0.50%

0.75%

1.00%

1.25%

1.50%

1.75%

2.00%

2.25%

2.50%

Annual Default Rate * Calculated to 9-year auction call date. Recovery assumption is 60% with 1-year lag. Source: Credit Suisse

The “Annual Default Rate” is a constant annual default rate (CADR). Take the 0.5% CADR as an example: this means that if the default rate of the underlying bonds stays the same at 0.5% per year, the return to the equity holder, if calculated to the first auction call date 9 years later, will be 12%. One thing to keep in mind: the default rate is applied at the “bond” level and to the remaining performing dollar balance.92 The 0.5% CADR implies a 5-year cumulative default rate of about 2.48%.93 Alternatively, we can also specify a cumulative default rate first, say, 2.5% for 5 years. Then we need to decide how to allocate this 2.5% over the 5-year period, i.e., the default timing. Rating agencies will normally stress different default timing patterns – front-loaded, back-loaded or evenly-distributed – during the rating process. We will discuss empirical evidences as to the default timing later. By the same token, Exhibit 80 shows a similar chart but for a high grade SF CDO. In this hypothetical deal, a 0.1% CADR implies a return of 12.7%.

92

Although we always prefer to model the deal at the "loan level", meaning each loan underlying the HEL or RMBS deal, in reality most of the new-issue SF CDOs are modeled at the bond level. 93 Based on the method discussed in Appendix I. Chapter 1. Structured Finance CDOs

75

31 March 2006

Exhibit 80: Illustrative Equity Returns Varying by Default Rates (of a HG SF CDO) 20% 15%

14.3%

12.7%

11.0%

Equity Return

10%

9.1% 6.9% 4.4%

5%

1.7%

0% -1.2%

-5%

-4.4% -7.8%

-10%

-11.5%

-15% 0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

0.8%

0.9%

1.0%

Annual Default Rate Source: Credit Suisse

We discuss some important points about the cumulative default rate: 1.

Using different units of time to calculate the default rate, such as monthly, yearly, or others, makes a huge difference: a 5-year default rate using 5-years as the unit could be much lower than a 5-year default rate using an iterative process of annual default rates, as discussed in Appendix I. This is similar to the compounding effect in interest rate calculations.

2.

A cumulative default rate could imply the following: 1)

It could mean the percentage of assets defaulted during the time period. For example, if there are 100 assets initially, a 5-year default rate of 5% could mean that 5 assets defaulted over the 5-year period.

2)

OR, it could also mean the probability for an asset to default over the period. A 5-year default rate of 5% means, for each asset, there is a 5% chance it will default by the end of the 5th year. Alternatively, it could “survive” to the end of the 5th year with a probability of 95%.

It is crucial to understand these differences. As we will show below, different rating agencies use different methods to calculate the numbers and the conclusions could be dramatically different. For example, Moody’s calculation is consistent with the second interpretation while S&P’s calculation is more in the spirit of the first definition.

Using the impairment rates of the right sectors Due to adverse economic conditions, accounting and underwriting issues, and credit deterioration in certain industries, some ABS sectors have suffered significant downgrades and losses.


76

31 March 2006

Exhibit 81: Distribution of US ABS Impairments by Asset Type (1993-2004) Asset Type Manufactured Housing Franchise Loans Healthcare Receivables Aircraft & Equipment Leases Home Equity Auto and Trucks Credit Card Other ABS Total

Number of Impaired Securities from 1993-2004

Total Number of Securities Studied*

Percentage**

263 57 12 51 95 12 13 1 504

662 148 32 341 3980 837 1500

39.73% 38.51% 37.50% 14.96% 2.39% 1.43% 0.87%

7500

6.72%

* Securities issued in 2004 are not included, and there are no impairments in 2004 vintage securities. ** These percentages could be viewed as the Lifetime Impairment Rates. Source: Moody’s Special Comment: “Default & Loss Rates of Structured Finance Securities: 1993-2004”, July 2005, and “Default & Loss Rates of Structured Finance Securities: 1993-2003”, September, 2004

Exhibit 81 shows the distribution of all securities impaired from 1993 to 2004 by ABS sector. As we can see, the 3 worst-performing sectors in terms of impairments are MH, Franchise Loans and Healthcare Receivables, of which almost 40% of the securities are impaired. Furthermore, more than half of all impairments come from MH sector (263 out of 504 securities). Given the significant exposure to these troubled sectors, many old vintage (1999-2002) SF CDOs have also suffered disappointing performances. However, recent vintage SF CDOs have stayed away from these sectors to the extent that most deals nowadays have zero exposure to them. Instead, the majority of the collateral is invested in residential mortgage related assets such as home equity and Resi-A. Thus, we think it is more relevant to look at the impairment rates of residential mortgage sectors. Exhibit 82 shows Moody’s 5-year cumulative impairment rates for US HEL, RMBS and CMBS sectors based on the data from 1993 to 2004. 94 There are several interesting observations from these numbers: 1.

For Aaa- and Aa-rated HEL and CMBS, there are NO impairments during any 5year period.

2.

Moody’s rates are calculated based on the number of bonds, rather than the dollar amount.

3.

If assuming a high grade deal, with average underlying asset ratings of Aa and an allocation of 50% HEL, 35% RMBS and 15% CMBS, the combined 5-year cumulative impairment rate is about 0.51%.

4.

Using the same allocation, but for a mezzanine SF CDO with average underlying rating at Baa, the combined 5-year cumulative impairment rate will be about 6.7%.

5.

For Ba-rated HEL, the impairment rate jumped significantly: from 6.99% at Baa rating to 26.9% at Ba rating.

We believe the way Moody’s treats withdrawn ratings when calculating the numbers is conservative (see Appendix I). The numbers without adjusting for withdrawals will be lower.

94

In its Special Comment: “Default & Loss Rates of Structured Finance Securities: 1993-2004”, July 2005, Moody's for the first time published impairment rates of HEL alone.


77

31 March 2006

Exhibit 82: Moody’s 5-Year Cumulative Impairment Rates by Original Rating and Sector (1993-2004) 30%

26.88%

25%

20%

15%

10%

6.99%

5% 0.00%

1.02%

0.00%

0.00%

1.45%

2.35% 0.00%

8.45% 6.05% 3.75% 1.62%

1.20% 0.66%

0% Aaa

Aa

A US HEL

US RMBS

Baa

Ba

US CMBS

Source: Moody’s Special Comment: “Default & Loss Rates of Structured Finance Securities: 1993-2004”, July 2005

Another reason the impairment rates at the Baa and Ba levels might seem higher than expected is that Moody’s 2004 study changed the unit of measurement from calendar years to months.95 As a result, the impairment rates are higher than those using calendar years, according to Moody’s. Finally, it is also interesting to take a deeper look at the impaired securities. In Exhibit 83 we list the number of impaired HEL bonds by vintage and original ratings. There are a couple takeaways: 1.

There have been no impairments for HEL bonds rated A1 or higher.

2.

There have been no impairments for HEL bonds issued after 2001.

Exhibit 83: Number of Impaired HELs by Vintage and Original Ratings (1993-2004) Vintage

A2

A3

1994 1995 1996 1997 1998 1999 2000 2001 Total

Baa1

Baa2

Baa3

Ba1

Ba2

B2 1

1 3

2 2 3 6 2 1 6 22

B3

2

1 1 1 1 4

1 2 2 1

6

2

1

3

Total

1 3 3 1 2 10

6 4 3 2 15

3 7

1 4 9 4

18

1

4 7 19 25 12 5 12 86

Source: Moody’s, Credit Suisse

Default timing is just as important as the default rate. Moody’s publishes impairment rates of 1-year up to 5-years. Based on their calculation (see Appendix I), we “back-out” the “marginal impairment rates”, i.e., the impairment rate in each year given the bond has not been impaired in the previous year.

95


And so going forward, according to Moody's.

78

31 March 2006

Exhibit 84: Marginal Impairment Rates by Years Since Origination 5.0%

Marginal Impairment Rate

4.5%

4.53% Baa HEL

Baa RMBS

3.87%

4.0% 3.5% 3.0%

2.66%

2.5%

1.94%

2.0%

1.56%

1.5% 1.0% 0.5% 0.0%

0.65% 0.00%0.08% 1-Year

0.15% 2-Year

0.46%

3-Year

4-Year

5-Year

Years since origination Source: Moody’s, Credit Suisse

Exhibit 84 shows our calculated marginal default rates of Baa-rated HEL and RMBS based on Moody’s cumulative rates. Surprisingly, contrary to traditional wisdom, which holds that default timing for HEL and RMBS securities is front-loaded, the Baa-rated HEL bonds show a back-loaded default timing pattern – default rates appear to increase faster in later years than in earlier years. Baa-rate RMBS exhibit a similar pattern except that its marginal rate peaks in the 4th year and drops significantly in the 5th year.96 Although SF CDOs invest mostly in new-issue securities, they also invest in seasoned bonds. So, for example, using these marginal rates, a one-year seasoned Baa-rate HEL bonds should be assigned a default rate of 0.15% rather than 0% for the first year, 0.46% instead of 0.15% for the second year and so on.

Other rating performance measures While all rating agencies, Moody’s, S&P and Fitch, publish performance measures such as rating transitions, we think they are less applicable to SF CDO modeling. The main reasons include: 1.

All the rating transitions available are based on cohort ratings. As we discussed previously, this limits their suitability for modeling CDOs.

2.

Some rating transitions, such as S&P’s, are calculated based on “rolling cohorts” and the term of the cohort depends on the term of the transition rate. For example, to calculate the 5-year transition, a 5-year cohort needs to be formed. Thus, a bond must be 5 years seasoned for it to be included in the calculation of the 5year transition rate. While this approach is easier to understand, it misses data for the most recent 4 years when calculating a 5-year transition rate.97

96 Unfortunately, Moody's only provide cumulative rates up to 5 years. Otherwise we would be able to derive marginal rates for more seasoned bonds. 97 A bond issued, say, 4 years ago, can not be used to calculate a 5-year transition rate since it does not have performance history longer than 5 years.


79

31 March 2006

We deem rating transition studies very important for ad hoc performance reviews and comparisons. One common argument is SF securities are more stable rating performers than corporate bonds. As shown in Exhibit 85 and Exhibit 86, based on both Moody’s and S&P’s annual rating transitions, HEL/RMBS outperforms corporate bonds as they have a much lower chance of being downgraded across most rating categories. Fitch’s results also shares similar conclusions.

Final Thoughts Moody’s ratings are ultimately determined by the expected loss rate, rather than the default rate. Moody’s Idealized Loss Rates, which are based on the default experience of corporate bonds, are used to derive the default rates of SF securities for SF CDOs. These corporate loss rates are also calculated based on cohort ratings. We think a better measurement and benchmark system of default rates needs to be developed for SF CDOs. The rating performance studies conducted by rating agencies are certainly valuable for achieving this goal, but it remains to be seen how the current study results can be incorporated into the rating processes. In our view, to date, Moody’s Impairment Rates are the most suitable. The new year is coming, and here is our resolution: an ideal measurement of SF securities default rate, calculated based on dollar amount and original ratings, separated by different sectors, and with the default definition as close as possible to CDO standards. Both marginal and cumulative rates are needed. To achieve this, further studies by rating agencies are needed.

Exhibit 85: Downgrade Rates from Moody’s Annual Ratings Transition Matrices* 12%

10.9%

10.5% 10% 8.5%

8.3%

8.4%

8.1%

8% 6.4%

6.4% 6%

4.9% 3.8%

3.7%

4%

3.0% 2.0%

2% 0.1%

0.4%

1.7%

2.1%

0.5%

0% Aaa

Aa

HEL Downgrade Rate

A

Baa

RMBS Downgrade Rate

Ba

B

Corporate Downgrade Rate

* By COHORT. For corporate bonds, the sample period is 1983-2004; for HEL and RMBS, the sample period is 1990-2004 Source: Moody’s Special Comment:: “Structured Finance Rating Transitions: 1983-2004”, February 2005


80

31 March 2006

Exhibit 86: Downgrade Rates from S&P’s Annual Ratings Transition Matrices* 12%

11.0% 10.3%

10%

8.9% 8.3%

8% 6.5%

6.0%

6% 4.5% 4% 2.8% 1.8%

1.5%

2%

1.2%

0.2% 0% AAA

AA

A

BBB

RM BS Downgrade Rate

BB

B

Corporate Downgrade Rate

* By COHORT. S&P’s RMBS include subprime mortgage transactions Source: S&P: “Global Structured Securities Rating Performance: 1978-2004”, March 2005

Appendix I. Moody’s Impairment Rates by Original Ratings To explain how Moody’s calculates its cumulative impairment rates by original ratings, we use an example. Here, we show how a 3-year rate is calculated.98

Exhibit 87: Illustration of Calculating Moody’s Cumulative Impairment Rates by Original Rating Year 1 Rating

Beginning

Year 2 End

Rating

Impaired

Withdrawn

0

10

Year 3

Beginning

End

Rating

Impaired

Withdrawn

Beginning

End Impaired

Withdrawn

Vintage Year 1 Baa

100

Baa

88

2

10

Baa

74

4

10

Ba

2

1

0

Ba

2

1

0

B

1

1

0

Baa

86

0

10

Ba

2

1

0

200

2

20

Vintage Year 2 Baa

100

4

8

Vintage Year 3 Baa Source: Moody’s, Credit Suisse

Suppose the sample period starts from Year 1 and there were 100 Baa-rated bonds at the beginning of Year 1, which we call “Vintage Year 1”. The top block in Exhibit 87 tracks the status of these 100 bonds during the 3-year period. For example, at the beginning of Year 3, only 74 bonds remain at Baa, 4 of which became impaired and 10 of which were withdrawn in Year 3.

98


This example is purely hypothetical and for illustration only.

81

31 March 2006

At the beginning of Year 2, 100 more Baa-rated bonds were issued which we call “Vintage Year 2”, and the middle block in Exhibit 87 tracks the status of these 100 bonds in the next 2 years. At the beginning of Year 3, 200 more Baa-rated bonds were issued which we call “Vintage Year 3”, of which 2 were impaired and 20 were withdrawn in one year. To calculate the first year Baa-impairment rate, all the numbers highlighted in yellow are included, i.e., the first-year experience of all the bonds in 3 vintages are used. The withdrawn ratings are adjusted by taking half of the withdrawals off the denominator. The weighted average first-year marginal impairment rate is calculated as: (0+4+2)/(100+100+200-10/2-8/2-20/2) = 1.57% To calculate the second year marginal Baa-impairment rate, all the numbers highlighted in pink are included. Therefore, numbers from only 2 vintages, Vintage Year 1 and Vintage Year 2, are used. It is calculated as follows: (2+0)/(88+86-10/2-10/2) = 1.22% By the same token, the third year marginal Baa-impairment rate can be calculated by using only the numbers of Vintage Year 1, highlighted in gray. It is calculated as: 4/(74-10/2) = 5.8% The cumulative rates are calculated using an iterative process. The 2-year cumulative rate is calculated as: 1-(1-1.57%)*(1-1.22%) = 2.78% A 2-year survival rate is calculated first, (1-1.57%)*(1-1.22%), and then the 2-year cumulative impairment rate is 1 minus the survival rate. Similarly, the 3-year cumulative rate is calculated as: 1-(1-1.57%)*(1-1.22%)*(1-5.8%) = 8.41% This methodology is also used for calculating the impairment rates by cohort ratings and is consistent with how Moody’s derives its corporate default rates.99 We view this as a very reasonable approach. However, there is one downside when using original ratings. For example, notice that there are 2 bonds in Vintage Year 1 that were downgraded to Ba in Year 1 (in Exhibit 87, there are 2 bonds which begin Year 2 at the Ba rating), and these 2 bonds will not be included in the calculation of the impairment rates of Ba rating as they are NOT originally rated Ba. Thus, some useful information might be lost among the calculations.

99 Please see Moody's Special Comment: "Default & Recovery Rates of Corporate Bond Issuers: 19702001", February 2002.


82

31 March 2006

Appendix II. List of Select Publications on Rating Performance by Rating Agencies Exhibit 88: Select Publications on Rating Performance by Rating Agencies Rating Agency

Report Title

Publication Date

Moody's Moody's Moody's Moody's Moody's Moody's Standard & Poor's Standard & Poor's Fitch Fitch Fitch

Default & Loss Rates of Structured Finance Securities: 1993-2004 Default & Loss Rates of Structured Finance Securities: 1993-2003 Payment Defaults And Material Impairments of U.S. Structured Finance Securities: 1993-2002 Structured Finance Rating Transitions: 1983-2004 Structured Finance Rating Transitions: 1983-2003 Structured Finance Rating Transitions: 1983-2002 Global Structured Securities Rating Performance: 1978-2004 Structured Finance Global Ratings Roundup Quarterly Fitch Ratings 1991-2004 Structured Finance Transition Study Fitch Ratings 1991-2003 Structured Finance Transition Study Structured Finance Rating Transition Study

July-05 Sep-04 Dec-03 Feb-05 Feb-04 Jan-03 Mar-05 Quarterly Mar-05 Nov-04 May-02



83

31 March 2006

Impact of S&P’s New Rating Criteria on SF CDOs100 Standard and Poor’s recently revised its proprietary CDO modeling tool, CDO Evaluator, from Version 2.4.3 (E2) to Version 3.0 (E3). For now (January 2006), the new Evaluator is only being applied to synthetic CDOs with no excess spread. However, as S&P has indicated, the same model will be applied to cash CDOs, hybrid CDOs, and synthetic CDOs with excess spread too, most likely in early 2006 when additional cash flow criteria are finalized. It is crucial for the CDO market to understand the implications of the new methodology. In this section, we focus on the impact of E3 on SF CDOs.

New default rate assumptions for ABS securities One of the key changes in E3 with potential implications on SF CDOs is the new default rate assumption for ABS securities. There is no change in ABS securities’ correlation assumptions and the recovery rate changes have minimal impact as the ABS recovery rates are user defined in the model.101 Previously in E2, the ABS default rates were derived by using corporate default rates as a proxy and the rates were one-dimensional – i.e., by ratings only, regardless of maturity. E3 uses a two-dimensional default matrix – by rating and by maturity. According to S&P, this matrix is built based on historical transition rates. By comparing the numbers, we made the following observations: 1.

S&P assumes an upward sloping default curve by maturity. The new model gives benefit to shorter maturity securities by assuming a relatively steep default curve, i.e., the default rates for shorter maturities are much lower than the rates for longer maturities. Exhibit 89 shows BBB default rates as an example - the new default rate starts very low at a 1-year maturity and converges to the old (E2) default rate at 2%.

2.

Compared to the previous default curve, depending on maturity, the new default rates could be higher or lower. At longer maturities, for ratings above BBB, the new default rates are much lower; while below BBB, the new default rates are much higher; for shorter maturities, all new default rates are lower. Exhibit 90 shows the 7-year cumulative default curve by rating in E3 as much steeper than E2.102 However, the 5-year cumulative default curve falls below the previous curve in E2 almost across all ratings. S&P capped the default rate of ABS securities at the 7th year, i.e., after year 7, the cumulative default rate does not increase and thus there are no additional defaults (i.e., the marginal default rate is assumed to be zero after 7 years). The “bad” news is, because legal maturities are used in E3 and ABS securities have typically very long legal maturities, the 7-year default rates are almost always used. So in reality, the “credit” given to shorter securities may never be “cashed”. All these nitty-gritty details will have profound impact on SF CDO ratings – both in mezzanine and high grade deals – we discuss more in detail later.

100

This section was originally published in "The CDO Strategist", Issue #13, January 25, 2006. In E3, stochastic recoveries can be used in addition to constant recoveries for corporate bonds or loans. But for ABS securities, there is no change regarding recovery. 102 A detailed default matrix can be found in Appendix I. 101


84

31 March 2006

Exhibit 89: BBB Default Rates by Maturity in Evaluator 3 & Evaluator 2

Cumulative Default Rate

2.5% 2.0% 1.5% 1.0% BBB Cum Default Rate in E3

0.5%

BBB Default Rate in E2 0.0% 1

2

3

4 Maturity

5

6

7


Exhibit 90: Default Rates of ABS in Evaluator 3 and Evaluator 2


16% 14%

E2 ABS Default Rate

12%

E3 ABS Default Rate (7 year) E3 ABS Default Rate (5 year)

10% 8% 6% 4% 2% 0% AAA

AA+

AA

AA-

A+

A

ABBB+ Rating

BBB

BBB-

BB+

BB

BB-



85

31 March 2006

New default rate assumptions of CDO tranches The CDO default rate matrix in CDO Evaluator serves two purposes: 1.

It determines the default rate to be used for each CDO tranche in the underlying asset pool when assessing their default risk.

2.

It also determines the subordination levels of the CDO being rated – it can serve as a confidence level to find the cutoff point – the Scenario Default Rate (SDR) – and consequently the Scenario Loss Rate (SLR) and the subordination levels of each tranche. For example, if we are to rate a tranche “AAA” and the associated default rate of an “AAA” rating is 0.5%, the SDR is determined such that the chance of the default rate of the underlying collateral being higher than this SDR is less than or equal to 0.5%. All things equal, the higher the default rate of the target rating (i.e., more defaults are allowed to achieve the target rating), the lower the cutoff point (the SDR) and thus the lower the subordination required.

Previously the CDO default rate assumptions were the same as that of corporates. In E3, for CDO ratings above BBB, the new default rates are lower, while for BBB and below ratings, the new default rates are higher. Exhibit 91 shows 8-year default rates as an example.103

Exhibit 91: 8-Year CDO Default Rate in Evaluator 3 and Evaluator 2 50%

8-year CDO Default Rate in E3

45%

8-year CDO Default Rate in E2

40% Default Rate

35% 30% 25% 20% 15% 10% 5% 0% AAA

AA

A+

A-

BBB Rating

BB+

BB-

B


There are two forces working against each other here as the same CDO default matrix is used for two purposes: on one hand, a higher (lower) default rate used for the underlying CDO tranches results in higher (lower) default risk of the underlying CDO tranches in the collateral pool and thus raises the overall default risk of the collateral pool (and ultimately it results in higher (lower) subordination requirement); on the other hand, higher (lower) default rates used for the target CDO being rated also suggests a more generous standard – more defaults are allowed to achieve the target rating – and results in lower (higher) SDR and subordination. It seems that the first force outweighs the second, as suggested by the example we show next.

103


A detailed default matrix can be found in Appendix I.

86

31 March 2006

First example – a mezzanine SF CDO First we ran both E3 and E2 on a real mezzanine SF CDO issued in 2005. Exhibit 92 and Exhibit 93 show the rating and sector breakdown of this deal. The underlying portfolio of this deal is typical for recent SF CDOs. The weighted average rating is about BBB+/BBB and the vast majority of the collateral is invested in Resi B&C and Resi A.

Exhibit 92: Rating Breakdown (Sample MZ SF CDO) A 10% BBB+ 29%

Exhibit 93: Sector Breakdown (Sample MZ SF CDO)

A7%

ABS Commercial 1%

A+ 2%

AA 2% AA2%

ABS Consumer 4%

Aerospace & Defense 1%

CDOs 3%

CMBS (Large Loan, Single Borrower, and Single Property) 1% CMBS Diversified (Conduit and CTL) 5%

AAA 1% BB 1%

Manufactured Housing 2%

BB+ 3% RMBS B&C 64%

BBB21%

Source: Credit Suisse. S&P

BBB 22%

REITs and REOCs 6%

RMBS A 13%


We use these assets as inputs to run this deal through both E3 and E2. We compare SDR’s from both models in Exhibit 94 and, with the exception of AAA and AA+ ratings, E3 generates higher SDR’s for all other rating categories. The main reason for this is because of the presence of BBB- and below rated assets in the pool – about 25% in total – which is penalized by E3 as the default rates of ratings below BBB are higher in the new model. While the default rates of BBB+ and above ratings are lower and the pool does have more than 50% BBB+ and above rated assets, it seems that it is not enough to overcome the penalty given to the lower rated assets.104 “Rating Default Probability” (RDP) is determined by rating and maturity from the CDO default matrix. As we run the analysis to the auction call date of 8 years, the RDP’s are exactly the same as the numbers in Exhibit 91. Exhibit 96 shows the default rate distributions from both E3 and E2. It turns out that the default distribution from E3 has a fatter right tail. Translation: due to the higher default rates assumed for lower-rated assets in E3, the model estimates that the underlying portfolio will have a higher chance of experiencing high default rates.

104 In E2, S&P uses a set of stress factors for SDR. For example, a stress factor of 1.2 is applied to AAA rating to reach the final SDR. In E3, the stress factors have been removed.


87

31 March 2006

Exhibit 94: Comparison of SDR – Mezz. SF CDO Desired Rating AAA AA+ AA AAA+ A ABBB+ BBB BBBBB+ BB BB-

E3 Rating Default E2 Rating Default Probability SDR_E3 Probability 0.405% 18.04% 0.658% 0.584% 16.54% 0.835% 0.927% 14.64% 1.445% 1.182% 13.69% 1.650% 1.472% 12.84% 1.896% 1.774% 12.12% 2.204% 2.395% 10.96% 2.632% 3.413% 9.70% 3.492% 5.310% 8.20% 4.667% 9.891% 6.23% 7.360% 12.007% 5.67% 11.525% 16.810% 4.72% 15.419% 22.544% 3.95% 17.816%

SDR_E2 18.93% 16.77% 13.75% 12.84% 11.91% 10.99% 10.01% 8.74% 7.52% 5.92% 4.39% 3.57% 3.14%

SDR_E3/SDR_E2 Ratio 0.95 0.99 1.06 1.07 1.08 1.10 1.09 1.11 1.09 1.05 1.29 1.32 1.26


Exhibit 95: Comparison of SLR – Mezz. SF CDO Desired Rating

E3 Rating Default Probability

SLR_E3


SLR_E2

0.405% 0.584% 0.927% 1.182% 1.472% 1.774% 2.395% 3.413% 5.310% 9.891% 12.007% 16.810% 22.544%

13.33% 11.56% 10.27% 9.63% 8.47% 8.01% 7.26% 5.86% 4.97% 3.79% 3.14% 2.62% 2.19%

0.658% 0.835% 1.445% 1.650% 1.896% 2.204% 2.632% 3.492% 4.667% 7.360% 11.525% 15.419% 17.816%

13.85% 11.59% 9.55% 8.93% 7.73% 7.15% 6.52% 5.17% 4.45% 3.52% 2.36% 1.92% 1.69%

AAA AA+ AA AAA+ A ABBB+ BBB BBBBB+ BB BB-

SLR_E3/SLR_E2 SLR_E3 – Ratio SLR_E2 0.96 1.00 1.08 1.08 1.10 1.12 1.11 1.13 1.12 1.08 1.33 1.36 1.29

-0.52% -0.03% 0.72% 0.70% 0.74% 0.86% 0.74% 0.69% 0.52% 0.27% 0.78% 0.70% 0.50%


Exhibit 96: Default Rate Distribution in E3 and E2 45% 40%

P ro b a b ility o f D e fa ult R a te _ E 3 P ro b a b ility o f D e fa ult R a te _ E 2

35%

Probablity

30% 25% 20% 15% 10% 5% 0% 0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

22%

D e fa ult R a te



88

31 March 2006

Based on S&P’s methodology, cash flow analysis is required to verify that each rated tranche can withstand defaults up to its SDR. 105 Ultimately, the credit enhancement or subordination levels are determined by a Scenario Loss Rate (SLR). The SLR determines the subordination level such that the probability of loss of the underlying portfolio exceeding the subordination – i.e., the SLR – is no greater than the default probability of the target rating. This is consistent with S&P’s basic scheme of a rating – it reflects the probability of “first dollar loss”.106 To determine SLR, recovery assumptions need to be made.107 Exhibit 95 lists the SLR’s from both E3 and E2. Similar to the pattern of SDR’s in Exhibit 94, the SLR’s – the credit enhancement levels – are higher for most of the ratings except AAA and AA+ based on E3. For example, for BBB rating, the enhancement level will have to be raised by 52 bps if E3 is used.

Second example – a high grade SF CDO Because the new default rates of ABS securities rated above BBB are lower than those in E2, one would expect the subordination levels required by E3 for high grade SF CDOs to be lower than those required by E2. A sample run through a real high grade SF CDO issued in 2005 proves so.

Exhibit 97: Rating Breakdown

Exhibit 98: Sector Breakdown

Sample HG SF CDO

Sample HG SF CDO A 7%

ABS Commercial 3%

A5% A+ 2%

AAA 39%

CDOs 31%

AA 27%

RMBS B&C, HELs, HELOCs, and Tax Lien 53%

CMBS Diversified (Conduit and CTL) 1%

AA+ 9%

Source: Credit Suisse. S&P

RMBS A 8%

AA11%

Monoline/FER Guaranteed 4%


As shown in Exhibit 97 and Exhibit 98, this deal has a weighted average rating of AA+/AA with no collateral rated below A-. The portfolio is more than 60% invested in Resi B&C and Resi A combined and over 30% in CDOs.

105 A Breakeven Default Rate – the maximum default percentage the transaction can withstand without any loss to the rated tranche, determined based on cash flow analysis. For a tranche to be rated at the target rating, the SDR has to be lower than the Breakeven Rate. 106 Moody's ratings are determined based on expected loss. 107 Please refer to Appendix II for details.


89

31 March 2006

Exhibit 99: Comparison of SDR – High Grade SF CDO Desired Rating AAA AA+ AA AAA+ A ABBB+ BBB BBBBB+ BB BB-

E3 Rating Default Probability 0.405% 0.584% 0.927% 1.182% 1.472% 1.774% 2.395% 3.413% 5.310% 9.891% 12.007% 16.810% 22.544%

SDR_E3 5.00% 4.45% 3.79% 3.49% 3.21% 2.98% 2.61% 2.23% 1.80% 1.16% 1.01% 0.81% 0.46%

E2 Rating Default Probability 0.658% 0.835% 1.445% 1.650% 1.896% 2.204% 2.632% 3.492% 4.667% 7.360% 11.525% 15.419% 17.816%

SDR_E2 7.90% 6.94% 5.58% 5.16% 4.76% 4.36% 3.93% 3.35% 2.82% 2.16% 1.53% 1.18% 0.99%

SDR_E3/SDR_E2 Ratio 0.63 0.64 0.68 0.68 0.67 0.68 0.66 0.66 0.64 0.54 0.66 0.69 0.46


Exhibit 100: Comparison of SLR – High Grade SF CDO Desired Rating


SLR_E3


SLR_E2

0.405% 0.584% 0.927% 1.182% 1.472% 1.774% 2.395% 3.413% 5.310% 9.891% 12.007% 16.810% 22.544%

2.51% 1.96% 1.67% 1.53% 1.12% 1.04% 0.92% 0.66% 0.52% 0.36% 0.28% 0.21% 0.13%

0.658% 0.835% 1.445% 1.650% 1.896% 2.204% 2.632% 3.492% 4.667% 7.360% 11.525% 15.419% 17.816%

4.03% 3.08% 2.47% 2.29% 1.68% 1.54% 1.39% 1.00% 0.84% 0.64% 0.40% 0.31% 0.26%

AAA AA+ AA AAA+ A ABBB+ BBB BBBBB+ BB BB-

SLR_E3/SLR_E2 SLR_E3 – Ratio SLR_E2 0.62 0.63 0.68 0.67 0.67 0.68 0.66 0.66 0.62 0.56 0.70 0.68 0.50

-1.52% -1.13% -0.80% -0.76% -0.56% -0.50% -0.47% -0.34% -0.32% -0.28% -0.12% -0.10% -0.13%


Both the SDR and SLR are significantly lower across all ratings if E3 is used, as shown in Exhibit 99 and Exhibit 100. Take BBB SLR as an example: E3 requires only 2/3 of the SLR required in E2. Alternatively, in terms of subordination level required, it is 32 bps lower. For high grade deals with very high leverage, this kind of drop would be very significant.


90

31 March 2006

Impact on the secondary market Adopting a new version of Evaluator by S&P may have a significant impact on the secondary SF CDO market, both synthetic and cash flow deals. All things equal, high grade deals are more likely to be upgraded than mezzanine deals because of this change in the model, and vice versa for downgrades. For existing synthetic deals without excess spread, the agency has already put some deals on watch list and also indicated no additional rating actions are expected at this time. However, in the future, because of credit migration in the underlying portfolio, investors need to understand the change in E3 in order to better evaluate their CDO holdings. For example, if there is some credit deterioration to below BBB ratings in the pool, it will be even more likely for the deal to be downgraded than before (with E2). For cash flow deals and synthetic deals with excess spread, even though the agency is still finalizing the cash flow criteria and the ultimate impact of E3 remains uncertain, investors still need to be aware of the potential changes and take them into account in their evaluations. In terms of rating distribution, the new model encourages a more bullet-like portfolio versus a barbell portfolio for mezzanine SF CDOs. In other words, a portfolio of, say, all BBB-rated assets will be required to have lower subordination levels than a half BBB+/half BBB- portfolio, given the reasons we discussed earlier. This could have spread implications on the underlying collateral markets. Of course, this will be a self-correcting process, i.e., if the spreads of lower-rated assets widen to certain levels, their attractiveness may outweigh the required additional enhancement.

Final comments As mentioned previously, S&P is still finalizing the cash flow assumptions such as interest rate, amortization speed, etc. The final rating and subordination levels will be determined by both the outputs from the new CDO Evaluator and the cash flow analysis. For example, even though we found that the subordination levels of high grade SF CDOs based on E3 are lower than those from E2, we also expect that the new set of cash flow assumptions to be released later might mute the impact to some degree.


91

31 March 2006

Value Shifting to Mezzanine SF CDOs108 In the past two months or so, subordinate (Baa1-Baa3) home equity (HEL) bonds spreads have significantly widened. The widening started with the CDS/synthetic spreads on HEL bonds, and now cash spreads have followed. Baa2 cash spreads stand at 235 basis points, 100 bps wider than the level just 2 months ago, and Baa3 cash spreads have doubled to 350 bps (see Exhibit 101). With the collateral of recent mezzanine SF CDOs dominated by Baa2/Baa3-rated HELs, the spread widening has had significant impact on the CDO market. We have seen newissue mezzanine ABS CDO liability spreads widen out, especially at the BBB level. In a recent pricing, the BBB class was priced at L+400 bps. Given the recent re-pricing, we believe that value is starting to shift to mezzanine ABS CDOs. In this issue’s Insight, we share some of our thoughts and demonstrate reasons for our view.

Exhibit 101: HEL CDS Spreads vs. Cash Spreads December 9, 2005 Rating Baa1 Baa2 Baa3

Cash Spread

Synthetic Spread

170 235 350

160 230 340

2 Month Ago Basis Cash Spread -10 -5 -10

120 135 175

Synthetic Spread

Basis

115 130 200

-5 -5 25


Widening asset spread boosts equity IRR of Mezz. ABS CDOs Given the current spreads of HEL bonds (cash or synthetic) and the predominance of HEL collateral in recent ABS CDOs, it is likely to have collateral pools with a weighted average spread of around L+240 bps. 109 110 Even with the recent widening in mezz. ABS CDO liability spreads, the potential IRR for the equity tranche is still very attractive. We use a hypothetical but representative mezz. ABS CDO to show some numerical examples.

Exhibit 102: Capital Structure of a Hypothetical Mezzanine ABS CDO* Tranche A B C Equity

Balance

%

Rating

Coupon

OC Target

IC Target

400,000,000 50,000,000 27,500,000 22,500,000

80.0% 10.0% 5.5% 4.5%

Aaa Aa2 Baa2

L + 35 L + 65 L+ 400

103.5% 101.0%

115.0% 110.0%

* We also assume this deal has a reinvestment/non-call period of 3 years, and an auction call date of 8 years after closing. We also assume there is a turbo feature on the Baa2 tranche and the equity return is capped at 18% during the turbo period. Source: Credit Suisse

Exhibit 102 shows the capital structure of our sample deal. Note we increase the Baa2 tranche spread to 400 bps. By assuming a 0.5% constant annual default rate (CADR) and a 60% recovery rate, we calculate the IRR on the equity tranche to be 24.5%, significantly higher than 10%-15% baseline numbers mezzanine ABS CDOs issued during the better part of 2005.

108

This section was originally published in "The CDO Strategist", Issue #12, December 15, 2005. The weighted average rating factor (WARF) of HEL bonds in a Mezzanine ABS CDO is around 360-420, or Baa2/Baa3-rated. And HEL bonds could take 60-80% of the collateral, with the rest invested in Resi-A (10%), junior tranches of other CDOs (10%), and others such as CMBS or credit card receivables. 110 Note that a WAS of L+240 is possible for new deals initiating their ramp-up during the last few weeks. For deals already significantly ramped prior to the spread widening, a lower WAS is expected. 109


92

31 March 2006

But does this mean Mezz. ABS CDOs offer value? We think so Currently the baseline IRR expectation for CLO equity and high-grade SF CDOs falls into the 10-15% range. However, just because the potential IRR of mezz. SF CDOs under one particular set of assumptions is higher does not necessarily mean mezz. SF CDOs offer superior value versus CLOs and/or HG SF CDOs. One may argue that the spread widening in HEL is justified: the US housing market may slow down dramatically causing defaults and losses among HEL bonds, which may increase and eventually ripple though to mezz. SF CDOs. In other words, the 0.5% CADR we assumed is too low and the 24.5% IRR will not be achieved. There is certainly some merit to this argument. To check its validity, we approach this issue from a slightly different angle: instead of comparing spreads and IRRs, we calculate the implied level of risk the market is pricing in. To talk relative value, we need to find a common benchmark. Before the recent re-pricing in subordinate HEL bonds and mezzanine SF CDOs, the baseline equity IRRs of HY CLOs, HG SF CDOs and mezz. SF CDOs were all hovering around 10-15%. Equity investors have generally accepted these as IRR market target range. In a benign credit environment with tight spreads across most markets, equity investors seem to agree on this IRR range as an “equilibrium” level, where the risks they are taking are fairly compensated, and marginal investors, who can switch among these different CDO products, are indifferent when choosing which product to invest in terms of risk versus return trade-off. As the expected IRRs of CLO and HG SF CDO equity has not changed significantly, it is not un-reasonable to assume an ”equilibrium” IRR of 15%, i.e., at this IRR, equity investors will be indifferent to choosing among CLOs, HG SF CDOs and mezz. SF CDOs. Now let’s ask the following question: if 0.5% CADR is too low and an IRR around 25% cannot be achieved, what is the right CADR to use in order to achieve a 15% IRR, for mezz. SF CDOs? We use the same hypothetical deal and solve for the CADR that would result in an IRR of 15%.

Exhibit 103: Implied CADR and Cumulative Default Rate Recovery Rate 60% 60% 60% 60%

BBB CDO Spread

Equity IRR

Imp. CADR

Imp. 5-y Cum Default

Imp. 5-y Cum Loss

350 400 450 400

15% 15% 15% 10%

2.67% 2.60% 2.53% 3.22%

12.66% 12.34% 12.03% 15.10%

5.06% 4.94% 4.81% 6.04%


As shown in Exhibit 103, the CADR has to reach 2.6% for the equity IRR to drop to 15%. Let’s put this number into historical perspective: based on Moody’s Impairment Rate study, the 5-year cumulative impairment rate of HEL is about 7%. However, if we calculate the 5year cumulative default rate of 2.6% CADR using the same methodology that Moody’s uses, the cumulative default rate would be 12.34%, much higher than the historical 7% cumulative impairment rate. 111 Note that Moody’s 5-year cumulative impairment rate of HEL is already a rather conservative number due to the following reasons:

•

The Impairment Rate is, in general, a broader concept than default rate.

111 The 5-year cumulative number is calculated as one minus the 5-year survival probability, or 1-(1CADR)^5.


93

31 March 2006

•

Moody’s 5-year cumulative rate is derived by calculating the marginal rates first. However, when calculating the 4th or 5th year marginal rates, recent vintages (after 2001) of HEL are not included. The HEL sector has evolved considerably since 2001: it has gone through the pre-1996 nascent stage, the initial growth from 1996 to 1998, the consolidation period from 1999 to 2001, and dramatic expansion since then. Many impairments due to industry-wide issues before 2001 are reflected in the 4th and 5th year marginal rates. As shown in Exhibit 104, there is a huge jump from the 3rd year marginal rate (0.46%) to the 4th and 5th year marginal rates (2.66% and 3.87%, respectively), and we believe this is due to the sampling issue just discussed. More important, we believe the 5-year cumulative impairment rate using these marginal rates over-estimates the actual experience.

Exhibit 104: Marginal Impairment Rates by Years Since Origination 5 .0 %

Marginal Impairment Rate

4 .5 %

4 .5 3 % Ba a HEL

Ba a R MBS

3 .8 7 %

4 .0 % 3 .5 % 3 .0 %

2 .6 6 %

2 .5 %

1 .9 4 %

2 .0 %

1 .5 6 %

1 .5 % 1 .0 % 0 .5 % 0 .0 %

0 .6 5 % 0 .0 0 % 0 .0 8 % 1 -Y e a r

0 .1 5 % 2 -Ye a r

0 .4 6 %

3 -Ye a r

4 -Y e a r

5 -Ye a r

Y e a r s s in c e o r ig in a tio n Source: Moody’s, Credit Suisse

The fact that Moody’s 5-year Impairment Rate is over-estimated and our implied 5-year cumulative default rate is even higher than the Moody’s number leads us to believe that the market would over-estimate the default risk if assuming an equity IRR of only 15%. In other words, we believe the actual default rate will be lower and the equity can achieve a higher IRR than 15%. Thus, we find relative value in equity tranches of recent mezzanine SF CDOs (priced in the past 2 weeks or so) and those still in the pipeline if market conditions stay unchanged. Some might contend that the equity IRR is high because the debt tranches are priced too rich, i.e., the spread is too low. We increased the BBB tranche spread from 400 bps to 450 bps and re-ran the numbers. Both implied CADR and cumulative default rate dropped slightly (see Exhibit 103) and the conclusion stands. We can certainly bump up the spread further, but note that historically the highest BBB mezz. SF CDO tranche spread was 450 bps during early 2003 and the conclusion still won’t change much even if spreads are raised. As a matter of fact, we find the BBB tranche attractive at L+400 to 450 level, even more so if there is a turbo feature on the BBB tranche. What if the spreads of senior tranches of SF CDOs jump as well? Given that the HEL spreads have widened and stayed wide, we do believe the senior spreads will eventually widen as well. We have already seen a deal price in the market with senior AAA at L+32 bps, 5-6 bps wider than recent historical lows. But notice that in the sample deal we used, we already consider the spread widening of senior tranches by applying an aggregate (senior and junior) AAA spread of 35 bps. Even if the spread widens further, say AAA spread doubles to 70 bps, we can still achieve an equity IRR above 20% at 0.5% CADR. If this does materialize, we would call for value in senior tranches given that most other AAA tranches are priced at the high 20’s to low 30’s, all else being equal.


94

31 March 2006

There is something ELSE about mezz. SF CDOs In addition to the points just discussed, we like new mezz. SF CDOs also for the following reasons:

•

Because of the spread widening in subordinate HEL bonds, there is more leeway now for SF CDO managers to find undervalued bonds and pick the right credits for their deals.

•

The more active synthetic market on subordinate HEL bonds and the attractive synthetic spreads also help managers find value.

•

The widening collateral spreads also allow mezz. SF CDOs to invest in just floating bonds, instead of using fixed bonds to boost equity returns (as some HG SF CDOs do) but also introduce other risks such as convexity risk.

Final Thoughts The fundamental reason we find value in new mezz. SF CDOs is because of the spread widening in subordinate HEL bonds. The wider spreads allow the CDO to take advantage of the arbitrage between asset and liability spreads and brings an attractive return, without sacrificing credit quality or increasing leverage. The widening new issue mezz. SF CDO spreads may also have an impact on secondary bonds. If wider new issue spreads are used to price seasoned bonds which cause those bonds to trade at a discount, we might find value in the secondary market as well. Depending largely on how the US housing market pans out next year, HEL spreads may widen and be more volatile, which will bring value and new opportunities to future mezzanine SF CDOs. So stay tuned.


95

31 March 2006

Impact of HEQ Available Funds Caps on ABS CDO Tranches112 Introduction Since the mid- to late 1990s, hybrid ARM loans have been growing in popularity among mortgage loan borrowers, notably in the subprime HEQ space. The securitization rate of this kind of product has also jumped dramatically since 2001 and taken a lot of market share from other mortgage products. The two most popular structures are so-called “2/28” and “3/27” ARMs. In a “2/28” ARM, the loan rate is fixed in the first 2 years and then resets to six-month LIBOR plus a margin. (Because these are 30-year loans, the name stems from the fact that the loan is fixed for 2 years and then floats for the remaining 28). However, the rate after reset is subject to an initial cap, which limits the rate reset (usually set at 3%), periodic cap rates (usually 1%-1.5% per reset), and a maximum lifetime cap rate (usually about 600 bps higher than the initial loan rate). Hybrid ARMs provide a rate advantage to borrowers during the fixed rate period but also expose the borrowers to the risk of a rate increase at the expiration of the fixed period. Generally, there is a significant increase in prepayments at the first rate reset, as many borrowers who can refinance into a new loan do so; this is driven by the overall rate environment, credit improvement of the borrower, and/or levels of home price appreciation. Subordinate BBBrated HEQ floaters become a large share of CDO collateral

ABS CDOs have evolved significantly over the last several years as a result of changing market conditions, investor desires, and improving structuring technology. The differences between latter-day ABS CDOs and ones originated at the asset class’s inception in 19992000 are vast, and we’ve argued that today’s deals represent a “second-generation” ABS/SF CDO113. Early ABS CDOs were created as a vehicle to gain diversified exposure to many and various ABS sectors, including auto loans, credit cards, home equities, manufacturing housing, but also esoteric assets such as aircraft securitization, franchise loan ABS, and mutual fund fee deals. However, given the poor performance of some of these sectors, recent ABS CDO deals have been shifting more towards residential and commercial mortgage-backed securities. Home equity (sometimes called ”residential B&C mortgages”) has become a much larger share of CDO collateral since 2002, concentrated in single-A and triple-B paper. In general, we think that this is a good thing and that the credit performance of mortgagerelated structured finance paper has been strong and is likely to remain so (again, see our January piece and other previously referenced home equity research for more on this topic). Exhibit 105 shows the typical collateral mix for early-vintage ABS CDOs. HEL and RMBS B&C only accounted for less than 10% of the pool. And Exhibit 106 shows the collateral of ABS CDO deals of newer vintages. HEL and RMBS B&C now take a share of 37%.

112

This section was originally written by Neil McPherson, David Yan, Rod Dubinsky and Helen Remeza, August, 2004. 113 Please see CSFB's ABS research report "The Compelling Case for SF CDOs" (January 27, 2004) Chapter 1. Structured Finance CDOs

96

31 March 2006

Exhibit 105: Collateral of ABS CDO – Early Vintage Other 1.5%

REIT 2.9%

RMBS 4.2%

SBL 1.7%

Tax Liens 2.2%

Auto 2.1%

CBO 11.8%

Mutual Fund Fees 2.7%

CC 6.4%

MH 11.9%

HEL/RMBS B&C 9.0% CMBS 25.2% Future Flow 0.5%

Franchise 1.6%

ETC 5.9%

Equip 2.0%

Corp 8.3%


Exhibit 106: Collateral of ABS CDO Deals – Newer Vintage*

Other 0.8%

REIT 6.5%

RMBS 10.7%

Structured Settlement SBL Auto 1.0% 2.0% 2.1%

CBO 7.6%

Mutual Fund Fees 0.6%

CC 3.4% CMBS 15.8%

Corp 4.0%

MH 6.7% HEL/RMBS B&C 37.1%

ETC 1.2%

Equip 0.6%

* As of August, 2004 Source: Credit Suisse

In the last two years, we’ve seen record supply of HEQ (and triple-B HEQ bonds) matched by equally strong demand from CDO managers in their ramp-up stage. Given the current situation in which the bid for subordinate floaters from CDO managers is exceptionally strong, it is important to understand the impact of AFC risk in subordinate HEQ floaters on ABS CDO tranches. Should interest rates rise significantly in the next two to three years, there could be a considerable impact on the cash flow and return of CDOs backed by these bonds as a result of cap risk. As stated earlier, available funds cap (AFC) risk refers to the situation in which the interest rate on the loans backing a subprime home equity floater is capped so that the home equity bond receives less than the rate promised. Factors influencing the AFC risk include the following: • • • •


Coupon during initial fixed rate term. The periodic and lifetime rate caps of the loan. The margin of the home equity floating bonds (i.e., the spread over one-month LIBOR). Increasing prevalence of mixed pools with both hybrids and fixed rate collateral.

97

31 March 2006

• • • • The mix of fixed and floating loans backing home equity floaters is one of the main determinants of AFC risk

Deep mortgage-insurance (MI) fees netted from the loan WAC114. Structural credit enhancements, such as overcollateralization (OC). Hedging vehicles, such as cap agreements. Presence of IO (interest only) tranche in the deal.

Given high demand for floating rate assets and the unprecedented sharp drop in interest rates (LIBOR) in recent years, subprime issuers can enhance the economics of securitizations by issuing LIBOR-based floating bonds backed by a collateral pool with some percentage of fixed rate loans – commonly 20%-30% of the pool. But this exposes the investors of these bonds to more AFC risk, because the fixed loans are fixed for life, and in addition, prepayment speed differentials that are different from pricing assumptions can cause the floating/fixed mix to change significantly over time. The AFC strike rate for a HEQ pool mixed with fixed rate and ARM loans is dependent on the percentage and WAC of fixed rate loans in the deal as well as the relative prepayment differential between the fixed rate and the ARM loans over the life of the deal. 115 Structural enhancements in the home equity deals, such as overcollateralization (OC), also affect the amount of funds available for coupon payments. The higher the existing OC level, the more funds it will generate to make coupon payments if shortfalls arise. We should note that Moody’s and S&P recently revised their interest rate stresses used in rating HEQ deals; the net effect is to increase OC requirements in newer HEQ deals.116 In most deals, the interest shortfall due to AFC can be carried forward and be paid by excess cash flow. However, given that AFC shortfall payments are usually paid at the bottom of the waterfall, the value of their offsetting the AFC risk should be significantly discounted. The increase in OC will improve the likelihood of paying back the basis risk shortfall. In many deals, the trust also purchases a cap contract to mitigate the cap risk. However, the cap contract usually covers only a limited time period, and the strike rate is often set far out of the money.

While the AFC risk is applicable to all tranches, its impact is greater for more subordinated tranches

While the AFC risk is applicable to all home equity ABS tranches, its impact is greater for more subordinated tranches. First, the more subordinated tranches usually have longer average lives. Thus, it is more likely to breach the strike rate, which is the same logic as a longer-term option having a higher value, all else equal. Second, the spread or margin on the subordinated bonds is higher than the spread on senior bonds, making it more likely to hit the cap rate. To simplify our analysis and concentrate on the differences in the impact of HEQ BBB tranches on CDOs and their inherent AFC risk, we use only one bond as the entire collateral pool (in our first three examples). This, to some extent, thus represents “worstcase scenarios,” because in typical ABS CDOs, a portion of the collateral pool perhaps equal in size to the HEQ portion will be in completely uncapped floaters. In addition, as we’ll see later, the presence of a multitude of HEQ tranches in a given deal can act to reduce the AFC risk of any one HEQ bond to the ABS CDO.

114

Weighted Average Coupon. Usually defined as the net WAC (initial WAC minus servicing fee and MI premium), minus bond spread/margin, plus payment from cap contract 116 See CSFB's Market TABS dated August 2, 2004 for a description of the S&P revision. 115


98

31 March 2006

Sample ABS CDO Deal We use a hypothetical ABS CDO structure to run our analysis. Exhibit 107 shows the detailed capital structure of the CDO and the tranche spreads.

Exhibit 107: Sample ABS CDO Deal Structure Tranche

Percentage

Floating/Fixed

Rating

Spread

78% 14% 4% 4%

Floating Floating Floating Residual

AAA AA BBB N/A

L+38 L+100 L+315 N/A

A B C Equity Source: Credit Suisse

We also make other assumptions as listed below in Exhibit 108:

Exhibit 108: Assumptions Coupon Payment:

Quarterly

Rapid/Turbo Structure:

1. All principal amortization will be used to pay down Class A notes and Class B notes pro rata. However, in case any IC or OC test is breached, A and B notes will revert to sequential for the rest of the transaction. 2. The Equity tranche is capped at an annual return of 15% for the life of the transaction or until the Class C is paid off. Excess cash flows will be used to pay down Class C notes.

Class A/B Overcollateralization Test Class C Overcollateralization Test Class A/B Interest Coverage Test Class C Interest Coverage Test Fixed-rate Voluntary Prepayment Curve ARM Voluntary Prepayment Curve

Fixed-rate Default (CDR) Curve* ARM Default (CDR) Curve* Recovery in Default*

105% 102% 115% 110% Ramp up to 20 CPR from month 1 to 12 and remain constant at 20 CPR thereafter Ramp up to 35 CPR from month 1 to 14, stay constant at 35 CPR through month 23, jump to 70 CPR in month 24, and then ramp down to 35 until month 31 and remain at 35 CPR thereafter Zero for the first 6 months, ramps up to 3.25 CDR at Month 30, and stay at 3.25 CDR thereafter Zero for the first 6 months, ramps up to 5 CDR at Month 30, and stay at 5 CDR thereafter Immediate recovery at 60%

Source: Credit Suisse * Only used in some of the examples, as indicated later

Turbo structure can shorten the average life of the Triple-B CDO tranche and build up its OC cushion

In essence, the Turbo structure117 in the CDO utilizes a portion of excess interest (after a capped equity return) to amortize a Triple-B CDO tranche, thereby shortening the average life of the Triple-B and also allowing its OC cushion to build up. The overall CDO structure is enhanced by the Turbo as relatively expensive subordination is replaced by cheaper OC. The pro rata paydown schedule of Class A and B notes acts to decrease the average life of the Class B notes and build OC for both classes. However, if any coverage test is breached, the payment schedule becomes sequential.

117 Please see CSFB's ABS research report, "Relative Value of Turbo Triple-Bs in ABS CDOs (November 26, 2002)


99

31 March 2006

To simplify the analysis, we use one BBB home equity floating bond as the collateral and run its cash flows through the CDO model

As we stated earlier, we assume the underlying collateral of the CDO is composed of only one floating rate home equity BBB bond and use the principal and interest cash flows (generated by Intex) to run through our CDO cash flow model. Because both the asset and the liabilities are floating, we ignore any hedging issues for the CDO. There is a mismatch between the index rates (we use one-month forward LIBOR on the home equity bond and three-month forward LIBOR on the CDO notes). We will shock them by the same magnitude, and therefore, we will not take this into consideration. We list the details of the three HEQ bonds issued in 2004 that we used for our analysis in Exhibit 109. We ran each one of them separately through our cash flow model based on the aforementioned CDO structure. (Again, our CDO deal is backed by only one bond as collateral.)

Exhibit 109: Details of Sample Bonds Moody's Rating Original Balance Fixed Percentage 2/28 ARM Percentage (as of all ARM loans) Initial Aggregate WAC (1) Fixed-Rate WAC WA Gross Margin WA Intial Rate Cap WA Periodic Rate Cap Bond Spread (over LIBOR) (2) Servicing Fee (3) Strike Rate during Fixed-rate Period (1)-(2)-(3) MI Percentage Initial OC Level Interest Cap Hedge?

Bond A

Bond B

Bond C

Baa2 7,000,000 18.9%

Baa2 11,529,000 30.1%

Baa2 5,609,000 30.45%

72%

95%

70%

7.15% 7.42% 6.59% 3.00% 1.17% 240 0.5%

7.23% 7.64% 6.89% 3.00% 1.50% 195 0.5%

7.99% 7.95% 7.75% 3.00% 1.00% 200 0.5%

4.25%

4.82%

5.49%

2.7% 1.65% Yes 3-year Term, low strike*

0% 2.25% No

49.67% 0.5% Yes 3-year Term, high strike*

Source: Credit Suisse, Intex *Detail see later

At first glance, it seems that Bond A has the highest AFC risk, Bond B second, and Bond C the last. During the fixed rate period (say, 2 years for 2/28 ARMs), it is easy to calculate the strike rate. Take Bond A as an example. If we subtract just the bond coupon (240 bps) and servicing fee (0.5%) from initial WAC (7.15%), we get the strike rate at 4.25%. However, for Bond B and Bond C, it is higher: at 4.82% and 5.49%, respectively. But, after the initial fixed period, the strike rate also depends on the mix of ARM and fixed rate, cap contract (hedging vehicle in the HEQ deal), and periodic cap rate and lifetime cap rate of loans, among other things. Furthermore, the usage of MI insurance will also lower the strike rate (as MI premium is paid from WAC). We will see that the conclusion is actually precisely the opposite: Bond A has the lowest AFC risk, Bond B second, and Bond C the highest.


100

31 March 2006

Impact on CDO Deal Backed by Bond A We first assume zero CDR and that the bond will pass its delinquency trigger as well118. In our base case, we use the forward curves and the prepayment curves aforementioned. Because there is not much AFC shortfall by shocking the forward curve by 100 or 200 basis points (bps), we shock the curves by 300, 400, and 500 bps, respectively,119 and reduce the prepayment speed on only the fixed rate loans by 25%, as we believe when rates rise, prepayments will slow and the fixed rate loans will be impacted to a relatively larger degree than the ARMs. Note shocking the forward curves in this manner is fairly extreme; +300 bps implies that three-month LIBOR, for example, rises immediately to 5% and to about 7% over two years. Exhibit 110 shows the base three-month forward curve we used, as well as the curve after a 500-bps shock.

Exhibit 110: Forward Curves 14% 12% 10% 8% 6% 4% 2% 0% 0

6

12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102 108 114 120 126 Month Base 3-Month Forward Curve

Shocked by 500 bps


Exhibit 111 shows the result of the sample CDO deal backed by Bond A. For the CDO tranches, in the base case, both Tranche AAA and Tranche AA share the same WAL because they are paid pro rata. Tranche BBB has a very short WAL of 3.81 as a result of the Turbo feature. Notice all the IRR and DM120 numbers are based on a bond priced at par.

118 We could assign a delinquency level (such as 30%), but it will not change the conclusion of this report much. Failing the delinquency trigger only changes the step-down date and the cash flows after the target step-down date (usually 3 years after origination). Further, failing a delinquency trigger does not necessarily cause loss. 119 All the curves - the six-month LIBOR on the HEL loans, the one-month LIBOR on the floating bond, and the three-month LIBOR on the CDO liability side - are shocked by the same magnitude, such as 300 bps. We start from 300 bps because there is not much shortfall if only shocked by 100 or 200 bps. 120 Discount margin, calculated based on forward curve.


101

31 March 2006

Exhibit 111: Result of CDO Deal Backed by Bond A – Zero CDR and with Turbo Home Equity Bond Base Case, Forward Curve FWD+300, Slow Fixed VCPR by 25% FWD+400, Slow Fixed VCPR by 25% FWD+500, Slow Fixed VCPR by 25%

Tranche AAA

Tranche AA

Tranche BBB

Equity

WAL

WAL

IRR

DM

WAL

IRR

DM

WAL

IRR

DM

IRR

4.23

4.14

4.49%

0.38%

4.14

5.11%

1.00%

3.81

7.37%

3.15%

19.18%

4.52

3.86

7.16%

0.38%

7.34

8.63%

1.00%

2.12

9.36%

3.15%

19.30%

4.54

3.86

8.07%

0.38%

7.33

9.57%

1.00%

2.13

10.32%

3.15%

18.00%

4.62

3.96

9.03%

0.38%

7.30

10.50%

1.00%

2.72

11.55%

3.15%

14.08%


Low percentage of fixed rate collateral and low-strike cap contract make the AFC shortfalls of Bond A literally zero under all stressed scenarios used

In the first stressed case (+300), there is already a coupon shortfall on the HEQ tranche starting from the second month. However, for this bond, fortunately, all the shortfalls in this scenario are paid back throughout the entire life of the HEQ bond. This is the case for the second stressed scenario (+400) as well. There are three main reasons for the low AFC risk: 1.

Relatively low percentage of fixed rate loans (19% initially).

2.

A cap contract (three-year term) with high initial notional and low strike rate, which makes up most of the AFC shortfall. The cap is in-the-money early on even in the 300-bps stress scenario.

3.

Excess spread, which also covers the rest of the shortfall.

So, when shortfalls can all get paid back (which is equivalent to no shortfalls)121, it turns out that increasing the interest rate raises the coupon rate on the HEL bond and thus generates more excess flows to the CDO. As a result, the BBB tranche gets paid more in interest and paid off faster, thanks to the Turbo feature, as shown by its short WAL and high IRR numbers. However, in the last stressed scenario (+500), after about five years the shortfalls are too high to be paid back (remember there are shortfalls in the more senior tranches of the HEQ deal and they need to be paid down earlier). Thanks to the Turbo feature, most of the BBB tranche has already been paid down, the WAL only extended slightly from 2.13 to 2.72. Only the equity tranche got hurt as its IRR dropped to 14%. Overall, in all scenarios, the DM always holds at the original floating spread for each tranche. Note that in the stressed scenarios, the WAL of Tranche AAA is much shorter than the WAL of Tranche AA. This is because the IC test failed once, so they switched to sequential pay-down. Some people might argue that as there is default or credit loss, the excess cash flow will be reduced so that the shortfall will not be paid back. We will assume certain non-zero CDR curves in our next example. What if we took away the Turbo feature? We would expect the WAL of BBB to increase significantly (even in the base case) because now it will be paid off after AAA and AA. This is exactly the case as shown in Exhibit 112, where we compare only the BBB and equity tranches with and without Turbo.

121


In Bond A's case, all the shortfalls are actually paid back in the same period as the shortfall occurs.

102

31 March 2006

Exhibit 112: Result of CDO Deal Backed by Bond A – Zero CDR BBB Without Turbo WAL IRR 7.09 7.88%

Base Case, Forward Curve FWD+300, Slow Fixed VCPR by 25% FWD+400, Slow Fixed VCPR by 25% FWD+500, Slow Fixed VCPR by 25%

DM 3.15%

With Turbo WAL IRR 3.81 7.37%

DM 3.15%

Equity Without Turbo With Turbo IRR IRR 23.11% 19.18%

7.88

10.46%

3.15%

2.12

9.36%

3.15%

26.36%

19.30%

7.89

11.39%

2.75%

2.13

10.32%

3.15%

24.13%

18.00%

7.94

10.92%

1.14%

2.72

11.55%

3.15%

15.82%

14.08%


A more important observation is that the WAL of the CDO BBB in the stressed scenarios is now longer than the WAL in the base case when the Turbo feature is absent (about 0.8 years longer). When the HEQ prepayment is slower, there is less principal cash flow; thus, the balances of AAA and AA tranche are paid down more slowly. With the Turbo removed, the CDO’s BBB tranche is pushed far back in the line to receive cash flows. In addition, the DM on the BBB tranche is reduced when Turbo is removed. On the flip side, the equity tranche is better off (higher returns). Usually, in real CDO deals, the difference in WAL between Turbo and no-Turbo deals is about three years. The reasons that the difference here is so dramatic (in the +300-bps case, it is about 5.6 years) are as follows: 1.

We use only one bond as collateral, which makes it extremely sensitive to the structural assumptions we use. In reality, there will be not only more home equity bonds but also other asset types, such as credit card receivables, auto deals, CMBS, etc.

2.

The Turbo BBB accounts for a relatively small share of the whole CDO deal (only 4%), which makes it even more sensitive – i.e., it does not take much cash flow to pay it down if funds are available.

3.

In our deal, there is also no reinvestment period, which in a real deal acts to extend the average life of a Turbo BBB tranche; non-Turbo BBB tranches are rarely longer than ten years even with a revolving period.

Overall, the ABS CDO deal backed by Bond A is not exposed to significant AFC risk. This is again due to the following three factors: a relatively low percentage of fixed loans, the absence of MI coverage, and a cap contract with high notional and low strike rate. As a result, the high margin on the bond can be fully enjoyed by investors.

Impact on CDO Deal Backed by Bond B Bond B has more fixed rate collateral and does not have cap contract in the deal

We make the same assumptions regarding Bond B. The biggest differences between Bond A and B are that B has a larger percentage of fixed rate loans (30%) and that it does not have a cap contract in the deal. As ARMs typically pay down faster than fixed rate loans and the AFC strike rate migrates towards the coupon on the fixed rate loans, this is especially problematic for bond B, because there is no cap contract present. Bonds with a higher percentage of fixed rate loans have more AFC risk than those with lower percentage of fixed rate loans, everything else equal. Exhibit 113 shows the results of the CDO deal backed by Bond B. Notice all the IRR and DM numbers are again based on a bond price at par.


103

31 March 2006

Exhibit 113: Result of CDO Deal Backed by Bond B – Zero CDR and with Turbo HEL Bond Base Case, Forward Curve FWD+300, Slow Fixed VCPR by 25% FWD+400, Slow Fixed VCPR by 25% FWD+500, Slow Fixed VCPR by 25%

Tranche AAA

Tranche AA

Tranche BBB

Equity

WAL

WAL

IRR

DM

WAL

IRR

DM

WAL

IRR

DM

IRR

4.52

4.28

4.56%

0.38%

4.28

5.17%

1.00%

7.26

8.00%

3.15%

14.24%

5.05

4.72

7.48%

0.38%

4.72

8.09%

1.00%

5.31

10.59%

3.15%

15.92%

5.05

3.98

8.14%

0.38%

8.71

9.78%

1.00%

2.31

10.36%

3.15%

15.29%

5.05

4.12

9.11%

0.38%

9.28

10.78%

1.00%

9.55

3.82%

N/A*

N/A*

Source: Credit Suisse, Intex *N/A means a large negative number

The first difference we notice is that even in the base case, the BBB tranche backed by Bond B has a longer WAL than that backed by Bond A (7.26 vs. 3.81). This has to do with another difference between Bond A and B – A has a much higher margin than B (240 versus 195, a 45-bps difference). When the AFC is not in effect, higher margin means more interest cash flow and excess flow to the CDO, especially the BBB tranche. The Turbo feature just makes the difference more dramatic. When there is not enough excess flow, the CDO BBB could be completely shut out from any payment. In the case of Bond B, there is a period of a little over four years during which it does not receive any principal. It gets paid off after the AAA and AA tranches are paid off. Remember that before step-down, the bond does not receive any principal, so the only thing that can be used to pay the BBB tranche is the interest cash flow in excess of the equity cap (15%). In both the first (+300 bps) and second (+400 bps) stressed scenarios, the WAL of the CDO tranche BBB shortens significantly. As we take a closer look at the AFC shortfalls and whether and when they get paid back, here is what we find: In the first stressed (+300 bps) scenario, all the AFC shortfalls are paid back in the first 86 months, and only twice is the payback made with a 1-month lag. In the second stressed (+400 bps) scenario, although the lag could be up to 12 months, all the shortfalls are paid off by the first 82 months. Consequently, as we discussed earlier, when shortfalls can be paid back (such as the +300 and +400 cases here), there is actually more excess flow to the CDO, and with Turbo, the BBB is paid off faster. In addition, all the IRR and DM numbers hold up well. However, it is a totally different case when the AFC shortfall cannot be paid back. In the third stressed scenario, where the forward curve is shocked by (an unrealistic) 500 bps, the shortfalls are too high to be paid back – as a matter of fact, no shortfalls are ever paid back in this scenario. Remember that the AFC shortfall can only be paid back at the bottom of the waterfall and from senior tranche to junior tranche. In this case, there is nothing left to pay the shortfalls on the Triple-B bond (raising interest rates also increases the AFC shortfall for more senior bonds). As a result, the BBB tranche is extended to a WAL of 9.55 and has a much lower IRR of 3.82%. DM also turns to a large negative number. A CDO deal backed by Bond B has greater AFC risk than the one backed by Bond A

Obviously, Bond B is worse than Bond A in terms of AFC risk protection. Remember that when the CDO is backed by Bond A, the impact of AFC on BBB is still very limited when interest rates are shocked by 500 bps! (Both the IRR and DM hold well.) The main factors hurting Bond B include a high percentage of fixed rate loans and lack of a hedging vehicle, such as a cap contract. It is even worse for the equity tranche. When the rate is shocked by 500 bps, the equity tranche gets almost nothing. Any cash flows that could have gone to the equity are diverted to make up any interest shortfall on the more senior tranches.


104

31 March 2006

AFC shortfall could cause the IC test to fail and thus change the cash flow of the whole capital structure

Another interesting observation is that the WAL of AAA and AA tranches are no longer the same in the second stressed (+400-bps) scenario. Based on our set-up in this article, the OC test in the CDO never fails, but the IC test could fail122. As the IC test fails, the AAA and AA are paid off sequentially rather than pro rata; thus, AAA’s WAL shortens while AA’s lengthens. Exhibit 114 shows the IC ratio for AA tranche backed by Bond B in the first 24 periods (quarters). It is clear that the IC test fails early in Scenario 3 and 4. The spike in Scenario 3 around the eighth period is caused by a large payback in the AFC shortfall.

Exhibit 114: IC Ratio of AA Tranche Backed by Bond B 250%

200%

Pass

Ratio

150%

AA IC Trigger: 115% 100%

Fail 50%

0% 1

2

3

4

5

6

7

AA IC_Base Case

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Period AA IC_+300 bps

AA IC_+400 bps

AA IC_+500 bps


We also check the results without the Turbo feature, as shown in Exhibit 115. The conclusions are very similar to those in the case of Bond A. One difference is that, as in the case with Turbo, the IRR in the 500-bps-shock scenario is much worse than that of Bond A and the DM turns negative. Another interesting observation is that even in the +400 bps scenario, the DM drops to 1.39% without Turbo. Turbo feature benefits the BBB investors significantly

There are two benefits of the Turbo structure for BBB investors here:

122


1.

The performance is a little bit better with Turbo in the +500 scenario: shorter WAL and higher IRR and DM.

2.

Without serious AFC shortfall (+400 scenarios), a Turbo structure will significantly improve the performance: much shorter WAL and higher DM.

Normally, the OC test will be triggered before the IC test is triggered.

105

31 March 2006

Exhibit 115: Result of CDO Deal Backed by Bond B – Zero CDR BBB

Equity

Without Turbo Base Case, Forward Curve FWD+300, Slow Fixed VCPR by 25% FWD+400, Slow Fixed VCPR by 25% FWD+500, Slow Fixed VCPR by 25%

With Turbo

Without Turbo

With Turbo

WAL

IRR

DM

WAL

IRR

DM

IRR

IRR

8.56

8.11%

3.15%

7.26

8.00%

3.15%

15.02%

14.24%

10.11

11.12%

3.15%

5.31

10.59%

3.15%

18.31%

15.92%

10.11

10.40%

1.39%

2.31

10.36%

3.15%

17.75%

15.29%

10.49

2.52%

N/A*

9.55

3.82%

N/A*

N/A*

N/A*

Source: Credit Suisse, Intex * N/A means a large negative number

Higher default/loss will decrease excess spread and thus increase AFC shortfall

Now let us apply our CDR curve, as shown in Exhibit 108, to our analysis. Increasing CDR will increase loss and eventually cut into OC. It could postpone the step-down date (if the HEQ deal’s OC level does not meet the target) and thus change cash flows to the HEQ bond and the CDO. Or, it could exhaust the entire OC cushion and cause principal loss to the most junior HEQ tranche first and continue to work from the bottom up. Higher CDR and credit loss will lower the excess spread available (by reducing the performing balance) for making up any AFC shortfall, and thus, more shortfall will accumulate. So, a higher default rate could have an effect on the AFC shortfall. Exhibit 116 shows the results with Turbo. Comparing the numbers in Exhibit 116 with those in Exhibit 113, we have the following observations: 1.

Overall, the results for AAA, AA and BBB tranches are very similar with and without CDR. CDR curves normally start from very low levels and then ramp up to a certain level around 30-36 months out and then level off. A CDR curve with this kind of profile will generate moderate loss early on and thus has minimum impact on the short AAA, AA and BBB tranche. However, under an extremely stressed scenario, such as forward curve plus 500 bps, the shortfall is so high that there is not much excess spread left to cover the loss. Eventually, the OC drops too low and the principal payback on the Triple-B CDO bond is further delayed; thus, the WAL of the BBB tranche jumps from 9.55 to 13.82.

2.

In the stressed scenarios, the return on the equity tranche turns still lower. With Turbo, the cash flow to the equity tranche tends to be back-loaded. As discussed above, a higher default rate will increase the AFC shortfall and decrease cash flows to the equity tranche.

Our CDR curves result in a lifetime cumulative loss of around 4.2% for fixed-rate and 2.5% for ARMs in the base case, given our prepayment and recovery assumptions123. While these CDR curves are relatively “light,” we should note that our interest rate stresses are so “heavy” that the probability for them to happen is extremely slim; in other words, excess spread is squeezed so much given these interest rate stresses that higher CDRs cannot be sustained.

123 Although our assumed CDR curve is higher for ARM than for fixed rate, the cumulative loss rate is higher for fixed rate since the prepayment speed of fixed rate is slower.


106

31 March 2006

Exhibit 116: Result of CDO Deal Backed by Bond B – With CDR Curve and with Turbo HEL Bond

Tranche AAA

WAL WAL Base Case, Forward Curve FWD+300, Slow Fixed VCPR by 25% FWD+400, Slow Fixed VCPR by 25% FWD+500, Slow Fixed VCPR by 25%

Tranche AA

Tranche BBB

Equity

IRR

DM

WAL

IRR

DM

WAL

IRR

DM

IRR

4.21

4.02

4.46%

0.38%

4.02

5.08%

1.00%

6.65

7.89%

3.15%

14.36%

5.02

4.37

7.37%

0.38%

4.37

7.98%

1.00%

5.17

10.56%

3.15%

13.56%

5.02

3.70

8.02%

0.38%

7.65

9.62%

1.00%

3.51

11.01%

3.15%

8.50%

5.02

3.84

9.00%

0.38%

8.28

10.65%

1.00%

13.82

5.87%

N/A*

N/A*

*N/A means a large negative number Source: Credit Suisse, Intex,

Impact on CDO Deal Backed by Bond C Compared with Bond A and B, Bond C not only has a higher percentage in fixed rate loans (relative to Bond A) but a higher percentage of loans covered by mortgage insurance (MI) as well. Because the MI premium is taken out of the WAC, a larger share of MI covered loans will increase the AFC risk, even for a high WAC bond, such as Bond C (7.99%). High percentage of fixed rate loans and MI coverage and low OC level make the CDO deal backed by Bond C exposed to even higher AFC risk

Another disadvantage that Bond C has is that its OC level is much lower than the OC level of Bond A and Bond B (we think this is probably because it has a high MI coverage). It is only 0.5% versus 1.65% for Bond A and 2.25% for Bond B. As mentioned earlier, a low OC level will exacerbate the AFC risk. Last, like most HEQ floating bonds, Bond C’s collateral has a periodic cap of 1%, which is lower than Bond A’s (1.17%) and Bond B’s (1.5%)124, which further limits the interest collection from the HEQ loans and increases the AFC risk. Exhibit 117 shows the results of the same sample CDO deal backed by Bond C. And Exhibit 118 shows the results without Turbo. We assume zero CDR here again. Overall, the conclusions are very similar between Bond B and Bond C. We believe that the much higher WAC of Bond C and the cap contract within the deal offset its higher percentage of MI. Given that, we still prefer Bond B a little bit more than Bond C. Exhibit 119 shows the IC ratio of AA tranche backed by both bonds in the +300-bps scenario. The lines are pretty much on top of each other early on before they reach around period 20, where the two lines start to diverge. Around period 22, the AA backed by Bond C starts to fail the test (that is why the WAL of AA in the Bond C scenario is a little bit longer than that of AAA).

Exhibit 117: Result of CDO Deal Backed by Bond C – with Zero CDR and with Turbo HEL Bond Base Case, Forward Curve FWD+300, Slow Fixed VCPR by 25% FWD+400, Slow Fixed VCPR by 25% FWD+500, Slow Fixed VCPR by 25%

Tranche AAA

Tranche AA

Tranche BBB

Equity

WAL

WAL

IRR

DM

WAL

IRR

DM

WAL

IRR

DM

IRR

4.17

4.06

4.46%

0.38%

4.06

5.08%

1.00%

5.49

7.67%

3.15%

15.47%

4.61

4.39

7.36%

0.38%

4.72

8.09%

1.00%

4.13

10.25%

3.15%

16.71%

4.61

3.99

8.14%

0.38%

6.94

9.50%

1.00%

2.81

10.65%

3.15%

12.83%

4.61

4.13

9.11%

0.38%

7.27

10.48%

1.00%

7.14

1.59%

N/A*

N/A*

Source: Credit Suisse, Intex, *N/A means a large negative number

124


Bond A and Bond B both have a higher-than-average periodic cap.

107

31 March 2006

Exhibit 118: Result of CDO Deal Backed by Bond C – with Zero CDR BBB


Without Turbo WAL IRR 6.65 7.80%

With Turbo WAL IRR 5.49 7.67%

DM 3.15%

DM 3.15%

Equity Without Turbo With Turbo IRR IRR 16.61% 15.47%

7.66

9.35%

3.15%

4.13

10.25%

3.15%

19.73%

16.71%

7.76

6.59%

1.60%

2.81

10.65%

3.15%

13.10%

12.83%

8.08

-0.16%

N/A*

7.14

0.51%

N/A*

N/A

N/A

Source: Credit Suisse, Intex, *N/A means a large negative number

Exhibit 119: IC Ratio of AA Tranche Backed by Bond B and C +300-bps Scenario 250%

200% Pass

Ratio

150%

AA IC Trigger: 115%

100%

50%

Fail

0% 1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Period AA IC_Bond B

AA IC_Bond C


The last thing we would like to point out is that the cap contract associated with Bond C has a much higher strike rate (well above 6%, and this varies depending on time and group125) than the strike rate of the cap contract associated with Bond A. Given that the deal also has a higher percentage in fixed rate loans and almost 50% MI coverage, the protection provided by its cap agreement could be limited in more stressed scenarios.

Putting All Three Bonds Together Some good news is that, in reality, ABS CDOs are backed by different asset classes and, within the same asset class, different bonds with various features. So we created a “portfolio” of these three bonds, equally weighted, and used this “diversified” pool to back the CDO deal. Not surprisingly, the results are less extreme. Exhibit 120 shows the results with zero CDR and Turbo. Although the WAL of the BBB tranche still gets extended to 8.57 in the third stressed scenario (+500), the return stays high at 12.7% and the DM only drops to 2.57%. Compared with the results of Bond B and Bond C, where the WAL gets extended and IRR and DM are reduced to very low levels, it is clearly better now. 125 For example, in September 2004, the strike rate is 6.6%, and in October 2004, it is 6.82% for Group 1 loans, while 6.31% and 6.52% for Group II loans. Also, the notional of the cap decreases over time.


108

31 March 2006

Exhibit 120: Result of CDO Deal Backed by Three Bonds – Zero CDR and with Turbo


HEL Bond WAL 4.44

Tranche AAA WAL IRR DM 4.12 4.49% 0.38%

WAL 4.12

Tranche AA IRR 5.10%

DM 1.00%

Tranche BBB WAL IRR 5.44 7.71%

DM 3.15%

Equity IRR 15.89%

4.86

4.06

7.24%

0.38%

6.67

8.54%

1.00%

3.82

10.22%

3.15%

16.71%

4.86

3.90

8.10%

0.38%

7.34

9.57%

1.00%

3.19

10.92%

3.15%

14.91%

4.89

3.95

9.03%

0.38%

7.33

10.50%

1.00%

8.57

12.71%

2.57%

N/A*


Remember that WAL is a measurement of how fast the principal gets paid back, while IRR is determined by not only the principal payback but also how much interest can be received. In the +500-bps scenario, because of AFC shortfall, there is not much cash flow left for paying interest on BBB tranche after paying interest on the AAA and AA tranches in the first seven years or so, and the entire principal cash flow goes to AAA (from a switch to sequential pay due to IC test failure). As a result, not much gets paid on BBB’s principal – not until both AAA and AA tranches are paid off. On the IRR front, thanks to the interest cash flow from Bond A, the BBB tranche gets paid in interest after seven years (no need to pay interest on AAA and AA tranches because they have been paid down, yet nothing is left for equity tranche); thus, its IRR gets boosted to 12.7%126. Remember again that, when the CDO is backed by Bond B or C, the BBB tranche does not get much from interest payment in the +500-bps scenario. So, as can be seen, the presence of several bonds with different features should act to reduce any extreme impact AFC risk might cause on ABS CDO deals.

Conclusion In this article, we investigated the impact of available funds cap risk of home equity bonds on ABS CDOs with regard to average life, return, and the IC compliance test. As can be seen, AFC risk is quite different depending on the home equity collateral bond structural and collateral features. In addition, the impact of AFC on different tranches of the CDO could vary and can also depend on the structure of CDO (such as deals with/without a Turbo). Our major findings/conclusions are summarized as follows: From a macro perspective, we believe interest rates would need to rise dramatically before sizable AFC risk affects the cash flows of ABS CDOs. Based on our analysis, three-month LIBOR would have to jump to 9% in two years (as of now, it stands at around 1.7%). This, of course, represents a very extreme scenario and is probably not very likely to happen. Moreover, hopefully, the economy will improve as rates go up, and thus, defaults on the home equity loans will go down. From a micro perspective, investors, as well as CDO managers, need to be aware of the drivers of AFC risk. To mitigate or avoid AFC risk, CDO managers should try to pick floating bonds with the following features to the extent possible: a relatively low percentage of fixed rate loans, a low percentage of MI coverage, higher available OC level, and effective hedging vehicles (such as a cap contract). In addition, for BBB-tranche CDO investors, a Turbo structure will further protect them from AFC risk and, when AFC shortfall is absent, improve the performance significantly. Finally, by investing in different bonds, the diversity effect will likely prevent the extreme scenarios from happening and thus avoid large losses from AFC risk. We hope this piece is useful to investors as a framework for understanding the extent that ABS CDOs are exposed to AFC risk. 126 Notice that even when the CDO is backed by Bond A only, in the +500-bps scenario, the IRR for BBB is 11.55% (lower than 12.71% here). That is because, when only Bond A is used, the BBB is paid down fast (WAL only at 2.72) and the rest of the cash flow goes to equity. However, with three bonds mixed, the WAL is extended to 8.57, and thus, some of the cash flow goes to pay BBB's interest rather than it all going to equity.


109

31 March 2006

Chapter 2. Collateralized Loan Obligations (CLOs)


110

31 March 2006

Calling Attention to CDO Calls127 Overview CDO calls have recently become one of the hottest topics in the secondary CDO market. We estimate up to $43 billion of CDOs will exit their non-call period over the next 12 months. This is based on the typical non-call period of 3-4 years and recognizes the majority of CDOs called to date are emerging market (EM) and high yield (HY) CDOs.128 With many CDOs trading at a premium, it is imperative that investors understand the drivers of the decision to call. We provide an overview of CDO calls in four points: 1)

Call Provisions: The Nitty-Gritty. We present the call provision found in most deals and the basic requirements for a deal to be callable.

2)

Call Rationale. A discussion of the primary drivers of CDO calls and whether they make economic sense.

3)

Candidates for Call. Characteristics of CDOs which may be good call candidates from the perspective of the equity holder.

4)

Blocked Call: Deterrents to Calls. Factors that may deter the callability of a deal.

We provide a list of known called CDOs at the end of this report.

Call Provisions: The Nitty-Gritty A typical CDO carries a set of optional redemption provisions (Article IX in most indentures). Based on the Optional Redemption provision, at the direction of a supermajority (two-thirds), or in some cases a majority (one-half), of the equity holders, a deal may be called following the end of the non-call period, usually about 3-4 years from the closing date. In order for a deal to be called, liquidation proceeds must be sufficient to cover the following liabilities and expenses: • Hedge termination/unwind fees; • Aggregate outstanding principal; • Accrued, unpaid and deferred interest (PIK-able tranches); • Make-Whole provisions. Some deals require an optional redemption premium for fixedrate tranches. See below for a detailed discussion; • Administrative and other fees & expenses; • Asset manager and advisory fees. Some deals also include the present value of forgone management fees (as a result of the early termination) for a predetermined period.

127 128

This section was originally published in "The CDO Strategist", Issue #2, May 31, 3005. HY CDO includes both CBOs and CLOs.


111

31 March 2006

The Make-Whole provision merits additional insight. While floating-rate tranches are typically callable at par, certain deals with fixed-rate tranches may be due a premium based on the present value of remaining fixed-rate tranche cash flows, discounted at a predetermined rate. Determining the remaining cash flows varies from deal to deal, but the most popular approaches include: 1.

Taking the coupon payments at each remaining payment date plus the principal (equal to the remaining balance of the tranche) paid back on the expiration date of the make-whole premium;

2.

Dividing the outstanding principal amount evenly among the remaining payment dates between the redemption and the maturity date or an expiration date (usually consistent with the expected average life of the tranche at closing), plus the interest on the notes for each remaining payment date;

3.

Utilizing a predefined principal amortization and interest schedule table.

The actual discount rate is typically calculated as a spread over Treasuries. In general, the Treasury rate is determined by interpolating the Treasury yields, reported on a specific date before the redemption date, to the remaining life of the tranche. While the discount spread also differs across deals, many CDOs calculate the spread as half the liability spread over Treasuries of the tranche at issuance.129

Call Rationale A call is economically viable if the present value of the call proceeds exceeds the present value of expected future equity cash flows without the call, i.e. : Present Value of Call Proceeds > Present Value of Cash Flows if No Call (Equation 1) Many people prefer to use IRR instead of present value. In terms of IRR, Equation 1 equivalent is: IRR of Reinvesting Call Proceeds > IRR of Future CFs by Investing Call Proceeds in the CDO (Equation 2) For example, assume the net proceeds from the call equal $10 million and by investing this elsewhere the equity holders can earn 12% IRR. To call the deal, the IRR on the future cash flows from the CDO has to be below 12%. Alternatively, using the present value methodology, the present value of future cash flows discounted at 12% has to be below $10 million for the call to be economically rational. The equity holder can also use a scenario analysis to see the profile of both approaches based on the cash flows generated under different assumptions, such as default and prepayment rates, to decide whether to call the deal. We discuss two primary drivers for CDO calls: asset spread compression and liability spread compression. Asset Spread Compression When asset spreads tighten, asset prices appreciate, motivating the equity holder to liquidate the assets in order to lock in gains. A strong credit environment over the last two years has driven spreads in for many collateral markets, particularly the emerging market (EM) and high yield bond (HY) sectors. Not surprisingly, this has fueled the up-tick in EM and HY CBO calls in recent years, as shown in Exhibit 121. The shadowed bars indicate the number of deals called at each point in time.

129

Please note that fixed-rate tranches are usually priced at a spread over swap.


112

31 March 2006

The price appreciation in leveraged loans is relatively limited, as loans are typically floating rate and callable at par. However, the fact that many CLOs could have other asset types, such as HY bonds (usually up to 10%), included in the collateral can raise the price further. Even if the collateral is not trading at a significant premium, it is still economically possible for a deal to be called, although it may not be on the first redemption date.

Exhibit 121: Asset Spread Compression vs. EM/HY CBO Calls 700

Asset Spread (bps)

600

EM/HY CBOs Called * BB US HY Bonds (CSFB HY Index, sw aps) BB CSFB SBI (sw aps) BBB CSFB SBI (sw aps)

1

500 400 300 200 100 0

O

ct -0 0 Ja n01 Ap r01 Ju l-0 1 O ct -0 1 Ja n02 Ap r02 Ju l-0 2 O ct -0 2 Ja n03 Ap r03 Ju l-0 3 O ct -0 3 Ja n04 Ap r04 Ju l-0 4 O ct -0 4 Ja n05 Ap r05

0

* Each vertical bar represents one EM/HY CBO called, i.e. the thicker the bar, the more deals called at that time. Source: Credit Suisse, based on CREDIT SUISSE’s Sovereign Bond Index and High Yield Bond Index

Liability Spread Compression We think asset spread compression is closely related to CDO liability spread compression. The latter is mainly a result of an improved credit environment, advancements in structuring technology, a maturing secondary CDO market, and most importantly, increasing investor acceptance and product demand. The compression in liability spreads may also potentially trigger CDOs to be called and refinanced into new deals, especially for HY CLOs. We believe the refinancing is usually initiated by CDO managers or issuers. If the managers don’t have enough share of equity holdings, they will either recommend the equity holders call or purchase the necessary shares from them.130 Equity holders should base their decision on Equations 1 or 2 shown above. The cost savings may boost the potential cash flows to equity holders, although this also depends on the return from the asset side of the new deal. Other factors driving HY CLO calls include both limited reinvestment options because of collateral eligibility criteria such as maturity restrictions, and limited availability of such collateral at cost-effective prices. Moreover, the surge in leveraged loan refinancings during the low rate environment of 2003 and 2004 left many HY CLOs with large cash positions, which diminishes equity returns and increases the incentive to call. Exhibit 122 shows CLO call activity versus the liability spread compression.

130

For some older CLO deals, it only takes the majority share of equities to call the deal.


113

31 March 2006

Exhibit 122: Liability Spread Compression vs. HY CLO Calls 350

Liability Spread (bps)

300

HY CLOs Called * AAA HY CLO AA HY CLO A HY CLO BBB HY CLO

1

250 200 150 100 50 0

Au g0 O 1 ct0 D 1 ec -0 Fe 1 b0 Ap 2 r0 Ju 2 n0 Au 2 g0 O 2 ct -0 D 2 ec -0 Fe 2 b0 Ap 3 r03 Ju n0 Au 3 g0 O 3 ct -0 D 3 ec -0 Fe 3 b0 Ap 4 r04 Ju n0 Au 4 g0 O 4 ct -0 D 4 ec -0 Fe 4 b0 Ap 5 r05

0

* Each vertical bar represents one HY CLO called, i.e. the thicker the bar, the more deals called at that time. Source: Credit Suisse

Candidates for Call In addition to the aforementioned rationales for calls, several CDO characteristics signal call candidates from the perspective of the equity holder. These include: Deals at the End of or After the Reinvestment Period As deals begin amortizing following the end of the reinvestment period (typically 5-7 years after closing), cash flow is diverted to pay down the tranches beginning with the cheapest, and most senior, notes. As a result, the all-in funding cost of the deal rises, reducing the equity return. Equity holders, therefore, have greater incentive to call the deal. Deals with Limited Reinvestment Options Many deals were called even before the end of the reinvestment period (see Exhibit 123). For CDOs with limited reinvestment options, the upside potential of trading gains and the ability to take advantage of market opportunities is capped. Collateral eligibility criteria such as average life, combined with the significant jump in secondary prices, limit the manager’s investment options, which results in a build-up of large cash positions (from principal proceeds and prepayments) and decreasing equity returns. Equity holders may find more value in calling the deal, shifting their interest to other alternative investments. Deals with Failed Coverage Tests At the first sign of a failed coverage test, cash flow is diverted away from the equity tranche to pay down senior notes. Equity holders must decide whether the tests can be cured so that cash flows can be resumed, or instead there may be further future losses, in which case calling the deal may result in a higher return.


114

31 March 2006

Blocked Call: Deterrents to Calls Several factors may deter the callability of a deal even though the call might make economic sense. These include: Identifying the Equity Holders As mentioned, most CDOs require a super-majority (two-thirds) vote from the equity holders to execute the optional redemption. The problem therein lies not only in getting the consensus of two-thirds of the holders to call the deal, but also in identifying the equity investors. For older deals, although the equity is less widely distributed, obtaining an investor list is more difficult as the trustee is not required to disclose the list. In addition, the equity may have changed hands several times during its lifetime. For more recent deals, the difficulty lies in much wider equity distributions, although many trustees are now required to disclose the holder list to requesting equity investors. Nature of the Equity Holders Whether the optional redemption ultimately gets exercised is dependent on the investment nature of the equity holder. While total-return investors are generally in favor of monetizing call potential, buy-and-hold investors, which hold most of the outstanding equity shares (especially in older deals), are more reluctant to sell. Even if a call is economically viable per our definition, the equity holder may still realize an immediate loss by executing the call, which may be unacceptable to many buy-and-hold investors. The Redemption Process Furthermore, the redemption process is far from trivial. Following a thorough ratification process to determine whether the call is feasible, proof that the collateral liquidation would be sufficient to cover the liabilities and expenses must be provided to the trustee in advance of the sale. This often takes the form of binding agreements with a highly rated counterparty or bid-side quotes with some haircut based on the amount of time to the redemption date. The process may require a significant amount of time, during which the market may move. For the typical buy-and-hold investor, the ends may not justify the means. Refinance Realities While the rally in CDO liabilities has motivated redemptions and subsequent deal refinancings, the reality is that several barriers hinder the ability to refinance. The collateral in CDOs past the non-call period may be trading at a premium in the secondary market, making it potentially difficult to roll into a new transaction. Other eligibility concerns include: credit impaired and credit deteriorated assets, which in many seasoned CDOs is likely; minimum ratings criteria; and average life considerations.


115

31 March 2006

Exhibit 123: CDOs Called Deal Name HY CBO AmVestors CBO Trust I Astron CBO Cedar Lake CBO Ltd. Dresdner RCM Caywood Scholl CBO I, Ltd. IBEX Financial II MassMutual/Darby CBO LLC Polar Funding I Ltd. Robeco CBO I, Ltd. San Joaquin HY CBO I Topsail CBO, Ltd. HY CLO AMMC CDO I, Ltd. Campobello Master Trust, Series 1999-1 Commercial Loan Funding Trust I Eaton Vance CDO IV, Ltd. ELC (Cayman) Ltd. 1999-3 ELC (Cayman) Ltd. 2000-1 ELC (Cayman), Ltd. Great Point CLO 1999-1 Ltd Harch CLO I, Ltd. Lakeshore Commercial Loan Master Trust I Northwoods Capital Ltd Pacifica Partners I, LLP Sequils I SEQUILS IV Van Kampen CLO I, Ltd. EM CBO Alliance Investments, Ltd. Atlas CDO, Ltd. Augusta Funding 1997-B EM CDO I * EM CDO II * Global Funding Ltd A Global Funding Ltd C Global Sovereign CBO, Ltd ML CBO XVII Series 1998-Carlson-1 New Alliance Global CDO, Ltd. One World Global Sovereign CBO Ltd. OUB Sovereign Emerging Markets CBO I Ltd. Phoenix Global Sovereign CBO, Ltd. TCW GEM IV, Ltd CRE CDO Mach One CDO 2000-1 Pinstripe I CDO, Ltd.

Manager

Deal Size ($mm)

Price Date

Non-Call (months)

Reinvest (months) Call Date**

Salomon Brothers Asset Mgmt Orix USA TCW Asst Mgmt Dresdner/Caywood Phoenix Investment Counsel, Inc. DL. Babson (Mass Mutual) ING Ghent Asset Mgmt LLC Robeco NV Pacific Investment Mgmt Company ING Ghent Asset Mgmt LLC

$254 $548 $150 $296 $980 $482 $300 $299 $240 $200

12/5/96 6/4/98 7/31/02 10/14/99 8/25/98 12/23/97 11/2/01 6/9/00 9/28/01 3/30/01

60 18 --48 --61 12 36 36 48

60 18 12 43 --61 static 60 60 48

7/1/03 2/1/04 9/30/04 5/2/05 10/4/04 5/16/05 4/1/04 12/30/04 11/2/04*** 4/23/05***

American Money Mgmt Corp. Bank of Nova Scotia Lehman Brothers CP Inc. Eaton Vance Mgmt DL. Babson (Mass Mutual) DL. Babson (Mass Mutual) DL. Babson (Mass Mutual) Sankaty Advisors Harch Capital Mgmt Bank of Montreal Angelo Gordon Imperial Capital Mgmt./Caywood Scholl TCW Asst Mgmt TCW Asst Mgmt Van Kampen

$400 $2,658 $823 $280 $452 $512 $431 $409 $425 $3,051 $475 $500 $713 $500 $1,276

11/30/99 4/26/99 8/20/97 3/14/01 12/9/99 6/13/00 12/22/98 5/26/99 3/10/00 7/17/98 1/28/99 8/27/98 4/1/99 4/28/00 10/8/97

61 ----24 48 36 37 63 38 --48 --36 36 36

61 ----60 60 60 58 60 60 --72 --84 60 36

1/26/05 5/1/03 6/1/03 4/1/04*** 4/14/05 4/11/05*** 1/20/05 9/20/04 3/22/05 11/1/03 9/13/04*** 6/1/04 6/1/04*** 5/24/04*** 4/8/05

Alliance Capital Mgmt Ashmore Investment Mgmt Bear Stearns Asset Mgmt N/A N/A Bear Stearns Asset Mgmt Bear Stearns Asset Mgmt Bear Stearns Asset Mgmt Carlson Mgmt. (Jersey) Ltd. Alliance Capital Mgmt One World Investments OUB Asset Mgmt Phoenix Investment Counsel, Inc. TCW Asst Mgmt

$388 $170 $282 N/A N/A $301 $269 $104 $173 $250 $198 $242 $250 $231

11/12/97 3/12/01 4/8/97 N/A N/A 1/7/98 4/21/98 4/8/99 7/16/98 4/25/01 7/19/01 6/30/98 8/10/00 1/22/99

--48 48 N/A N/A 24 24 24 36 35 36 24 41 24

--60 96 N/A N/A 96 96 60 60 59 60 96 41 96

5/1/04 4/15/04 10/10/03*** 4/21/03 9/3/03 1/8/04*** 10/23/03*** 10/8/03*** 7/23/03 4/12/05*** 7/26/04*** 6/30/03*** 2/10/04 7/22/03***

Bank One Alliance Capital Mgmt

$310 $484

5/15/00 3/16/01

36 120

static 36

6/29/04 11/2/04

* Confidential Transaction ** In some cases, the ratings withdrawal date *** Deals called before reinvestment period Source: Credit Suisse, S&P, Moody’s, Intex, deal documents


116

31 March 2006

When’s the Best Time to Call? Optimal Timing of CDO Calls and Relative Values131 There has been much discussion in the market on CDO calls or optional redemptions. Notwithstanding all the non-economic factors preventing a CDO from being called, it is important for CDO investors to understand the nuances in assessing CDO calls from an economic perspective. Here we provide a framework for assessing CDO calls, as well as some discussion on relative value. The economic rationale for a CDO to be called is discussed in the previous section (Equations 1 and 2). While simple in principle, there are many factors impacting the value on both sides of the equations, including the following: 1.

Underlying Collateral Factors: 1) Prepayment speed/amortization rate of the underlying collateral 2) Default rate of the underlying collateral 3) Recovery rate after default

2.

Market Factors: 1) The market price of the collateral at the potential call dates 2) The tightening of the liability spreads of CDOs, especially for CLOs 3) The IRR on alternative investments available to equity holders at the time of call

3.

Structural Factors: 1) How many fixed tranches in a CDO and the Make-Whole Provision 2) The hedging agreement embedded in a CDO 3) The management fee and/or incentive fees in a CDO

In our analysis, we use an actual HY CLO deal as an example. Exhibit 124 shows the detailed information, a 2001 vintage deal with one year remaining to the end of the noncall period. Exhibit 124 also shows the base-case prepayment, default and recovery assumptions. By running these assumptions through Intex and using a forward LIBOR curve, we generate cash flows for each tranche for import into our call model. Make-whole premium on fixed tranches could be significant An important issue is to quantify the make-whole premium of fixed tranches based on the Make-Whole Provision specified in the indenture. Usually there is an expiration date for the make-whole premium, before which the redemption price is the present value of the remaining schedule of payments of principal and interest, assuming the entire remaining outstanding principal will be paid at par on the expiration date. After the expiration date, the fixed tranche could be called at par. Exhibit 124 also shows the expiration dates of each fixed tranche. The make-whole premium could be calculated as: (PV of a Par Bond (discounted at Treasury plus make-whole spread, with a maturity from now to the expiration date) – Par)/Par

131

This section was originally published in "The CDO Strategist", Issue #2, May 31, 2005.


117

31 March 2006

Using tranche D2 as an example, the last column in Exhibit 125 shows the results. The make-whole spread for this tranche is 371 bps based on the indenture. Given the remaining maturity to the expiration date of 5.75 years (if called on the first redemption date) and the corresponding Treasury rate of 3.88%, the discount rate to use is 7.59%, much lower than the coupon rate of 12.05%. As a result, the premium needed to pay down this tranche is a whopping 20.68%! So, if the remaining balance of D2 is $11,800,000, the equity holders will have to pay $14,239,972 to the D2 holders if they want to call the deal. If we discount this payment along with the total cash flows D2 holders received before the call date by a discount rate of Treasury rate plus the pricing spread (71 bps), we have a total present value of $14,427,071, or a price (priced to first call date) of $122.26!

Exhibit 124: Sample CLO Deal Deal Information Issue Date Reinvestment End Date Non-Call End Date Legal Maturity Total Size

3/29/01 4/29/06 4/29/06 3/29/16 750,000,000

WAC of Fixed Assets WAS of Floating Assets Floating Rate Assets Payment Frequency

8.85% 2.92% 74.33% Quarterly

Capital Structure Tranche Name A1 A2 B1 B2 C1 C2 D1 D2 Equity

Current Balance 563,500,000 10,500,000 40,000,000 22,500,000 11,700,000 18,000,000 12,000,000 11,800,000 60,000,000

Spread/Coupon L+47 bps 6.28% L+125 bps 6.95% L+205 bps 7.82% L+635 bps 12.05%

Rating Aaa Aaa A3 A3 Baa2 Baa2 Ba2 Ba2

Expiration Date of Make-Whole Premium N/A 4/29/2010 N/A 7/29/2011 N/A 10/29/2011 N/A 1/29/2012 N/A

Base Case Assumptions Prepayment of HY Loans Default of HY Loans Recovery of HY Loans

5% CPR 0.5% CDR 70%

Prepayment of HY Bonds Default of HY Bonds Recovery of HY Bonds

20% CPR 2% CDR 30%

Source: Credit Suisse, INTEX

We apply a similar calculation on other fixed tranches. For floating tranches, equity holders typically only need to pay the par value of the aggregate outstanding amount to call. To calculate the prices for floating tranches, we use the spreads consistent with new issue pricing spreads. For comparison, we also calculate the prices assuming the deal is never called. Exhibit 125 lists the results for all tranches. There are several interesting observations:

132

1.

For this deal to be called on the first redemption date (1 year later), the equity holders will have to pay $655,246,986 (sum of Row 12) to the note holders.132

2.

Equity holders will have to pay significant premiums on fixed tranches. Therefore, the more fixed tranches in a deal, the less likely the deal will be called, holding all else equal.

3.

When priced to the first call date, the prices of all fixed tranches are higher than the prices without call. It is the exact opposite for floating tranches.

We ignore any accrued interest, deferred interest , etc.


118

31 March 2006

th

Exhibit 125: Results of Base Case on the First Redemption Date (4 Quarter from now) Tranche Name A1

A2

B1

B2

C1

C2

D1

D2

(1) WAL of Tranche if no call

3.05

3.05

6.11

6.11

6.93

6.93

7.69

7.69

(2) WAL of Tranche if called Remaining Maturity to Make(3) Whole Expiration Date (Year) (4) Make-Whole Spread (bps) Treasury Rate for Make-Whole (5) Premium (based on (3)) Treasury Rate for Pricing if (6) Called (based on (2)) Treasury Rate for Pricing if No (7) Call (based on (1)) Pricing Spread over LIBOR (for (8) floating)/over Treasury (for fixed) Coupon Rate (Fix) (9) /LIBOR Spread (Float) (10) Make-Whole Premium Remaining Notional (11) (on Redemption Date) Optional Redemption Payout (12) = (11)*(1+(10)) PV of Optional (13) Redemption Payout (14) PV of cash flow before call (15) Total PV of cash flow if called (16) Price if called (17) Price if no call

0.91

0.91

0.91

0.91

0.91

0.91

0.91

0.91

4.00

4.00

5.00

5.00

5.25

5.25

5.75

5.75

77

111

155

371

3.82%

3.87%

3.87%

3.88%

3.40%

3.40%

3.40%

3.40%

3.76%

3.88%

3.88%

3.89%

0.30%

0.71%

0.80%

1.22%

1.95%

2.25%

5.00%

5.20%

0.47%

6.28%

1.25%

6.95%

2.05%

7.82%

6.35%

12.05%

6.16%

8.68%

10.91%

20.68%

522,552,558

9,737,004

40,000,000

22,500,000

11,700,000

18,000,000

12,000,000

11,800,000

522,552,558

10,337,045

40,000,000

24,453,274

11,700,000

19,964,137

12,000,000

14,239,972

501,367,043

9,922,886

38,186,354

23,355,416

11,041,699

18,874,896

10,986,126

13,078,431

62,596,238 563,963,281 $100.08 $100.28

1,375,230 11,298,116 $107.60 $105.15

1,959,210 40,145,564 $100.36 $102.15

1,519,619 24,875,035 $110.56 $109.74

661,204 11,702,903 $100.02 $100.31

1,359,264 20,234,161 $112.41 $109.56

1,164,675 12,150,801 $101.26 $107.21

1,348,640 14,427,071 $122.26 $116.34


To call or not to call? Which price then is the right price? Or, from a relative value perspective, which tranche, floating or fixed, should investors buy and for how much? To answer these questions, we assess the call likelihood of the deal. Exhibit 126 shows the break-down of the numbers. By assuming a market price of $100, the equity holders will collect $689,852,233 if they sell all the collateral. After paying the termination fee of the swap contract and paying down all outstanding notes, the equity holders are left with $33,733,390 on the redemption date, or a present value of $29,923,236.133 Combined with the $11,614,423 present value of cash flows they received from now to the redemption date, the total present value is $41,537,659, which provides the left side of Equation 1.

133 Notice that in our example, there is still one year left from now to the first redemption date, or the end of non-call period.


119

31 March 2006

Exhibit 126: Cash Flows on the First Redemption Date Value Asset Notional (on redemption date) Market Price of Assets* Market Value of Assets (on redemption date) Swap Termination Payment (on redemption date) Principal and Premium to Liabilities Cash flow to Equity (on redemption date if called) IRR of Equity** PV of cash flow to equity on call date PV of cash flow to equity before call date Total PV of cash flow to equity if called PV of future fees (after call date) if not called Total PV of cash flow to equity if not called To Call or Not to Call?

$689,852,233 $100.00 $689,852,233 ($871,857) ($655,246,986) $33,733,390 12% $29,923,236 $11,614,423 $41,537,659 $14,925,119 $68,032,714 Not Call

Source: Credit Suisse, INTEX * Assume dirty price with accrued interest for simplicity ** The current IRR available to equity holders from alternative investments

If the equity holders choose not to call the deal on the first redemption date, they will receive future excess cash flows as well as management and incentive fees if they are also the managers. By discounting the cash flows (including the ones they received from now to the call date) and management and incentive fees at the equity IRR, they could receive a total present value of $68,032,714, much higher than the expected proceeds if they call the deal. Note the management and incentive fees may be a significant amount. We assume the manager is not necessarily the majority equity holder and ignore the management and incentive fees. In this example, the decision is not to call the deal even without these fees. Therefore, from an economic perspective, this deal is unlikely to be called on the first redemption date. If the deal is not called on the first call date but is still priced to the first call date, the fixed tranches are over-valued while the floating tranches are under-valued. When’s the best time to call then? Does this suggest tranches should be priced assuming no-call? No, because the deal may be called later. Exhibit 127 shows whether to call or not to call on each payment date/redemption date by number of quarters from today.

Exhibit 127: Call Decision at Each Redemption Date Call Date (# of quarters from now) PV Cash Flow to Equity If Called PV of Cash Flow to Equity If Not Called* Call or Not Call

4 41,537,659

8 46,857,301

12 51,100,208

13 51,942,908

14 52,426,590

15 53,099,680

16 53,505,206

20 54,401,451

24 54,305,781

53,107,596

54,317,470

53,795,898

53,815,316

53,336,809

53,465,593

53,132,096

52,635,609

52,294,879

Not Call

Not Call

Not Call

Not Call

Not Call

Not Call

Call

Call

Call

Source: Credit Suisse, INTEX * Ignore management and incentive fees

It shows, keeping everything else constant, the present value of call proceeds to equity holders will be higher than the present value of cash flows if the deal is called 16 quarters from now. Only on this redemption date, for the first time, will it be economically optimal to call the deal.134

134 If it is not called on the 16th quarter from now, it may still be optimal to call on the later redemption dates.


120

31 March 2006

What’s the fair value for the tranches? Exhibit 128 shows the detailed information on the 16th quarter (from today), when the deal should be called. The prices are very similar for A1 and A2 tranches whether called or not, as the majority of the balance of both tranches have been paid down by then.135 The fair price for these two tranches should be $100.25 and $105.53 respectively, for a DM of 30 bps for the A1 and a spread pick-up over Treasury of 71 bps for the A2, both with a WAL of 2.75 years. We examine the prices against the redemption dates to see how the prices change at each date and find the upper and lower bounds of the fair price. We use Tranche D2 as an example. Exhibit 129 lists the price of D2 called on each redemption date, as well as the price without call. After a certain period, prices converge as the tranche pays down before the potential redemption date. Whether the deal is called or not, the last row lists the final fair price for the tranche. Exhibit 130 plots the prices against time (in terms of number of quarters from today). There are a couple of interesting findings: 1.

For Tranche D2, the price to call can actually drop below the price without the call.136 The lower boundary is around $115 at the 27th quarter, when the makewhole premium expires and the equity holders only have to pay par to call.

2.

The upper boundary for “fair” price should be about $118.25 when it should be called for the first time 16 quarters from today.

Without make-whole premium, more likely to call One of the advantages our model provides is flexible scenario analysis. The first scenario removes the make-whole premium. As shown in Exhibit 131, without the make-whole premium, the deal could be called much earlier – in the 12th quarter, rather than the 16th. How Much Tightening in CDO Liability Spreads To Trigger a Call? We believe a large part of the appreciation in the underlying collateral is being driven by CDO buying.137 As the increasing demand for CLO paper is reflected in the tightening of CLO spreads, we believe there is a connection between the appreciation of leverage loan prices, or tightening in leverage loan spreads, and the tightening in CLO liability spreads. A simple regression of CLO liability spreads on leverage loan spreads shows the correlation is 63%.138 More interestingly, the regression also shows that for each basis point of tightening in CLO liability spreads,139 the leverage loan spread tightens by 0.89 basis point. To answer this question, we use our sample deal as an example. We first stress the CLO liability spread tightening. Then we calculate the spread tightening of leverage loans based on the regression result aforementioned. As leverage loans are floating rate and based on our calculation, we use a spread dollar duration of $0.1140 for each basis point change in spread. Finally we calculate the prices under each scenario and see how much tightening in CLO liability spread will trigger a call.

135 As a matter of fact, if the entire tranche is paid off before the call date, the prices will be exactly the same. 136 All the prices calculated are impacted by the shape of the Treasury curve, as the Treasury rates used are all WAL adjusted. 137 Based on CSFB's estimate, more than 60% of the institutional loans are gobbled by CLOs. 138 Data sample used include monthly numbers from late 2001 to now. The leverage loans spread used is the CSFB Leverage Loan Index. 139 Weighted average spread of CLOs. 140 In other words, for each basis point change in spread, the price of the leverage loan will change by $0.1.


121

31 March 2006

th

Exhibit 128: Results of Base Case at the 16 Quarter from Today Tranche Name B2

C1

C2

D1

D2

(1)

WAL of Tranche if no call

3.05

3.05

6.11

6.11

6.93

6.93

7.69

7.69

(2)

WAL of Tranche if called Remaining Maturity to Make-Whole Expiration Date (Year) Make-Whole Spread (bps) Treasury Rate for Make-Whole Premium (based on (3)) Treasury Rate for Pricing if Called (based on (2)) Treasury Rate for Pricing if No Call (based on (1)) Pricing Spread over LIBOR (for floating)/over Treasury (for fixed) Coupon Rate (Fix) /LIBOR Spread (Float) Make-Whole Premium Remaining Notional (on Redemption Date) Optional Redemption Payout = (11)*(1+(10)) PV of Optional Redemption Payout PV of cash flow before call Total PV of cash flow if called Price if called Price if no call

2.75

2.75

3.91

3.91

3.91

3.91

3.91

3.91

1

1

2

2

2.25

2.25

2.75

2.75

(3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17)

A1

A2

B1

77

111

155

371

3.42%

3.66%

3.66%

3.66%

3.66%

3.80%

3.80%

3.80%

3.76%

3.88%

3.88%

3.89%

0.30%

0.71%

0.80%

1.22%

1.95%

2.25%

5.00%

5.20%

0.47%

6.28%

1.25%

6.95%

2.05%

7.82%

6.35%

12.05%

2.04%

4.14%

5.51%

11.56%

160,402,257

2,988,862

40,000,000

22,500,000

11,700,000

18,000,000

12,000,000

11,800,000

160,402,257

3,049,727

40,000,000

23,431,257

11,700,000

18,992,157

12,000,000

13,163,979

133,401,390

2,563,258

32,606,465

19,192,517

9,108,497

14,936,949

8,274,100

9,220,917

431,527,312 564,928,702 $100.25 $100.28

8,517,200 11,080,458 $105.53 $105.15

7,963,455 40,569,920 $101.42 $102.15

5,635,141 24,827,658 $110.35 $109.74

2,607,788 11,716,285 $100.14 $100.31

4,967,784 19,904,733 $110.58 $109.56

4,245,175 12,519,275 $104.33 $107.21

4,732,308 13,953,225 $118.25 $116.34


Exhibit 129: Tranche D2 Valuation Call Date (# of quarters from now) Call or Not Call

4

8

12

14

15

16

18

20

24

27

28

Not Call Not Call Not Call Not Call Not Call

Call

Call

Call

Call

Call

Call

32

36

Call Not Call

Price of D2 if called

122.26

121.36

119.65

119.16

118.88

118.25

117.63

117.25

115.85

114.92

115.27

116.30

116.34

Price of D2 if not called ever

116.34

116.34

116.34

116.34

116.34

116.34

116.34

116.34

116.34

116.34

116.34

116.34

116.34

Price adjusted by Call

116.34

116.34

116.34

116.34

116.34

118.25

117.63

117.25

115.85

114.92

115.27

116.34

116.34

Source: Credit Suisse , INTEX


122

31 March 2006

Exhibit 130: Price of Tranche D2 123 122 121

Price ($)

120 119 118 117 116 115 114 0

2

4

6

8

10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 # of Quarters from Now

Price of D2 if called

Price of D2 if not called ever

Fair Price adjusted by Call


Exhibit 131: Call Decision on Each Redemption Date (without Make-Whole Premium) 4

8

12

16

20

24

28

PV Cash Flow to Equity If Called

47,709,249

51,407,980

54,275,824

55,577,602

55,551,519

54,590,744

53,411,659

PV of Cash Flow to Equity If Not Called

53,107,596

54,317,470

53,795,898

53,132,096

52,635,609

52,294,879

52,162,267

Not Call

Not Call

Call

Call

Call

Call

Call

Call Date (# of quarters from now)

Call or Not Call Source: Credit Suisse, INTEX

Exhibit 132 shows the results on the first redemption date four quarters from now. Although at a market price of $100 it is not economically rational to call the deal, it is the case if CLO liability spread tightens by 22 bps, causing the market price to jump to $101.78. This change will also impact the final fair price of the tranches because: 1) it changes the probability of call, which, in turn, determines which price to use − the one priced to call or the one sans call; and 2) it changes the discount rate used, as we use the new issue spread for pricing. We can also run the same analysis on a different potential redemption date and create a two-dimensional (liability spread tightening vs. time) matrix.


123

31 March 2006

Exhibit 132: Call Decision on First Redemption Date by Changing CLO Liability Spreads CLO Liability Spread Tightening (bps) Leverage Loan Spread Tightening (bps) Market Price PV Cash Flow to Equity If Called PV of Cash Flow to Equity If Not Called Call or Not Call

-10

-5

5

10

21

22

23

25

30

-8.90

-4.45

-

4.45

8.90

17.80

18.69

19.58

20.47

$99.11

$99.56

$100.00

$100.45

$100.89

$101.78

$101.87

$101.96

$102.05

$36,091,446

$38,845,149

$ 44,291,362

$ 46,983,872

$52,980,826

$53,531,567

$54,082,308

$55,183,789

$56,224,077

$53,107,596

$53,107,596

$ 53,107,596

$ 53,107,596

$53,107,596

$53,107,596

$53,107,596

$53,107,596

$53,107,596

Not Call

Not Call

Not Call

Not Call

Not Call

Call

Call

Call

Call


Higher IRR on Alternative Investments for Equity Holders, More Likely to Call If equity holders can earn a higher IRR on alternative investments, a higher discount rate is used to calculate the present value of future cash flows to the equity holders if not called, or the right side of Equation 1. The lower the present value, the more likely equity holders call the deal. In other words, if the equity holders have limited investment options, the deal is less likely to be called. Faster Prepayment Speed, More Likely to Call So far we used base line prepayment and default assumptions: 5 CPR and 2 CDR for bonds and 20 CPR and 0.5 CDR for loans. What if the expected prepayment speed is faster? Given a sequential payment schedule, faster prepayments may reduce the leverage and increase the funding cost faster. Also, faster prepayments retire the notes earlier, reducing potential management and incentive fees collected in the future. All these factors contribute to a higher likelihood of calling the deal when prepayment jumps.

Closing Thoughts Assessing the call risk of CDOs is no easy task, even from a pure economic perspective. The diversity of CDO structures and the unpredictability of market conditions make it difficult to precisely estimate the probability of call and evaluate a CDO tranche’s fair value from a macro perspective. We take a micro approach by leveraging the CDO modeling expertise and CDO deals covered by Intex, running projected cash flows through our CDO call model. Based on this model, we can gauge the impact and sensitivity of each parameter on CDO calls and reasonably estimate the fair value of a certain tranche. The market might over- or under-estimate the call probability from time to time. If a floating tranche is priced to call but the call probability is very low, the tranche will be undervalued; if a fixed tranche is priced to call but the model shows the call is not very likely, the fixed tranche is usually overvalued, especially if it has a more generous make-whole premium. In addition, typically the room for profit is bigger for lower-rated tranches.


124

31 March 2006

A Comparison of US and European CLOs141 The European CLO market has seen tremendous growth in recent years, echoing the growth of the US CLO market.142 In this section, we take a comprehensive look at these two markets, comparing the underlying collateral, deal-level characteristics and market conditions. The objectives of this piece are to provide investors with a greater understanding of both the US and European CLO markets, to keep readers abreast of new developments in the CLO markets, and to advocate continued improvement of analytical and valuation capabilities.

The collateral: US vs. European leveraged loan markets Leveraged loan issuance strong in both the US & Europe

First let’s look at the underlying collateral, the institutional leveraged loan markets. The issuance of both US and European leveraged loans have increased dramatically since 2003, yet driven by different factors. In Europe, LBOs (Leveraged Buy Outs) have been the primary force behind the surge in leveraged loan issuance, while in the US, other factors, such as M&A activity and refinancing due to the low interest rate environment, have contributed to the substantial growth.

Exhibit 133: New Issue Institutional Leveraged Loan Volume: US vs. Europe New Institutional Loan Volume ($ Billions)

250 US ($BN)

223

Europe ($BN)

200 152 150

118

100 55

64

50

50

55

32

5

7

11

13

13

1999

2000

2001

2002

2003

26

0 2004

Jan-Oct 2005

Source: CREDIT SUISSE, LPC, S&P LCD. European figures converted to USD using Euro spot rate of 1.1953.

Exhibit 133 shows the total volume of newly issued institutional leveraged loans in the US and Europe. Compared to the US market, the European market is still relatively small: $26 billion versus $223 billion in 2004. However, in terms of the pace of growth, the European market is equally as impressive.143 LBO drives European loan market

Unlike its US counterpart, most of the proceeds from European leveraged loan issuance are used for LBO financing, as shown in Exhibit 134 and Exhibit 135. An astonishing 95% of European issuance during the first half of 2005 was driven by LBOs. This phenomena has critical implications for analyzing the credit risk of European loans as LBO-motivated issuances tend to have more aggressive credit characteristics.

141

This section was originally published in "The CDO Strategist", Issue #12, December 15, 2005. In this piece, we use "CLO" and "CDO" interchangeably. For a further discussion of European and US leveraged loan markets, please refer to CSFB’s Global Leveraged Finance Strategy & Portfolio Products report: The Week in Leveraged Finance, Week Ending June 9, 2005, by Sam DeRosa-Farag and team.

142 143


125

31 March 2006

Exhibit 134: US Leveraged Loans: Use of Proceeds* Recap/ IP O Recap/ Other 5%

Other 8%

Exhibit 135: Euro Leveraged Loans: Use of Proceeds* Refinancing 5%

Refinancing 33%

14%

Recap/ Dividend 20%

M &A 20%

LB O 95%

Source: Credit Suisse, S&P LCD * During 1st half of 2005

Higher leverage for European loans

Source: Credit Suisse, S&P LCD * During 1st half of 2005

The higher risk embedded in European loans can be exhibited by comparing the leverage ratios. Both senior debt multiple and total debt multiple are higher for European loans than for US loans (see Exhibit 134 and Exhibit 135). Especially noteworthy is the debt multiple of European loans jumping significantly, to 5.5 times EBITDA in recent months, a 7-year high.

Exhibit 136: Comparing Leverage: Average Senior Debt Multiples 5.0 Average Senior Debt/EBITDA

4.5

4.3

4.0

3.6

3.5 3.0 2.5 2.0 1.5 1.0 0.5

US

Europe

Ju

M

ar -

98 l-9 N 8 ov -9 M 8 ar -9 9 Ju l-9 N 9 ov -9 M 9 ar -0 0 Ju l-0 N 0 ov -0 M 0 ar -0 1 Ju l-0 N 1 ov -0 M 1 ar -0 2 Ju l-0 N 2 ov -0 M 2 ar -0 3 Ju l-0 N 3 ov -0 M 3 ar -0 4 Ju l-0 N 4 ov -0 M 4 ar -0 5

0.0

Source: CREDIT SUISSE, S&P LCD

Exhibit 137: Comparing Leverage: Average Total Debt Multiples

Average Total Debt/EBITDA

6.0 5.5

5.5 5.0 4.5

4.0

4.0 3.5

US

Europe

M ar

-9 8 Ju l- 9 N 8 ov -9 M 8 ar -9 9 Ju l- 9 N 9 ov -9 M 9 ar -0 0 Ju l- 0 N 0 ov -0 M 0 ar -0 1 Ju l- 0 N 1 ov -0 M 1 ar -0 2 Ju l- 0 N 2 ov -0 M 2 ar -0 3 Ju l- 0 N 3 ov -0 M 3 ar -0 4 Ju l- 0 N 4 ov -0 M 4 ar -0 5

3.0



126

31 March 2006

European loan spreads more static than US loan spreads; pricing abnormalities exist

There is a remarkable difference between the US and European leveraged loan markets in terms of loan pricing and spread performance. As shown in Exhibit 138, the pricing and spread movement for European loans has been very static, whereas US loan spreads have tightened dramatically since mid-2003. In addition, given BB spreads on top of B spreads for European loans suggests European loan pricing is driven by factors other than credit ratings. That said, we note a recent growing differential in pricing, with BB spreads about 20 bps (272 vs. 292) tighter than B spread.

Exhibit 138: Institutional Loan New Issue Spreads New Issue Spreads (over LIBOR)

430

US B Spread

Euro B Spread

US BB Spread

Euro BB Spread Back to "normal": B w ider than BB

380 Euro BB wider than B 330

292 272 269

280 230

187

D

ec -9 M 9 ar -0 Ju 0 n0 Se 0 p0 D 0 ec -0 M 0 ar -0 Ju 1 n0 Se 1 p0 D 1 ec -0 M 1 ar -0 Ju 2 n0 Se 2 p0 D 2 ec -0 M 2 ar -0 Ju 3 n0 Se 3 p0 D 3 ec -0 M 3 ar -0 Ju 4 n0 Se 4 p0 D 4 ec -0 M 4 ar -0 Ju 5 n05

180


With this, CDOs benefit from illiquidity and pricing discrepancies; the arbitrage between asset and liability for European CLOs is higher than for US CLOs, improving CDO economics in Europe. This attractive arbitrage exists because while US and European CLO liability costs have dropped in tandem, European leveraged loan spreads have remained wider – a point we revisit later. Note that the spread difference between European BB-rated loans and US BB-rated loans is 85 bps, a very attractive pick-up assuming all things equal. More European loans are unrated

Unlike the US market, the European loan market remains largely private in nature as a significant share of loans are unrated and held by traditional banks. Exhibit 139 and Exhibit 140 compares the rating distributions of US and European loans based on the CREDIT SUISSE US and Western European Institutional Leveraged Loan Index; nearly 47% of European loans are unrated.

Exhibit 139: US Institutional Loans by Rating*

NR CCC/Split 1% CCC 8%

Split B 9%

Split B B 10%

Exhibit 140: European Institutional Loans by Rating*

Split B B B 6%

Split B 1.0%

Split BB 11.8%

Split BBB 0.7%

BB 8.7% B 30.9%

BB 27%

B 39%

Source: Credit Suisse, As of 11/30/2005. * Based on CREDIT SUISSE US Institutional Loan Index


NR 46.8%

CCC/Split CCC 0.1%

Source: Credit Suisse, As of 11/30/2005. * Based on CREDIT SUISSE European Institutional Loan Index

127

31 March 2006

It is helpful to understand who the participants are in leveraged loans of both jurisdictions. Exhibit 141 and Exhibit 142 show the investor bases of all leveraged loans (institutional and pro-rata tranches). 144 Clearly, the biggest investors of US leveraged loans are CDOs, while European banks dominate the European loan market with a 62% share. This is due to the composition of leveraged loans in both markets: the US market has a much larger institutional share of leveraged loans while the European market remains predominantly pro rata (see Exhibit 143 and Exhibit 144). This helps explains why European institutional loan pricing has been by and large static; most of the market remains in the private sector, minimizing price fluctuations and credit rating differentiation. However, we note that the institutional share in the European loan market has continued to grow, likely due to the proliferation of institutional investors and CDOs in the market.

CDOs dominate US leveraged loan market while banks dominate European leveraged loan market

Because CLOs invest mostly in institutional loans, their market share looks much more similar between the jurisdictions when only considering the institutional loan portion: CLOs dominate the US institutional loan market with 61% and also dominate the European market with a more impressive 83% (as of 1H 2005).145

CLOs dominate the institutional loan markets

Exhibit 141: Investors of ALL US Leveraged Loans

Exhibit 142: Investors of ALL European Lev. Loans

Finance Co. 6% Domestic Banks Euro pean 10% Banks 8%

Other 12%

Other 5%

CDOs 19%

Insurance Co. 1%

US Banks 5%

CDOs & Hedge/HY Funds 67%

Insurance Co . 4%

Finance Co. 1%

European Banks 62%

Source: Credit Suisse, S&P LCD, As of 1H 2005.

Source: Credit Suisse, S&P LCD, As of 1H 2005.

Exhibit 143: US Pro-Rata vs. Institutional ‘01-‘05

Exhibit 144: Europe Pro-Rata vs. Institutional ‘01-‘05

Pro-Rata

Institutional

Pro-Rata 100%

100% 90% 80% 70%

25%

90%

40%

56%

80%

60%

62%

60%

30% 20%

75%

40%

60%

44%

89%

30%

40%

38%

27%

23%

34%

70% 60% 50%

50% 40%

11%

Institutional

73%

77%

66%

20%

45%

55%

10%

10%

0%

0% 2001

2002

2003

Source: Credit Suisse, S&P LCD. * As of Oct 2005.

2004

2005*

2001

2002

2003

2004

2005*

Source: Credit Suisse, S&P LCD. * As of Oct 2005.

144 Leveraged loans are typically structured with a pro rata portion, comprising a revolving facility and a Term Loan A (TLA), and an institutional loan portion, comprising Term Loan B (TLB), Term Loan C (TLC) or other tranches. 145 CSFB Global Leveraged Finance Strategy & Portfolio Products, and S&P LCD.


128

31 March 2006

Media and Telecom: Lion’s Share

It is also interesting to see the industry breakdown of both loan markets, as shown in Exhibit 145 and Exhibit 146. “Media and Telecom” stands out as the biggest bucket in both jurisdictions: 19% in US and 36% in Europe.

Exhibit 145: US Institutional Loan by Industry*

Ret ail 2%

ServiceTransportat ion 3% 9%

Utilit y 10%

M et als/M ineral 4%

Aerospace 2%

Exhibit 146: European Institutional Loan by Industry* Consumer NonUtility Transportation durables Consumer 2.1% 0.5% 4.1% Energy Aerospace Chemicals Durables Service 0.3% Retail 1.4% 1.1% 9.6% 9.1% Food/tobacco 6.8% M etals/M ineral 4.0% Financial 0.1% 1.7%

Chemicals 5% Consumer Products 3% Energy 7% Financial 2%

M edia/ Telecom 19% M f ct uring 3%

IT 5% Housing 3%

Forest Prod/Container 6.1%

Food & Drug 2% Healt hcare Gaming/ Leisure ForestFood/ t obacco 3% 7% 6% Prod/ Container 6%

Source: Credit Suisse, As of 11/30/2005. * Based on CREDIT SUISSE US Institutional Loan Index

M fcturing 6.4%

M edia/Telecom 35.9%

Housing Gaming/Leisure 3.0% 4.7% Healthcare 3.2%

Source: Credit Suisse, As of 11/30/2005. * Based on CREDIT SUISSE European Institutional Loan Index

How have both US and European loans performed so far? Unfortunately, the performance data on European loans is very limited, however, we can gain some perspective by observing the ratings transition matrix. Exhibit 147 and Exhibit 148 show the average oneyear rating transitions of both US and European loans. Although the comparison isn’t exactly “apples-to-apples” (i.e. the US matrix is based on a much longer history – 20 years from 1984 to 2004 – while the European numbers are only based on the performance during 2003 and 2004) we can glean some general ideas.

Exhibit 147: Average 1-Year Transition Rates of US Loans, 1984-2004 (%) From/To

BB+

BB

BB-

B+

B

B-

BB+ BB BBB+ B BCCC/C

69.6 7.5 2.5 0.4 0.5 0.3 0.2

6.8 71.8 8.0 1.7 0.7 0.2 0.4

3.7 8.2 71.4 6.0 2.0 0.8 1.0

1.6 3.2 9.0 75.8 8.6 4.1 1.3

0.9 1.8 3.2 6.8 65.6 8.1 3.1

0.2 0.5 1.2 2.7 6.4 60.1 6.7

CCC

D Downgrade

0.7 0.6 1.0 1.0 1.3 1.9 2.6 3.4 6.2 9.5 11.7 14.0 53.5 33.0

Upgrade or Stable

Ratio

69.6 79.3 81.9 83.9 77.4 73.6 66.2

4.8 5.1 4.9 5.4 3.5 2.9 2.0

14.5 15.7 16.6 15.5 22.1 25.7 33.0

Source: S&P

Exhibit 148: Average 1-Year Transition Rates of European Loans, 2003-2004 (%) From/To BB+ BB BBB+ B BCCC

BBB

BBB-

BB+

BB

BB-

B+

B

B-

CCC

5.6 0.0 0.0 0.0 1.9 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0

52.8 2.7 0.0 0.7 0.0 1.9 0.0

23.6 73.8 1.6 0.0 0.0 0.0 0.0

11.8 12.0 82.3 5.4 0.0 0.0 0.0

6.3 5.8 11.3 77.7 6.8 1.9 0.0

0.0 5.8 1.6 9.5 71.6 9.4 0.0

0.0 0.0 3.2 4.1 13.5 71.8 13.9

0.0 0.0 0.0 2.7 6.4 8.3 66.2

Upgrade D Downgrade or Stable Ratio 0.0 0.0 0.0 0.0 0.0 6.6 20.0

41.7 23.6 16.1 16.3 19.9 14.9 20.0

58.4 76.5 83.9 83.8 80.3 85.0 80.1

1.4 3.2 5.2 5.1 4.0 5.7 4.0

Source: S&P


129

31 March 2006

Rating transition performance mixed

For example, “Upgrade/Stable versus Downgrade” ratios suggest that at BB+/BB levels, US loans outperform European loans, while at B and below levels, Europe outperforms US.146 This observation seems consistent with the spreads shown in Exhibit 139 B-rated European loans are priced to similar levels as BB-rated loans, perhaps because their credit quality is similar to BB-rated loans. 147 We note that this is just one possible explanation; with more empirical evidence, stronger conclusions may be drawn.

Deal Level: US versus European CLOs Robust CLO issuances

Both US and European CLO markets have exhibited significant growth and expansion in the past several years. This has been driven mainly by increasing investor demand for CLO paper due to superior credit performance. In 2005 so far, approximately $42 billion of US CLOs have been issued, up 68% versus 2004 volumes; the European CLO market, while small compared to the US, has seen an even more impressive growth rate, up 93% from $6.9 billion last year to $13.3 billion in 2005 to date (see Exhibit 149).

Exhibit 149: CLO Volume: US vs. Europe 45.0

41.8 US CLO ($BN)

CLO Volume ($ Billions)

40.0

Europe CLO ($BN)

35.0 30.0 25.0 20.0

24.9 19.1

17.7

17.1

14.4

13.5

15.0

13.3

10.0 5.0

0.4

2.0

3.5

3.4

4.5

6.9

0.0 1999

2000

2001

2002

2003

2004

Up thru 11/2005


Top CLO managers

Exhibit 150 and Exhibit 151 show the top 15 CLO managers for both jurisdictions. With respect to these managers, there is minimal overlap, with the exception of managers such as Babson Capital, Invesco and PIMCO. We have also seen some new managers entering the European CLO market, such as The Carlyle Group, Rabobank, CELF Investment Advisors, GSC Partners, WestLB, AIB Capital Markets, and CSAM.

146

The higher the ratio, the more loans stay stable or get upgraded, than loans get downgraded. The order of the ratio of US loans seems to be reasonable: higher rated loans have better performance, i.e., higher ratios; while the order of European loans seems to be counterintuitive. 147


130

31 March 2006

Exhibit 150: Top 15 CLO Managers in US (all vintages) Rank

US CLO Manager

Total Issuance ($BN)

Deal Count

1 2

Highland Capital Management

8.63

12

Babson Capital

8.19

15

3

Credit Suisse Asset Management

7.57

13

4

ING Capital Advisors

5.33

10

5

Invesco Institutional Inc.

4.85

10

6

Stanfield Partners LLC

4.84

9

7

Ares Management

4.65

10

8

Sankaty Advisors

4.52

10

9

American Express Asset Management Group

4.35

7

10

Black Diamond Capital Management

4.30

6

11

TCW Asset Management

3.63

8

12

Pacific Investment Management Company

3.41

8

13

Deerfield Capital Management

2.92

8

14

Chase Capital Partners (Octagon Credit Investors)

2.79

6

15

ING Pilgrim

2.78

6

Total Issuance ($BN)

Deal Count


Exhibit 151: Top 15 CLO Managers in Europe (all vintages) Rank

European CLO Manager

1

Harbourmaster Capital

3.03

5

2

Alcentra Group

2.62

5

3

Babson Capital Europe Limited

2.57

5

4

Intermediate Capital Group

2.43

8

5

Pacific Investment Management Company

2.06

3

6

AXA Investment Managers

1.60

4

7

Avoca Capital

1.36

3

8

Mizuho Corporate Finance

1.35

2

9

Allied Irish Bank Capital Markets

1.27

3

10

Prudential M&G

1.13

3

11

CELF Investment Advisors

1.13

2

12

Invesco

1.11

3

13

RMF Investment Products

1.11

3

14

NIB Capital Management

0.93

2

15

BNP Paribas

0.89

3


CLO spreads tightening in both markets

CLO spreads have been tightening in both markets. Senior spreads of European CLOs have converged with US spreads while subordinate spreads at the BBB level have compressed even tighter than US levels. Exhibit 152 and Exhibit 153 show historical CLO spreads for AAA and BBB tranches.


131

31 March 2006

Exhibit 152: AAA CLO Spreads: US versus Europe*

AAA CLO Spreads (bps)

75 65 55 45 35

US CLO AAA EU CLO AAA

25

Se p01 D ec -0 1 M ar -0 2 Ju n02 Se p02 D ec -0 2 M ar -0 3 Ju n03 Se p03 D ec -0 3 M ar -0 4 Ju n04 Se p04 D ec -0 4 M ar -0 5 Ju n05 Se p05 D ec -0 5

15

Source: CREDIT SUISSE, Intex * US spread over LIBOR, Europe spreads over Euribor

Exhibit 153: BBB CLO Spreads: US versus Europe*

BBB CLO Spreads (bps)

340 290 240 190

US CLO BBB EU CLO BBB

140

Se p01 D ec -0 1 M ar -0 2 Ju n02 Se p02 D ec -0 2 M ar -0 3 Ju n03 Se p03 D ec -0 3 M ar -0 4 Ju n04 Se p04 D ec -0 4 M ar -0 5 Ju n05 Se p05 D ec -0 5

90

Source: CREDIT SUISSE, Intex * US spread over LIBOR, Europe spreads over Euribor

There has been a convergence in CLO all-in liability costs too. As shown in Exhibit 154, the all-in liability cost of European CLOs is similar to that of US CLOs: both at around 36 bps. As noted earlier, with underlying loan spreads for European loans wider than US loan spreads, the arbitrage is higher for European CLOs. Assuming all things equal, this means higher potential IRR for European CLO equity investors.

Exhibit 154: CLO All-in Liability Cost* 90

Assuming the follow ing capital structure: 70% AAA, 10% AA, 3% A & 7% BBB

CLO Cost of Funding (bps)

80 70 60 50 40 30

EU CLO Cost of Funds US CLO Cost of Funds

20 10 0 2H01

1H02

2H02

1H03

2H03

1H04

2H04

1H05

6ME Oct 05

Source: CREDIT SUISSE, Intex, S&P * US spread over LIBOR, Europe spreads over Euribor


132

31 March 2006

There has been a growing concern regarding collateral over-concentration in CLOs. To address this concern, we compare the collateral industry breakdown and rating breakdown of US CLOs versus European CLOs.

Exhibit 155: US CLO Collateral by Ratings*

CCC & B elo w 2.2%

UNRA TED A 0.1% 4.3%

Exhibit 156: European CLO Collateral by Ratings*

BBB 1.7% BB 35.6%

B 56.1%

BBB 0.4%

UNRATED 38.3%

BB 22.2%

CCC & Below 0.2%

Source: Credit Suisse, Intex. * 2004 – 2005 vintages.

B 38.8%

Source: Credit Suisse, Intex * 2004 – 2005 vintages

More unrated loans in European CLOs

We also looked at rating distribution. As shown in Exhibit 155 and Exhibit 156, the most noticeable difference there are a lot more unrated loans in Europe, which poses additional challenge when analyzing European CLOs.

Exhibit 157: US CLO Collateral by Industries*

Exhibit 158: European CLO Collateral by Industries* Building & Real Est at e

Aerospace & Def ense Transport at i on Ut il it ies 3% Agricult ure 5% 4% Tex t iles 1% Telecom 1%

Chemicals Conglomerat e Mf g. 5%

5% Ret ail

Tr anspor t at ion

6% Consumer Non-

Tex t iles

Durables

1%

Telecom

3% Cont ainers

3%

5% Broadcast ing & Agr icult ur e Ent ert ainment Business Eq. & Serv ices Ut ilit ies 1% 5% 0% Chemicals 3% 9% Conglomer at e Mf g.

Aer ospace & Def ense 1%

10%

4%

9%

Consumer Durables 0%

4% Gr ocery

Ot her

Broadcast i ng &

15%

Ent ert ainment

Oil & Gas 4%

Food Nat ural Resources Lodgi ng 3% 3%

Machi nery

6% Grocery

Leisur e 5%

1%

Healt hcare, Educat ion & Childcare

0%

7% Building & Real Est at e 6%

Ret ail

1%

4%

Consumer Non-Durables Ot her

Food

17%

6%

Oil & Gas 2% Nat ur al Resour ces 1%

Source: Credit Suisse, Intex. * 2004 – 2005 vintages.

No industry overconcentration found

1%

Lodging 3%

8%

6%

Healt hcare, Educat ion &

Leisure

Machinery

3% Cont ainer s

5% Indust rial 0%

Childcare 4%

Source: Credit Suisse, Intex * 2004 – 2005 vintages

Exhibit 157 and Exhibit 158 show the industry distribution of collateral in 2004 and 2005 vintage US and European CLOs available in Intex. Two general conclusions can be drawn from these charts: 1.

The industry distributions are different between US and European CLOs. The top three industries in US CLOs are 1) Healthcare, Education & Childcare; 2) Broadcasting & Entertainment; and 3) Conglomerate Manufacturers. However, the top 3 industries in European CLOs are 1) Transportation; 2) Telecom; and 3) Chemicals.

2.

On an aggregate level, there is no industry over-concentration as the collateral is highly diversified across all industries: no single industry has a share exceeding 10%.


133

31 March 2006

To address the overlapping of issuers among CLO pools, we reviewed each asset in all CLOs issued from 2004 to 2005 of which collateral information was obtainable, and counted the number of CLOs sharing identical loan issuers in their portfolios. Our sample includes 73 US CLOs and 16 European CLOs and Exhibit 159 and Exhibit 160 show the lists of issuers appearing in more than half of the CLOs.

Exhibit 159: Issuer Concentration Among US CLOs (2004-2005 Vintage) Rank

Issuer Name

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

MGM Kerr Mcgee General Growth Properties Graham Packaging Boise Cascade Jean Coutu Group Panamsat Corp Huntsman Corp Constellation Regal Cinemas Inc Reliant Energy Resort International Rockwood Specialties Group Goodyear Tire & Rubber Texas Genco Valor Telecommunications Fidelity National Information Solutions UGS Allied Waste R.H. Donnelley Warner Chilcott Holdings Company

Number of CLOs with This Issuer

Percent*

67 64 60 56 55 54 54 51 50 49 49 49 49 48 48 48 47 47 46 46 46

92% 88% 82% 77% 75% 74% 74% 70% 68% 67% 67% 67% 67% 66% 66% 66% 64% 64% 63% 63% 63%

RankIssuer Name 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

Direct TV Movie Gallery Smurfit Stone Container Dresser Rand Group Novelis Venetian Casino BCP Caylux Lake Las Vegas Resort MCC Iowa Invensys International Universal City Development Partners Charter Communications Pinnacle Foods Community Health Foundation Coal Jarden Nortek Spectrum Brands Cooper Standard Hercules Offshore


Percent*

45 45 45 44 44 44 43 43 42 41 41 39 39 38 38 38 38 38 37 37

62% 62% 62% 60% 60% 60% 59% 59% 58% 56% 56% 53% 53% 52% 52% 52% 52% 52% 51% 51%

Source: Credit Suisse, Intex * Divided by 73, the total number of US CLOs in our sample

Issuer overlap not as It is somewhat disconcerting to see some names appearing in most of the deals, for example, significant as MGM is in 67 out of 73 US CLOs and TDF appears in 13 out of 16 European CLOs. However, on an aggregate basis, the overlap does not seems as significant as anticipated. expected Note that there are about 1,300 issuers in all sampled US CLOs and about 480 issuers in all sampled European CLOs. But only 41 and 25 issuers, US and European respectively, appear in more than half of the sampled CLOs. Insolvency regimes differ among countries

Another challenge facing investors in European CLOs is the fact that the insolvency regimes and bankruptcy procedures among European countries could be significantly different. For example, the laws are relatively more creditor-friendly in the UK while they tend to be less so in France. These differences have important implications on issues such as the recovery rate of leveraged loans and CLOs. For example, S&P assumes different recovery rates for different European jurisdictions, as show Exhibit 161.


134

31 March 2006

Exhibit 160: Issuer Concentration of European CLOs (2004-2005 Vintage) Rank Issuer Name 1 2 3 4 5 6 7 8 9 10 11 12 13


Percent

13 12 11 11 11 10 10 10 10 9 9 9 9

81% 75% 69% 69% 69% 63% 63% 63% 63% 56% 56% 56% 56%

TDF Cognis Deutschland II Grohe Holdings Kabel Deutschland Satbirds Finance Aster Frans Bonhomme Kappa Packaging Tank & Rast Debitel Demag Investments Dragoco Gerberding Editis

Rank

Issuer Name

14 15 16 17 18 19 20 21 22 23 24 25

Fina Cold Ineos Acrylics Finance Rockwood Specialties WAM Acquisition World Directories Acquisition Corleone Capital Elis Group Invensys International Holdings Materis Holding Luxembourg Nachtwache Acq OGF Holding Springer Science & Business Media


Percent

9 9 9 9 9 8 8 8 8 8 8 8

56% 56% 56% 56% 56% 50% 50% 50% 50% 50% 50% 50%

Source: Credit Suisse, Intex * Divided by 16, the total number of European CLOs in our sample

Exhibit 161: S&P Recovery Rate Matrix by Country S&P Priority Category Senior Secured Loans Senior Unsecured Loans Subordinated Loans S&P Priority Category

US

Group 1

Group 2

Group 3

Group 4

56% 40% 22.8% US

60-75% 35-45% 10-15% Group 1

50-60% 35-45% 20-30% Group 2

45-55% 30-40% 15-25% Group 3

40-50% 25-35% 10-20% Group 4

Group 1: Ireland & UK Group 2: Germany, Netherlands & Switzerland Group 3: Austria, Denmark, Finland, Norway & Sweden Group 4: Belgium, France, Greece, Italy, Luxembourg, Portugal & Spain Source: S&P

The secondary CLO markets: US vs. Europe The secondary market of US CLOs has grown dramatically in recent years. Total trading volume of US CLOs in 2004 was estimated to be around $23-$25 billion, more than double the amount in 2002. 148 The growth was driven by several factors, including improving transparency and liquidity, strong performance of most CLOs, and improving analytical capabilities of investors. The bid from vehicles for BB and higher rated CLOs has been very strong while B and lower rated paper, in addition to non-Moody’s rated tranches, is largely trading to hedge funds and prop desks. We have even seen significant activity in non-rated equity tranches. Compared to US secondary market, European CLO secondary market is still in its infancy. However, as the primary European CLO market develops further, the secondary market should evolve similarly.

148

Based on estimates from CSFB trading desk.


135

31 March 2006

Summary After comparing the leveraged loan and CLO markets of US and Europe, we summarize key observations and recommend the following: 1.

Compared to the US leveraged loan market, the European leveraged loan market is less efficient, as evidenced by its less responsive pricing system and lack of rating coverage. However, this inefficiency actually makes European CLOs more attractive, as higher liquidity premium could be passed along to CLO investors.

2.

On the other hand, the inefficiency of the European loan market also makes it more challenging to analyze European CLOs, which in turn becomes an impediment for further improvement of liquidity and transparency.

3.

We do not think there is substantial industry over-concentration in either US or European CLO collateral pools.

4.

We strongly believe that there are many opportunities in the European CLO market. However, investors need to be mindful of some of the issues such as lack of historical performance data and differences in the legal systems and bankruptcy procedures of different jurisdictions. For investors unfamiliar with the European market, we recommend investing in managed deals, leveraging a manager’s expertise.


136

31 March 2006

Chapter 3. Trust Preferred CDOs


137

31 March 2006

Diversified Bank Trust Preferred CDOs Primer149 Executive Summary The diversified trust preferred CDO (DTP CDO), one of the newest CDO products, first appeared in the CDO market in 2000. A trust preferred security qualifies as Tier 1 capital for issuing banks, but unlike common equity, it does not dilute shareholders’ ownership and also reduces tax costs for issuers. While trust preferreds have been a favored capital option for larger financial institutions, they are usually too expensive for smaller banks to issue on a stand-alone basis due to high transaction costs. By forming a consortium of regional banks to issue DTP CDOs, underlying banks benefit from the economies of scale and CDO investors enjoy regional diversification. We believe DTP CDOs offer small banks a viable way to raise Tier 1 capital. We believe that DTP CDOs will not only provide a cost-efficient capital solution for small banks, but also are likely to deliver strong returns, should collateral banks continue to sustain a low failure rate. Recent bank history demonstrates a low failure rate, sound bank fundamentals, highly detailed disclosure, rigorous regulatory oversight, and better risk management, all of which have resulted in increased public confidence in banks. Regional banks, mostly small banks, not only share those positive attributes, but also focus mainly on consumer finance and have far lower exposure to large corporations, which have been the source of recent negative headlines. Regulators remain strong proponents of industry consolidation, which reduces competition, improves efficiency and enhances profit margins. We think small banks are well positioned in the event of consolidations and can benefit from acquirers’ larger and higher credit quality franchises. DTP CDOs present institutional investors an efficient way to gain exposure to diversified pools of regional bank trust preferreds, a previously unavailable asset class with favorable risk/reward characteristics. For eligible commercial banks, even including the 1980s’ banking crisis, historical bank failure statistics imply an average triple-B default rate, better than most HY CBOs’ underlying credits, which are typically single-B rated. There is also clear evidence that DTP CDOs offer regional diversification. We think well-capitalized regional banks that have focused management teams, robust customer bases and strong deposit franchises will perform as strong credits, enhancing DTP CDOs’ performance. DTP CDOs offer long term investors seeking exposure to the banking sector attractive relative value opportunities, as DTP CDO notes offer substantial spread pick-up over other more established products such as HY CDOs, with greater credit enhancement and better collateral credit quality. In our view, primary risk factors associated with investing in DTP CDOs are uncertainties related to long-term bank credit quality, adverse collateral selection issues, the lack of diversification beyond the banking sector, longer average lives and the short history of DTP CDO performance records.

149


This section was originally written by Neil McPherson, Helen Remeza, and David Kung, October 2003.

138

31 March 2006

ORIGIN, EVOLUTION AND FUTURE Origin The FRB granted trust preferreds as Tier 1 capital in 1996

Diversified trust preferred CDOs are backed by a pool of trust preferred securities. In August 1996, the Federal Reserve Board (FRB) approved trust preferred securities as Tier 1 capital, which resulted in the trust preferred issuance boom. Trust Preferred Security A trust preferred security promises to make periodic coupon payments and has a stated maturity (debt like), generally 30 years. Unlike debt, it is required to make the coupon payment only when the issuer is financially able (equity like). Otherwise, interest may be deferred for up to five-years, and the deferred interest is paid back on a cumulative basis. A trust preferred security is a bullet bond (not an amortizer) with a 5 or 10-year non-call period. After that, it is callable, usually at par (but not always). The “equity like” nature enables a trust preferred security to be qualified as equity for regulatory capital purposes, while its “debt like” nature enables the coupon payment on the security to be taxdeductible for issuers, unlike other forms of equity. Tier 1 Capital Tier 1 capital, also known as core equity capital, is defined as the sum of common equity and perpetual preferred stock, less any ineligible intangible assets. The FRB requires Tier 1 capital to constitute at least 50% of total capital, and trust preferred and perpetual preferred stock to constitute at most 25% of Tier 1 capital. From 1996 to 1998, a flood of $32 billion trust preferreds reached the market, as highly rated financial institutions rushed to lock in the Tier 1 treated trust preferreds (Exhibit 162). The trust preferred new issue market slowed down in 1999 and 2000, as the demand from institutional investors slowed down. Most issuance since 2001 has been distributed through retail investors. As of June 2002, public trust preferred issuance reached $55 billion in total.

Exhibit 162: Public Trust Preferred Issuance by Year and Issuer Asset Size* 14

14

13

13

12

12

11

11

10

10

9

9

8

8

7

7

6

6

5

5

4

4

3

3

2

2

1

1

Issuance (billion)

15

0

Issuance (billion)

15

0 1995

1996

1997 <$200mm

1998 ($200mm, $1bn)

1999 ($1bn, $5bn)

2000 >$5bn

2001

2002 (as of June 2002)

other

Source: Credit Suisse, SNL * This excludes the trust preferreds issued through DTP CDOs.


139

31 March 2006

Using trust preferreds to raise capital is attractive for banks

To stay competitive amid the current pace of regulatory and market change, banks often need to raise more capital. Using trust preferreds to raise capital is attractive for financial institutions. Unlike common equity, though qualifying as Tier 1 capital, a trust preferred security does not dilute common equity ownership; i.e., there is no dilution on voting rights, earnings and return on equity. Also, the interest of trust preferreds is tax-deductible for the issuers, making it a “cheaper” funding source.

Three common reasons to issue trust preferreds

The proceeds of trust preferred securities are typically used for a number of purposes by the issuer, including: 1)

Buying back common stock Banks often use the trust preferred proceeds to retire the likely more “expensive” common stock, while preserving regulatory capital requirements and enhancing stock returns.

2)

Funding product or service expansions Bank customers increasingly demand better “one-stop shopping” capabilities including access to multiple products, such as mutual funds and stocks. Bettercapitalized larger banks have the upper hand when expanding into new product lines.

3)

Financing a current or pending acquisition, or creating a cash and equity reserve for future acquisitions The repeal of Glass-Steagall prompted mega-mergers of commercial banks and investment banks, allowing banks to cross-sell products, leverage economies of scale and diversify product lines.

Evolution While larger banks have benefited from using trust preferred as a cheaper capital source, regional banks had not prior to the advent of DTP CDOs. Regional banks typically are smaller and specialize in consumer and small business lending across regional localities. Since regional banks typically are small banks, we will use “regional bank” and “small bank” interchangeably. Only 2% of small banks issued trust preferreds vs. 60% for the top 50 largest banks

Historically the trust preferred utilization rate differed dramatically across banks (Exhibit 163). Excluding the trust preferreds issued through DTP CDOs and by bank count, we estimate that only 2% of smaller banks issued trust preferreds vs. 32% for larger banks (with more than $5bn in assets) vs. 60% for the largest banks (top 50 banks by asset size).

Exhibit 163: Public Bank Trust Preferred Issuance by Issuer Asset Size * 60

500 Issuance total

450

Cumulative issuer count *

400 350

40

300 250

30

200 20

Issuer Count

Total Issuance ($ billions)

50

150 100

10

50 0

0 < $200 mm

$200 mm and $1 bn

$1 bn and $5 bn

> $5 bn

Source: Credit Suisse, SNL * This excludes the trust preferreds issued through DTP CDOs.


140

31 March 2006

Cost and event risk were the key impediments

The issuance disparity between the market share of banks and trust preferreds is largely attributable to high transaction costs to issuers and investor perceptions of greater event risk and less liquidity associated with individual small banks. These factors impede small banks’ ability to access the capital markets on a stand-alone basis.

DTP CDOs present a “win-win” solution for banks and investors

DTP CDOs present a “win-win” solution for issuers and investors, because they enable the economies of scale and regional diversification needed to make a deal viable. In a pooled issue, the underwriting process is largely standardized and simplified across individual banks. For example, a standard set of documents is used for all collateral banks, and no independent road show or rating application is required for individual collateral banks. In addition, DTP CDO investors are less sensitive to individual bank’s event risk as the pool becomes more diversified. In Exhibit 164, we use two examples to illustrate how a DTP CDO reduces transaction costs.

Reduction in transaction costs is substantial via DTP CDOs

Examples Suppose a bank with $300 mm in assets and $30 mm in capital desires to raise another 10% Tier 1 capital, or $3 mm, by issuing a trust preferred security. On a stand-alone basis, the transaction costs (including underwriting, documentation, accounting, road show costs, rating fee, legal fees) can be as high as $303,000, or 10.10%. In a pooled issuance, the fee is around $128,100, or 4.27%. This amounts to a total saving of $174,900, or 5.83%, in fees. In the second example, the issue size is $20 mm, larger than in the previous example. The savings in this case is $302,400, or 1.51%. While in percentage terms the savings is lower than the previous example, in dollar terms it is still quite a meaningful saving to the trust preferred issuers.

Exhibit 164: Examples of Trust Preferred Offerings: Savings in Transaction Costs $3,000,000

$20,000,000

Pooled Issuance

% of Issuance

Pooled Issuance

% of Issuance

Pooled Issuance

% of Issuance

Pooled Issuance

% of Issuance

Placement/ Underwriters Fee

90,000

3.00%

112,500

3.75%

600,000

3.00%

750,000

3.75%

Legal Fees

30,000

1.00%

100,000

3.33%

30,000

0.15%

100,000

0.50%

-

-

20,000

0.67%

-

-

20,000

0.10%

Offering Type

Printing Accounting Trust Expense Sub Total Annual Trust Fees Grand Total First Year Savings

-

-

50,000

1.67%

-

-

50,000

0.25%

5,100

0.17%

13,500

0.45%

5,100

0.03%

13,500

0.07%

125,100

4.17%

296,000

9.87%

635,100

3.18%

933,500

4.67%

3,000

0.10%

7,000

0.23%

3,000

0.02%

7,000

0.04%

128,100

4.27%

303,000

10.10%

638,100

3.20%

940,500

4.71%

$174,900

5.83%

$302,400

1.51%


Clearly, larger banks are more likely to execute stand-alone offerings, as their issue size tends to be larger, where for them the savings over a pooled issuance is not as significant. In addition, they may prefer the higher visibility from an independent offering, and, as such, we believe the DTP CDO technology will mainly benefit smaller banks.


141

31 March 2006

Future DTP CDOs almost doubled the trust preferred issuer base

DTP CDOs have already changed the landscape of the trust preferred market. As of June 15th 2002, approximately 450 regional banks issued a total of $5.2 billion trust preferreds through DTP CDOs.150 This almost doubled the trust preferred issuer base and increased the size of the trust preferred market by about 10%.

The advent of DTP CDO levels the playing field, in our view

We believe small banks will continue to use the DTP CDO platform to issue trust preferreds, which are treated as the Tier 1 capital. The advent of DTP CDO marks a new era where improving capital adequacy via trust preferred issuance is no longer only a game that bigger banks can play. Small banks can play it well, too. This is a big step towards establishing a level playing field for all banks. In fact, by deal count, year-overyear by DTP CDO issuance increased by 100% and 50% for 2001 and 2002, respectively. In all, DTP CDOs reached $12.9bn or 29 deals as of October 2003 (Exhibit 165).

Exhibit 165: DTP CDO Issuance (2000~October 2003) $ Annual Issuance

5

35

Cumulative DTP CDOs Issued (by Deal Count)

4.5

30 25

3.5 3

Deal Count

Issuance ($ billion)

4

20

2.5

15

2 1.5

10

1 5

0.5 0

0 2000

2001

2002

Oct-03


We expect the issuance pace to slow down

That said, we expect DTP CDO issuance to slow down slightly but nevertheless be steady. The fast pace of DTP CDO issuance (since its inception in 2000), coupled with the current stringent eligibility criteria (such as the 10% pro forma Tier 1 requirement) reduces the availability of quality collateral banks.

Caveat Emptor

We caution that should regulators challenge the tax-advantaged status of trust preferreds as they did once before in 1997, there may be additional uncertainties surrounding trust preferred issuance and, as such, DTP CDOs issuance may be affected. However, we don’t foresee this in the near future, in light of the broader acceptance of trust preferreds across US and Europe, and DTP CDOs’ increasing contribution to level the playing field across the banking sector.

150

Among the 11 DTP CDOs priced as of June 15th 2002, there were a total of 350 collateral banks in seven deals, while we estimated another 100 banks were represented in the other four deals in the pipeline at that time. Chapter 3. Trust Preferred CDOs

142

31 March 2006

What’s Under the Hood: The Collateral As with other CDO products, it is important to understand the collateral - the trust preferreds in the context of DTP CDOs. We focus on three aspects: collateral default rate, bank selection criteria and surveillance. We will discuss key CDO structuring assumptions such as regional diversification and structural enhancements in the next section.

Assessing the underlying collateral Perhaps the greatest difficulty in analyzing DTP CDOs is in assessing collateral credit worthiness. Collateral banks in DTP CDOs are often too small to be rated by the three major rating agencies. Two ways to infer collateral banks’ credit quality

Rating agencies have approved two primary approaches to evaluate the collateral credit quality for DTP CDOs. These include obtaining rating estimates for each issuer, or adopting a “pooled approach”. (1) Rating Estimate For a fee, issuers can obtain estimated ratings for some or all of the individual trust preferreds in DTP CDOs. Some issuers may apply a combination of the two approaches, i.e., paying for the estimated ratings for selected banks but implementing the “pooled” approach for the rest of the collateral banks. (2) “Pooled” approach The “pooled” approach assumes that collateral banks possess a similar credit quality as the overall bank universe; i.e., collateral banks perform at the average of the overall bank universe. This is a reasonable assumption if the sample size of the pool is relatively large. DTP CDO portfolios often consist of a relatively large number of banks (i.e., ranging from 30 to 75 banks), and rating agencies have deemed the “pooled” approach applicable for these portfolios.

Outline the “pooled” approach

We outline the pooled approach as follows: 1) Historic bank intervention statistics of the overall bank universe are used to infer an average bank’s credit quality. 2) The credit quality of a trust preferred is assumed equivalent to that of the issuing bank or bank holding company (BHC); i.e., a trust preferred will default following the default of its issuing bank or BHC. The subordination nature of trust preferreds is reflected in low recovery rates. 3) 3) Bank selection criteria are applied to eliminate “weaker” banks. By choosing slightly larger banks with better capital adequacy and longer track records, we believe a positive credit selection bias is established for DTP CDOs.

Using bank “intervention” to approximate bank defaults


We based our study on FDIC’s Historical Statistics on Banking, which provides comprehensive lists of individual banks that failed or received financial assistance from the FDIC, collectively bank “interventions.” We approximate the bank default rate by the intervention rate, and then estimate bank credit quality by comparing the intervention rates to rating agencies’ benchmark corporate default rates. For example, a one-year intervention rate of between 0.2% and 0.4% indicates approximately a ‘Baa3’ rating. Appendix 1 lists Moody’s benchmark default rates.

143

31 March 2006

Intervention rate is a conservative measure for bank failure rate

The FDIC’s intervention rates are a conservative measure for bank failure rates or trust preferred default rates, for at least two reasons: 4)

All FDIC interventions were counted as defaults.151 An intervention does not always necessarily imply a bank failure or the default of banks’ obligations including trust preferreds. For example, an intervened bank might continue to operate under some arrangements, enabling it to continue to meet partial or all obligations.

5)

The intervention rate is computed on an occurrence basis, and each bank was counted individually; i.e., if one multi-bank holding company experienced five defaulting subsidiaries instead of one, five defaults were counted. To be concise, we will use “failure rate” consistently in the remaining text. A Case of Bank Intervention First City Bancorporation is an example of a failed bank that continued to partially meet its obligations, thanks in part to effective regulatory oversight. First City Bancorporation Inc., headquartered in Texas, was the fourth largest bank holding company in Texas in 1988, with $11.2 billion in assets and 60 banking subsidiaries. First City grew rapidly during the oil boom, but later suffered heavily due to the crisis in agriculture, energy, and real estate markets. In 1987, First City approached the FDIC for assistance. In 1988, the FDIC finalized the assistance plan that included injecting $500 million in new capital through a stock offering and transferring troubled assets to a separate entity. Despite the FDIC resolution, First City’s asset quality continued to deteriorate as losses mounted and the Texas economy sagged. In 1992, concerned about the weakening First City rippling through its regional economy, the FDIC stepped in once again. It created 20 bridge banks to assume deposits and some assets and liabilities from the failed banks, and then proceeded to sell all of the bridge banks in 1993. The acquiring institutions assumed all of the deposits and nearly all other bridge bank liabilities. In 1994, the FDIC announced that all creditors with valid claims were to be paid in full. In May 1995, more resolutions were announced including senior preferred shareholders would be paid over two years; junior preferred shareholders would receive between $100 million and $150 million and 35% of the new company’s common stock; common shareholders would get 15% of the new company’s stock. Had First City had trust preferreds outstanding, trust preferred holders would likely have been paid in full or would have recovered considerably as they are typically pari passu to senior preferred shareholders.

Historical bank failure rates Historic bank failure rates imply a tripleB rating

The cumulative 152 commercial bank failure rates across 31 years (1970~2002) suggest that, even including the 1980s’ banking crisis, the commercial bank universe exhibited lower failure rates than ‘Baa3’ corporates (Exhibit 166). For example, the inferred credit quality of the overall commercial bank universe is better than most HY CBO collateral quality, which is typically single-B rated.

151 Resolutions Handbook, FDIC. Types of FDIC intervention include assistant transactions, reprivatizations, re-openings, purchases or assumptions, insured deposit transfers, consignment program institution, and pay offs. Assistant transactions and pay offs are no longer used today. 152 This conclusion is based on cumulative failure rate (CFR), which is calculated by simply summing all annual failure rates. While we understand that ideally the CFR should be calculated based on a “cohort” study, the data required for the cohort is not available.


144

31 March 2006

Exhibit 166: Cumulative Bank Failure Rate and Corporate Default Rate 25%


Commercial banks

Baa3 rated corporate

Baa2 rated corporate

20%

15%

10%

5%

0% 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Source: Credit Suisse, FDIC, Moody’s.

Though the “Baa3” implied commercial bank credit quality was drawn from the overall universe, which includes larger banks, it should be applicable to small banks. This is because the failure rates were weighted by the number of banks, and over 98% of banks are small banks with asset sizes of less than $5 billion. The data excluding the 1980s’ crisis suggested a higher bank credit quality

It is also worth noting that including the 1980s crisis in the rating estimation procedure implies additional conservatism. Exhibit 167 contrasts the implied ratings from two different timeframes: 1) the 1993~2002 period (which excludes the 1980s’ banking crisis), and 2) the 1984~2002 period (which includes the 1980s’ banking crisis). The implied ratings are derived from comparing the historical annual bank failure rate to Moody’s idealized annual default rates.

Exhibit 167: Annual Failure Rates for Commercial Banks* 1993-2002 Bank Asset Size Less than $200 mm $200 mm to $500 mm $500 mm to $1 bn $1 bn to $3 bn $3 bn or More Weighted Average (WA) WA excluding <$200 mm

1984-2002

Annual Failure Rate

Implied**Credit Quality

Annual Failure Rate

Implied Credit Quality

0.10% 0.09% 0.03% 0.09% 0.00% 0.10% 0.07%

BBB BBB Higher than A A Higher than A A~BBB High BBB

0.64% 0.45% 0.44% 0.38% 0.21% 0.61% 0.41%

BBB BBB BBB BBB BBB Low BBB BBB

Source: Credit Suisse * Since the majority of collateral banks in most DTP CDOs are commercial banks and not S&Ls, we do not include S&Ls here. ** Derived from comparing to Moody’s idealized default rates

Excluding the 1980s, the data suggest a lower failure rate and, therefore, higher credit quality. As shown, the annual commercial bank failure rates imply an average credit quality anywhere between single-A and triple-B, higher than the triple-B derived from the 1984~2002 data. This trend of lower failure rates is also consistent across banks of different sizes. This suggests that the banking system in general has been far healthier in the last decade than it was in the past two decades.


145

31 March 2006

Bank selection criteria By choosing larger banks with better capital adequacy and more established track records, a positive credit selection bias is established for DTP CDOs. Some typical eligibility criteria for collateral bank inclusion are: • • •

Asset size greater than $200 mm Pro forma Tier 1 capital ratio greater than 10% 153 Chartered five-years and longer

Let’s discuss each of these criteria in turn. Size Matters Small regional and community banks typically focus on consumer and small business and stand to benefit from their in-depth local market knowledge and unequaled customer relationships. Being close to their customers allows them to be more proactive in managing problem credits, resulting in fewer loan losses. We believe that small bank fundamentals remain sound, as they continue to maintain sufficient margins, manageable asset quality and ample capital. …but the smallest banks suffered in the 1980s

That said, for some of the smallest banks, the difficult banking environment of the 1980s was challenging. These banks failed at a higher rate, largely as a result of concentrated exposures to distressed commercial real estate loans, lower net interest margins from a high interest rate environment and regional economy recessions. For example, in the 1980s, the cumulative failure rate of these smallest banks increased at a faster rate than banks of other sizes (Exhibit 168).

Exhibit 168: Cumulative Failure Rates by Bank Size (1984~2002) Cumulative Commerical Bank Failure Rate

12% 10% 8% 6% 4% 2% 0% 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Less than $200mm

$200mm ~ $500mm

$1 ~ $3bn

$3bn or more

$500mm ~ $1bn

Source: Credit Suisse, FDIC

Reducing exposure to the smallest banks leads to a pick-up in credit quality

Trimming down exposure to these smallest banks reduces the historical bank failure rate. For example, for banks with assets between $200 mm and $1 billion, the 17-year (1984~2002) cumulative default rate drops from 12% to 8%, implying a pickup in credit quality from ‘Baa3’ to ‘Baa2’, based on Moody’s idealized cumulative default rate benchmarks.

153


The 10% is “pro forma”; i.e., the calculation includes the trust preferred issuance via DTP CDOs.

146

31 March 2006

Better capitalized banks failed less often

Banks that failed had lower equity-to-asset ratios than surviving banks in the year before recessions. These recessions include the 1982 agriculture recession in the Southwest, the 1990 real estate downturn in Northeast, and the 1991 California real estate depression. By selecting banks with better capital adequacy, i.e., higher equity-to-asset capital ratios or higher capital-to-asset ratios, we believe the collateral banks in DTP CDOs are less likely to fail.154

Older is better

Newly chartered banks failed with greater frequency than pre-existing banks in the 1980s. For example, among all the institutions chartered in 1980-1990, 16.2% failed through 1994, compared with a 7.6% failure rate for banks that were already in existence on Dec. 31, 1979. This was partly attributed to an influx of new banks and mutual conversions during this period.155 Amidst the recessionary environment of the 1980s, newly chartered banks began operating at a time when inexperience was a distinct liability. Also, the newly converted mutuals reacted to the pressure of increasing earnings and meeting shareholder expectations by aggressively expanding loan portfolios to leverage initial capital positions, a strategy which eventually led to severe loan losses. If history is a guide, by selecting larger, better capitalized and more established banks, larger and better capitalized, we are likely to see fewer bank failures.

Surveillance and bank disclosure Another important aspect of DTP CDOs is deal surveillance. Underpinning good surveillance is deal/collateral transparency. We think that current bank disclosure is excellent, and this allows DTP CDO investors to obtain timely performance information. Quarterly Call Reports

For example, banks regulators require all commercial banks to file a quarterly Call Report, and it is mandatory for all S&L institutions to file a periodic Thrift Financial Report, both containing a wealth of financial information.156 Regulators also conduct periodic on-site examinations, including interviewing management, auditing financials, and revising credit indicators such as the CAMEL ratings.157 Numerous financial ratios are available in the Call Reports. We think the following aspects are important to monitor: 1)

Credit performance: often measured by non-performing assets, loan loss reserves, charge-offs, etc.

2)

Capitalization: often measured by equity to assets, Tier 1 capital ratio, total risk adjusted capital ratio, etc.

3)

Profitability: often measured by return on assets, return on equity, profit margin, etc.

4)

Funding mix: a strong retail/commercial deposit franchise is very valuable for regional banks.

154

Banks with capital-to-asset ratio greater than 10% are considered “well-capitalized” by BIS. Mutual conversions refer to mutual savings banks that converted to the stock form of ownership. See “Understanding the Experience of Converted New England Savings Banks,” Jennifer Eccles and John Keefe, FDIC Banking Review 8, no. 1 (1995). 156 Please see http://www.ffiec.gov/reports.htm 155

157


This refers to capital, assets, management, earning and liquidity.

147

31 March 2006

Other “composite” indicators

Aside from the financials, there are also some helpful “composite” bank surveillance tools, which predict or provide credit quality indications for individual banks. For example, available resources 158 might include 1) Thompson Financial’s bank ratings, and 2) the “bank failure calculator” from the Office of the Comptroller of the Currency (OCC) or FDIC’s CAMEL ratings, should they become publicly available.

Caveat Emptor

We caution that the previously discussed three bank selection criteria provide a good starting point for establishing a positive selection bias, but they are insufficient for a proper and thorough evaluation of bank credit. We advocate a careful selection of collateral banks to limit adverse selection issues.

Key ingredients for CDO structuring Having gained some insight of the collateral fundamentals, we now focus on portfolio risk and CDO structural enhancements. We believe regional diversification dampens collateral portfolio risk. We also rationalize structural assumptions such as recovery value and prepayment, and round out with a discussion of some structural enhancements, cash flow analyses and relative values.

Regional diversification

The timing and severity of bank failures differed across regions

East meets West and all places in between We believe local economics and regional legislative differences are key drivers of regional diversification. By selecting banks from various locations, regional diversity is introduced to DTP CDOs. In DTP CDOs, geographical concentration guidelines limit single bank/location/region exposure and diversify collateral pools, resulting in a better risk/return profile. Evidence of regional differences There is clear evidence of regional differences (with respect to failure timing and drivers) within the banking sector. Exhibit 169 shows that regional bank failures did not peak at the same time, and were more largely concentrated in the Southwest.

Exhibit 169: The Timing & Magnitude of Bank Failures Differed Across Regions * 250

80 70

Number of Banks

60

Midw est West East Central Southw est (right axis)

50

200

150

40 30

100

20 50 10 0

19 70 19 72 19 74 19 76 19 78 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

0

Source: Credit Suisse, FDIC *Note Southwest is represented on the right scale

158


Off-site Surveillance Systems, FDIC.

148

31 March 2006

Regional economic factors affecting failure rates varied

Regional bank failure patterns can be depicted

Clearly, factors affecting bank failures differed across localities, for example:159 •

AL/LA/OK/TX/WY: severe economic downturns related to the collapse in energy prices.

•

CA/Northeast/Southwest: real estate related downturns.

•

IO/KA/NE/OK/TX: the agricultural recession of the early 1980s.

•

CA/TX: an influx of banks chartered in the 1980s and the parallel phenomenon of mutual-to-stock conversions (MA).

•

CO/IL/KS/TX/WY: regulation prohibited branching that limited banks’ ability to diversify loan portfolios geographically and only allowed funding growth through core deposits.

•

NY/PA: the failure of a single large bank (Continental Illinois in May 1984) or a small number of relatively large banks.

We can visualize the dispersion of bank failures by color-coding and shading the states (Exhibit 170). For example, the West and Southwest region of the US experienced the worst bank failure rates, while the Central and Southeast generally had less than 5% bank failure from 1980~1994. Clearly, historical bank failures display regional patterns.

Exhibit 170: Historical Bank Failure Distribution Displayed Regional Patterns (1980~1994)* NH MA

OR

CT

WY UT

CO

CA AK

AZ

NM

KS OK

TX

LA

HI

Cumulative Bank Failure Rate (1980-1994) 0% to 2% 3% to 5% 6% to 10% 11% to 15% Over 15%

State* Count 12 13 9 6 12

Color Code

Source: Credit Suisse, FDIC * Puerto Rico and US Virgin Island are included. The Appendix 1 provides FDIC’s six regional carve-outs.

159


“The Banking Crises of the 1980s and Early 1990s: Summary and Implications”, FDIC.

149

31 March 2006

Quantify regional diversification Apply Moody’s alternative diversity score

To quantify collateral pool diversification, we implemented Moody’s alternative diversity score framework to quantify regional diversity.160 While the agencies assume five regional carve-outs, each of which is a separate industry category (just like in HY CBOs), the beauty of the alternative approach is that one does not need to arbitrarily impose “independent” regions. A key ingredient for the diversity score calculation is default correlation for all the pair-wise collateral banks.

Quantify bank failure correlation

In analyzing bank failure history across the US, we observed that bank failure rates for neighboring states tended to be more correlated than two distant states. We calculated bank failure correlations between the states and show that, in fact, states within the same region show higher failure correlation. Here, we applied the five-region carve-out used by rating agencies (Appendix 1), and implemented Moody’s alternative diversity score methodology, assuming all the trust preferreds in a DTP CDO share the same notional and default rate. Based on the FDIC’s bank failure data for the 50 states and the District of Columbia from 1966 to 2000, we construct a 51 by 51 correlation matrix using the method published in the Journal of Fixed Income (see a summary of the approach in Appendix 2).161 The data covers 13,529 banks in 1966 to 8297 banks in 2000, with 1,669 failures over 35 years across the 51 locations. For example, we estimated that two banks in the Southwest have a one-year intra-regional correlation of 2.15%, while two banks in the Southwest and the East have a one-year inter-regional correlation of 0.33%. To incorporate our view that default correlation may be higher for longer terms, i.e., longer than a one-year horizon, we stress the default correlations by five times to 10.73% and 1.63%, respectively. In our view, correlation is not exactly “time” dependent, but it may vary across economic cycles; i.e., higher correlation in market down cycles and lower correlation in bull markets. We view the five-times multiple as reasonably conservative, but, of course, one may impose one’s own assumption.

Randomly sample banks

Now, let’s look at a DTP CDO backed by 40 banks as an example. To obtain the diversity score of the pool, we randomly pick 40 banks across 51 localities, which include the 50 states and the District of Columbia. The probability of the bank belonging to a specific state is proportional to the number of institutions in that state. For example, since Texas has a total of 710 (data as of the year 2000) commercial banks whereas Alaska only has six, any randomly picked bank would be 771/6=118 times more likely to be in Texas than Alaska. Across 100 randomly selected portfolios, the average diversity score is 20 and the standard deviation is 2.0. We also re-ran the exercise using FDIC’s six-region carve-out (Appendix 3), yielding a 22 diversity score and a 2.1 standard deviation.

A conservative diversity score results in a more highly enhanced CDO

Were the random bank selection rule to mimic reality (which we would not claim is always the case) and if our default correlation assumptions are reasonable, we believe the typical 14 diversity score assignment to a well diversified 40-bank trust preferred CDO pool is fairly conservative. All else equal, a conservative diversity score assumption results in a more highly enhanced CDO structure.

160 161


“Moody’s Multi-sector CDO Rating Approach”, Moody’s, 2000. “Default Correlation and Credit Analysis”, Douglas J. Lucas, Journal of Fixed Income, March 1995.

150

31 March 2006

“Something about DTP CDO structuring” Aside from collateral default rates and regional diversification, other key structuring assumptions include collateral recovery value, interest deferral frequency and prepayment. We will round up this section by highlighting some structural enhancement features, illustrating breakeven rates/multiples and comparing relative value.

Recovery value Recovery value is a conservative “guess”

It is difficult to make any meaningful assessment of the recovery value of trust preferreds, as very few troubled cases are known to us. This is partly due to the short history of the bank trust preferred market and the healthy banking environment since the inception of the trust preferred market in 1996. Nevertheless, after some “digging,” we identified Bay View Capital Corp. (BVC) in California, as an example where the trust preferred has gone into a “deferral mode.” An example of trust peferred deferring interest BVC is an example of trust preferred deferring interest. Barring any unforeseen circumstances, we believe it is likely that BVC will make the trust preferred holders whole eventually. BVC is a bank holding company whose subsidiary is Bay View Bank, a retail and commercial bank that operates 57 branches throughout the San Francisco bay area. Originally “B1” rated by Moody’s, it issued $90 mm trust preferred in Feb. 1998. It acquired FMAC, a franchise loan operation in 1999. Mainly due to the losses incurred by its franchise loan lending, BVC had trouble maintaining healthy capital ratios, triggering the FRB’s request of suspending its 9.76% dividend payment to its trust preferred holders starting in Sept. 2000. Around that time, the bank’s rating was lowered to Caa1/D/CC by Moody’s/S&P/Fitch. Subsequently, the bank completed its restructuring and raised over $130 mm in new capital. In Oct. 2001, Moody’s upgraded BVC’s deposit and holding company’s rating; in June 2002, Moody’s and S&P put all the ratings on positive watch, citing that BVC has substantially improved its capital adequacy and is poised to return to profitable operation.

Two things point to the “conservatism” of a 10% recovery rate used by Fitch

Fitch assumes a 10% recovery rate on trust preferreds. 162 While trust preferreds may recover only a pittance in the event of failures due to their deeply subordinated nature, we believe the 10% assumption is relatively conservative, in light of the following: 1)

We use a broad bank failure or default definition; i.e., including all FDIC interventions where in some instances, common shareholders were partially paid or eventually paid in full. For example, in case study illustrated on Page9, had First City had trust preferreds outstanding, trust preferred holders would likely have been paid in full or would have recovered considerably as they are typically pari passu to senior preferred shareholders and senior to common stock.

2)

Preferred stock, which is typically junior to trust preferred, recovered 15% (median) and 22% (mean) based on Moody’s 1970~2000 corporate data (including banks). We also think with effective regulatory oversight (most other corporate sectors are not as regulated), bank paper is likely to recover more than average corporates as bank regulators are likely to proactively resolve bank failures and to restore public confidence. This further supports the “conservatism” argument.163

162 163


“Bank trust preferred securities form new asset class for CDOs”, Fitch, February 16, 2001 “Default and Recovery Rates of Corporate Bond Issuers: 2000”, Moody’s, Feb. 2001.

151

31 March 2006

Interest Deferral Trust preferred issuers have the ability to defer interest payment on trust preferred securities for up to five years, though there is little evidence about how frequently and for how long trust preferred security will defer payment. Rating agencies assume that deferral will generally go with bank failures or regulator interventions, and thus will occur at the same rate as default. Should deferred interest be paid back in full on a cumulative basis, it is not an event of default. However, we think an event of interest deferral signals likely credit troubles ahead. Diversification and excess spread mitigate deferral risk

Portfolio diversification can greatly reduce the impact of interest deferral. Simply put, for a diversified portfolio, the likelihood of multiple banks missing interest payments at the same time is not as likely. Also, compared to other CDOs, DTP CDOs have more excess spread, which can be tapped to offset interest shortfalls.

A liquidity facility is often used too

Interest deferral does not usually affect PIKable 164 mezzanine or junior CDO notes as much as non-PIKable senior CDO notes, as timely payment of interest is not a must for mezzanine or junior CDO notes. Interest deferral may affect senior noteholders’ ability to receive timely cash flows. A typical mitigant is to establish a liquidity facility at the outset and/or to fill it over time with available excess spread.

Prepayment After trust preferreds’ non-call period expires, collateral issuers may re-finance the paper because: 1) they may lock in a low fixed rate in a lower interest rate environment; 2) as issuers’ credit quality improves, they can borrow at lower rates, or 3) as the overall credit spread of trust perferreds tightens due to the likely increase in demand for regional bank paper, collateral banks can re-finance at lower rates. Collateral being called may result in positive credit events for CDO debt

Should collateral be called, static pool CDOs de-lever, likely resulting in higher enhancement to CDO debt. This is almost surely a positive credit event for CDO debt, conditional on no adverse selection in the collateral pool. Consolidation has been prevalent in the financial sector in the 1990s. In fact, the drastic 40% decline of the total number of banks outstanding from over 14,000 in 1991 to fewer than 10,000 in 2001 is a testimony of the rapid pace of M&A activity in the banking sector (Exhibit 171). Interestingly, most of the decline is attributable to the buyout of banks with less than $100 mm in assets, and more than 97% of banks being acquired since 1990 are the ones with less than $5 billion in assets.

164 “PIKable” refers to the ability of the bond to “pay-in-kind” (PIK), which means deferred interest is paid back in accrued cash interest or more bonds.


152

31 March 2006

Exhibit 171: Number of Banks by Asset Size (1991~2001) 16,000

<$100m

($100m, $300m)

($300m, $1bn)

($1bn, $3bn)

1996

1998

>$3bn

14,000

Number of Banks

12,000 10,000 8,000 6,000 4,000 2,000 0 1991

1992

1993

1994

1995

1997

1999

2000

2001


Small-cap banks – ways to play

CREDIT SUISSE’s small-cap bank equity analyst, Lauren Lieberman, argues that in a consolidating environment, small banks are in an enviable position.165 She also suggests a couple of ways for small banks and investors to play the consolidation game. For example, small banks are likely to be acquired by larger banks that seek to grow or to establish platforms for new market expansion. Also, the banks may be consolidators themselves, expanding product and distribution capabilities while eliminating back-office redundancies and improving operational efficiency.

Small banks poised to benefit from M&A

Despite a recent slowdown, we believe M&A activity will eventually resume as the pricing power (i.e., equity valuation) of banks improves. Today, small banks are well positioned in the event of consolidation and can benefit from larger and higher credit quality franchises that can obtain more attractive financing, likely resulting in trust preferred prepayment. On a cautious note, though, we think prepayment may lead to positive credit events for CDO notes, it also shortens the average life, likely resulting in lower total returns. To better understand the prepayment sensitivity, we examine how CDO cash flows vary across multiple prepayment assumptions in the next section.

Other elements For DTP CDOs’ investors, it is also important to focus on 1) structural enhancement 2) cash flow analysis, and 3) relative value comparison. We will discuss these aspects in turn. Shortening the average life of CDO debt

DTP CDOs have a long legal final (typically 30 years), and may have a longer average life if collateral call rate is slow. Two common structural enhancement features seen in long maturity CDOs are “debt turboing” and “an auction call,” both of which are intended to reduce the average life of CDO debt.

Debt turboing

Using excess spread to pay down the most expensive liability,166 usually the triple-B rated tranche in a DTP CDO, can increase the amount of future excess cash flow and shorten the triple-B average life. For tranches senior to the triple-B, credit enhancement is not affected, as only excess interest (which would have otherwise been paid to equity) is applied to pay down the triple-B, and this is conditional on the satisfaction of senior and mezzanine coverage tests. In essence, subordination is “replaced” with OC (overcollateralization). 165 166


“Small-Cap Banks – Three Ways to Play”, CSFB Regional Bank Research, June 6, 2002. This is often conditional on the satisfaction of preset equity return targets.

153

31 March 2006

Auction call

Mandatory auction call redemption is another common feature with long maturity CDOs. CDO trustees are required to conduct auction calls on a regular basis (they typically coincide with payment dates, after the 10th anniversary of the transaction). To the extent that the market value of CDO collateral pool is greater than the combined value of CDO liabilities, the trustee should liquidate the collateral pool and use the proceeds to pay down liabilities. Auction call redemptions are likely to enable an early return of principal, and, as such, shorten the average life of CDO liabilities. Barring any unexpected credit deterioration in the pool, it is likely that the auction call can be exercised. At the auction call date, two occurrences are likely to have happened: 1) the collateral would have seasoned and shortened its remaining average life, possibly being sold at tighter spreads (or higher prices); 2) the triple-B would have been partly paid down from debt turboing, reducing the amount of outstanding CDO liabilities. Both of these may result in an in-the-money auction call; i.e., the value of the collateral pool being greater than the value of the liabilities. Separately, after a CDO’s regular non-call period expires, equity holders are increasingly likely to call the deal as the CDO may have de-levered from triple-B turboing and collateral prepayment, which reduce the leverage and arbitrage. We caution that should collateral credit deteriorate, both the auction call and the regular call become less likely to be in-the-money.

Breakeven analysis

Central to CDO cash flow analyses are “breakeven” rates, which are the maximum collateral default rates before liability experiencing a first dollar loss (break in yield) or first principal loss (break in principal). Usually, the principal breakeven rate is higher than the yield breakeven rate, as the first loss of principal is a more severe scenario than the first dollar loss of cash flow. As a generic example, we look at a DTP CDO with a $500 mm capitalization, with 54% in ‘AAA’, 21% in ‘AA’, 17% in ‘triple-B’ and 8% in equity. Exhibit 172 shows the breakeven rates (see the footnotes of Exhibit 17 for modeling assumptions). For example, the triple-A can sustain a 10.0% annual collateral default rate, or 64.2%, cumulative collateral default rate before it begins to lose yield, and a15.1% annual, or 79.2% cumulative rate, before it starts to lose a dollar in principal.

Exhibit 172: Breakeven Rates for a Generic DTP CDO * Based on a break in yield

Based on a break in principal

Annual

Cumulative

Annual

Cumulative

Default Rate

Default Rate 167

Default Rate

Default Rate

AAA

10.0%

64.2%

15.1%

79.2%

AA

7.0%

50.8%

8.9%

59.8%

BBB

3.2%

27.5%

5.0%

40.0%

NA

NA

2.3%

20.3%

Class

Equity

Source: Credit Suisse * We assume 10-year bullet collateral, no deferral of interest payment on the collateral, constant default starting immediately, 10% recovery with no lag, turbo ‘BBB’. Spread assumptions: collateral L+360bp, ‘AAA’ L+80bp, ‘AA’ L+110bp, ‘BBB’ L+375bp.

Sensitivity to collateral prepayment

Another commonly used concept is “breakeven multiple,” derived from dividing breakeven rates by a base case default rate. For DTP CDOs, we adopt Fitch’s 10% 30-year trust preferred default assumption as the base case.168 Exhibit 173 shows the multiples for the breakeven rates for the first dollar loss of principal, assuming that all collateral prepays at year 10, 15 or 30. Clearly, early collateral prepayment results in a positive credit event for CDO debt, enhancing the breakeven multiples. Interestingly, the equity multiples are quite stable across different prepayment assumptions.

167

Cumulative default rate = 1 – (1- annual default rate/periodicity)^(periodicity*years of defaults). For example, for the ‘AAA’ tranche, 64.2%=1-(1-10.0%/2)^(2*10) for semi-annual pay trust preferred pools. 168 “Bank trust preferred securities form new asset class for CDOs”, Fitch, February 16, 2001. Chapter 3. Trust Preferred CDOs

154

31 March 2006

Exhibit 173: Principal Breakeven Multiples for a Generic DTP CDO 25

AAA

Principal Breakevn Multiple

AA 20

BBB Equity

15

10

5

0 10 yr

15 yr

30 yr

Average Life of Bullet Collateral Source: Credit Suisse

Conclusion The performance of DTP CDOs is directly tied to the health of the regional bank sector. In our view, the overall banking sector possesses positive attributes such as low failure rates, excellent disclosure, effective regulatory oversight and strong public confidence. Being close to their customers allows small banks to be more proactive in managing problem credits. We believe that regional banks’ fundamentals remain sound, as they continue to maintain sufficient margin, manageable asset quality and ample capital, all of which contribute to a low failure rate. Furthermore, regional banks are well poised in an environment of consolidation and pools of regional bank trust preferreds offer geographical diversification; both can be beneficial to DTP CDOs. We believe well-capitalized regional banks that have focused management teams, robust customer bases and strong deposit franchises will perform as strong credits, enhancing DTP CDOs’ performance. Nevertheless, in our view, primary risk factors associated with investing in DTP CDOs are uncertainties related to long term bank credit quality, adverse collateral selection issues, the lack of diversification beyond the banking sector, longer average lives and the short history of DTP CDO performance records. Should regional banks continue to sustain a low failure rate, we believe DTP CDOs not only provide a cost-efficient capital solution for small banks, but also are likely to deliver strong returns for CDO investors, a “win-win” for market participants. DTP CDOs offer long term investors seeking exposure to the banking sector attractive relative value opportunities, as DTP CDO notes offer substantial spread pick-up over other more established products such as HY CDOs, with greater credit enhancement and better collateral credit quality.


155

31 March 2006

Appendix 1. Rating Agency’s Five-region Carve-Out

West

Midwest

Central

Southwest

East

WA OR CA HI AK

ID MT ND MN WY SD IA NV UT CO NE KS MO AZ

WI MI IL IN OH KY TN MS AL

NM TX OK AR LA

ME NH VT MA RI CT NY NJ PA WV MD DE DC VA NC SC GA FL

* This map displays Fitch’s five regional carve-outs. Each of the regions is colored and shaded, and the states included in the regions are listed in the table. Source: Fitch, Credit Suisse


156

31 March 2006

Appendix 2. FDIC’s Six-Region Carve-Out

Northeast Region

Southeast Region

Central Region

Midwest Region

Southwest Region

West Region

Connecticut

Alabama

Illinois

Iowa

Arkansas

Alaska

Maine

Florida

Kentucky

Missouri

Oklahoma

Arizona

New Hampshire

Georgia

Ohio

North Dakota

Louisiana

Montana

Pennsylvania

Mississippi

Indiana

Kansas

Texas

California

Delaware

North Carolina

Michigan

Nebraska

New Mexico

Colorado

Maryland

South Carolina

Wisconsin

South Dakota

New Jersey

Tennessee

Rhode Island

Virginia

Massachusetts

West Virginia

New York Vermont

Minnesota

Hawaii Utah Idaho Nevada Washington Oregon Wyoming

* This map displays FDIC’s regional carve-outs. Each of the regions is colored and shaded, and the states included in the regions are listed in the table. Source: Credit Suisse


157

31 March 2006

An Introduction to Insurance Trust Preferred CDOs169 Five ITP CDOs priced so far

Since the first insurance trust preferred (ITP) CDO was brought to the market in November 2002, the number of deals backed by ITPs and surplus notes has been growing gradually, with five deals priced to date, bringing total outstanding ITP CDOs to $1.6bn (Appendix 1).

ITP CDO platform offers a “win-win”

Proceeds from insurance trust preferreds and surplus notes issuance are often used for financing acquisitions, funding company growth or demutualization, and for replacing capital reduction from investment losses, etc.170 Just like pooled bank deals, we believe ITP CDOs offer a more level playing field for smaller insurers (vs. larger ones), as the ITP CDO platform allows smaller insurers to achieve lower financing costs. For example, trust preferreds and surplus notes remain qualified for partial equity credit for rating agency treatment, while other forms of debt such as bonds and loans do not. Further, the application of CDO technology creates a “win-win” in that it also provides an opportunity for mainstream fixed income investors to buy pooled insurance trust preferred risk with product line and geographic diversity at an attractive spread. To illustrate how an ITP CDO works, we’ll focus on: •

Collateral selection;

•

Portfolio diversification;

•

Collateral credit performance;

•

Regulation and disclosure;

•

The insurance sector outlook; and,

•

Some unique structural enhancement features for ITP CDOs.

Collateral About a 7:3 split between P&C and L&H insurers Two main types of collateral: trust preferreds and surplus notes

Collateral type On average, outstanding ITP CDOs usually have about 35 insurers participating in the program, with 70% in the property & casualty (P&C) sector and the balance in life & health (L&H) companies (Exhibit 174) and others, roughly proportional to the market share (by company count) breakdown between P&C and L&H companies. ITP CDOs typically contain two types of collateral: trust preferreds and surplus notes. Trust preferreds are issued by the holding company of a publicly owned company (“stock company”). For an overview of the trust preferred issuance structure, please see Appendix 2. Surplus notes are typically issued by a mutual company’s operating entity. A mutual company is owned by policyholders rather than by shareholders. The largest US P&C insurer, State Farm, is a mutual company. In 2001, mutual P&C insurers represented 33% of industry surplus171, 27% of assets, and 32% of underwritings. Since 1978, the number of mutuals has dropped below that of stock companies and remained fewer, partly because of the difficulty in raising capital and the absence of stock-related incentives for management.172

169 This report was originally written by Neil McPherson, Helen Remeza, David Kung and Eric Zhai, December 3, 2003. 170 Demutualization refers to the event in which a mutual insurer is restructured as a stock company, which is then owned by shareholders rather than policyholders. 171 Surplus, or policyholders’ surplus, refers to the sum remaining after all liabilities are deducted from all assets. Essentially, this is an insurer’s statutory net worth. Surplus, in addition to loss reserves, provides financial protection to policyholders in the event that a company suffers an unexpected or catastrophic loss. 172 2003 Property-casualty insurance primer – 18th edition, February 2003, CSFB P&C insurance equity research.


158

31 March 2006

So far, about 62% of the assets in ITP CDOs have been invested in trust preferred securities issued by insurance holding companies, while 33% are invested in surplus notes issued by mutual insurance operating companies (Exhibit 174).

Exhibit 174: Select collateral statistics for outstanding ITP CDOs # Financial Institutions Property & Casualty Other (Incl. Life & Health) Trust Preferred Surplus Note

Average

Range

35 72% 27% 62% 33%

(31, 40) (67%, 76%) (19%, 33%) (51%, 70%) (30%, 37%)

Source: Credit Suisse, Fitch.

A comparison of the two main types of securities found in ITP CDOs is illustrated below (Exhibit 175).

Exhibit 175: A comparison between trust preferred securities and surplus notes Trust Preferred Key Characteristics

Key attractions for insurers

Market size

* 30-yr maturity* Subordinated to other debt but senior to common and preferred equity * Regulators have oversight of the overall health of an insurer, for which they may exercise their discretion to suspend dividends to the holding company, which can result in deferring dividend payments to trust preferred holders * Unpaid dividends accrue until paid * No voting or equity conversion rights * Dividends paid are tax deductible to issuer * Rating agencies give some equity credit for trust preferreds, resulting in a lower leverage ratio for the insurance company

As of 2003Q2, SNL data source indicates there are about $15bn of trust preferred securities across 228 insurers outstanding in US

Surplus Note * 30-yr maturity, but possibly shorter * Subordinated to secured debt and policy holders * Interest and principal payments subject to prior state regulatory approval (in the issuer’s domicile) * No voting or equity conversion rights

* Interest is tax deductible to issuer * Mutuals can issue surplus notes, being treated as equity capital by regulators, without having to demutualize * Surplus notes generally go to increase issuer surplus, resulting in a lower leverage ratio for the insurance company * Rating agencies give some equity credit for surplus notes, resulting in a lower leverage ratio Since 1993 and as of Dec. 2002, $19.7bn surplus notes were issued across 337 insurance companies, including $6.1bn in the P&C sector and $13.6bn in the L&H sector


Small insurers, a large part of the insurance universe, benefit most from ITP CDOs

Collateral Selection Similar to the banking sector, in which over 95% of banks have assets less than $10bn, most companies in the insurance industry are relatively small. In 2003, there were 2,671 P&C and 1,164 L&H companies in the U.S. Most are very small, i.e., 88% (by company count) with assets less than $1bn and 98% with assets less than $10bn. These smaller insurers are taking advantage of the CDO platform, i.e., gaining more efficient funding. This greater funding efficiency (and better access to the capital market) results from a reduced issuance cost due to ITP CDO diversification, documentation standardization and reduced road show requirements. To provide some color on the underlying insurance companies in ITP CDOs, we list some key insurer eligibility criteria as described by Fitch (Exhibit 176), i.e., insurers satisfying the criteria shown below can participate in the pooled (CDO) program. Typically an eligible pool can achieve an average Single-B rating equivalent by the rating agencies. While having a snapshot of these indicators is helpful, we think investors should also keep a close watch on evolving trends, which may shed additional light on creditworthiness.


159

31 March 2006

Exhibit 176: Fitch’s key eligibility criteria for insurers participating ITP CDO programs P&C Companies

Life Companies

1. Minimum five-year operating history

Same

2. No significant businesses other than the core P&C insurance operation 3. Minimum of $30 million of statutory capital 4. Minimum NAIC risk-based capital (RBC) ratio of 150% 5. Maximum NPW/PHS of 2.5X 6. Maximum net leverage of 5.0X 7. Reinsurance Recoverables /PHS < 100% 8. Minimum 5-year return on surplus of 5% 9. Maximum risky assets to adjusted surplus ratio of 100% 10. Trust preferred capital represents less than 25% of total GAAP capital structure 11. Maximum adjusted leverage ratio of 45% on a GAAP basis

No significant businesses other than the core life insurance operation Same Minimum NAIC risk-based capital ratio of 250% (under the new risk based capital ratio formula) NA NA NA Same Same Same Same

Source: Fitch, Credit Suisse

It is also common that the rating agencies may choose to obtain a "credit estimate" for each underlying insurer in ITP CDOs. This score is typically assigned by the agencies’ insurance group and/or is derived from a credit-scoring model. Fitch suggests that it will evaluate insurers using a model that considers factors such as capital/reserve adequacy, profitability, investment allocation and risks, operating/financial leverage, and credit exposures to re-insurers.

Portfolio Diversification As in all CDOs, collateral risk diversification results in more stable portfolio defaults/losses, benefiting ITP CDO debt performance. Several aspects of ITP CDO collateral diversification include diversification across sector, product line and geographic region. Insurance sector classification Based on the type of risk insured, broadly speaking, there are two types of insurance companies: • Property/Casualty (P&C); and, • Life/Health (L&H). Aside from the above, reinsurers and alternative insurers173 also offer risk coverage. Product line classification P&C insurers Insurance companies typically offer multiple product line coverage. For example, P&C companies typically offer: • Personal lines: auto, homeowners’ multiple peril174; and, • Commercial lines: workers’ compensation, commercial multi peril, property reinsurance, directors’ & officers’ liability, etc. In 2001, total net premiums written for the P&C insurance industry were $329bn, 49.6% and 46.1% for personal and commercial lines, respectively, according to A. M. Best.

173 Alternative insurance is often offered by industry or labor groups rather than an insurance company. In the alternative risk transfer market, the insured typically assumes a substantial amount of its own loss exposure, primarily the predictable, frequent losses, and transfers the less predictable, excess risks to insurers and reinsurers. In most cases, the client purchases unbundled services that include risk management, loss and claims control, and investment management. The benefits of these alternatives include lower and more stable insurance costs, greater control over the client’s risk management, and an increased emphasis within the client's organization on loss prevention and control. 174 Commercial Multi-Peril provides a wide range of coverage for commercial establishments, including property coverage.


160

31 March 2006

L&H insurers

Life companies typically offer the following type of policies: • Whole life: universal, variable and universal variable life; • Term insurance; • Group life, accident & health insurance; • Annuity; • Other policies, such as credit insurance175 and industrial life insurance.176 Health insurers cover disability and supplemental health, etc.

Product line diversification sheds additional insight

It is important to examine ITP CDO pools by product lines, as companies within the same broad sector (i.e., P&C, L&H) may have very different products. To illustrate this, we use an example in a CREDIT SUISSE insurance credit research publication entitled, “Hurricane Isabel: Could Create Some Buying Opportunities“.177 Exhibit 177 provides an example of some P&C companies and their product line distribution by premium collection. For instance, while the homeowners’ insurance exposure across 30 selected companies in this example ranges from 0% to 24%, auto exposure extends from 9% to 90%. This suggests that insurance companies operating in broad industry categories may have a substantially difference product mix (or portfolio risk). Thus, examining an ITP CDO portfolio diversification only by broad insurance sector classification (such as P&C or L&H) may not offer enough detail. Aggregating premium collection across underlying issuers by product line can shed additional insight. Typically, sector and product line concentration are monitored and controlled, as rating agencies often impose issuer, sector and product line concentration limits.

175 Term life insurance designed to cover the repayment of a loan, installment purchase, or other financial obligation. 176 Also know as home service life insurance, the premium is collected by the salesperson at the home of the insured on a weekly or monthly basis. 177 “Hurricane Isabel: Could Create Some Buying Opportunities”, CSFB, September 15, 2003.


161

31 March 2006

Exhibit 177: Insurer’s product focus differs P&C Companies Focused in States in Path of Hurricane Isabel, with At Least 20% of Premiums in Auto, Homeowners’ Commercial Multi-Peril and Property Reinsurance Lines. Sorted by percentage of total net 2002 premiums written in New York, New Jersey, North Carolina, Virginia, Pennsylvania and Connecticut. Figures in $millions unless indicated otherwise

P&C Group 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Selective Insurance Group Inc PMA Capital Insurance Group Erie Insurance Group Harleysville Insurance White Mountains Insurance Grp Amica Mutual Group Travelers PC Pool Ohio Casualty Group Chubb Group of Insurance Cos Berkshire Hathaway Ins Group [1] Nationwide Group MetLife Auto & Home Group [1] Kemper Insurance Companies Liberty Mutual Insurance Cos Allstate Insurance Group [1] Hartford Insurance Group [1] Royal & SunAlliance USA GMAC Insurance Group Fairfax Financial (US) Group Allmerica Prop & Casualty Cos [1] Great American P&C Ins Group American International Grp Inc [1] USAA Group Progressive Insurance Group Allianz of America, Inc Horace Mann Insurance Group [1] State Farm Group [1] Cincinnati Insurance Cos [1] Westfield Group Sentry Insurance Group

12 mo. 2002 Total NPW 1,075.1 1,054.2 3,330.0 1,126.3 3,112.4 1,156.2 11,882.3 1,448.6 7,811.3 15,203.8 11,740.5 2,876.5 2,089.6 10,573.6 23,342.1 8,394.7 3,123.1 2,634.5 3,003.0 2,269.2 2,386.8 21,045.8 6,967.0 9,455.6 2,631.9 523.1 42,747.4 2,612.7 1,252.0 1,552.9

Auto

Homeowners

Comm'l MultiPeril [2]

Property Reins

Total

Total NPW Focus in Isabel States

21% 9% 52% 22% 36% 73% 27% 26% 8% 46% 56% 74% 14% 34% 71% 29% 21% 56% 9% 51% 36% 19% 75% 90% 18% 72% 67% 21% 31% 46%

3% 2% 15% 9% 9% 22% 12% 10% 14% 0% 15% 22% 5% 8% 23% 8% 4% 0% 2% 16% 0% 1% 21% 0% 17% 24% 22% 9% 12% 2%

4% 5% 11% 28% 11% 0% 17% 20% 17% 3% 9% 0% 10% 8% 2% 18% 11% 0% 7% 15% 6% 2% 0% 0% 23% 0% 2% 26% 19% 1%

0% 10% 4% 0% 1% 0% 0% 0% 1% 11% 0% 0% 0% 1% 0% 3% 0% 1% 6% 0% 0% 1% 0% 0% 0% 0% 0% 0% 2% 0%

27% 27% 83% 59% 57% 95% 57% 56% 40% 60% 81% 96% 28% 51% 96% 57% 37% 58% 25% 81% 42% 22% 96% 91% 58% 96% 92% 55% 64% 49%

73.5% 69.3% 66.1% 61.7% 36.5% 34.4% 33.3% 32.5% 31.9% 30.5% 30.2% 29.0% 28.9% 27.3% 25.6% 25.5% 25.1% 24.9% 24.3% 21.5% 20.5% 20.1% 20.0% 19.8% 19.8% 16.2% 14.6% 14.0% 13.2% 12.0%

1) These companies all have sizable life insurance operations, premiums for which are not included in the above table. Life premiums as a percent of consolidated company premium are the following – Berkshire Hathaway Inc. (3%), MetLife (91%), Allstate Corp. (9%), Allmerica Financial Corp. (15%), American International Group (52%), Horace Mann Group (15%), Cincinnati Insurance Group (3%), State Farm Group (7%). 2) Commercial Multi-Peril provides a wide range of coverage for commercial establishments, including property coverage. Source: Company Reports, AM Best, Credit Suisse

Smaller insurers are often niche players…

Smaller companies such as Midland Company (with market capitalization of $395mm as of Sept. 2003) have a very different product profile than larger insurers (Exhibit 178). For example, Midland specializes in writing physical damage insurance and related coverage on manufactured housing, homeowners, lower valued homes, dwelling fire, mortgage fire, collateral protection, watercraft and related insurance, segments on which larger insurers may not focus.178 For pooled deals, small insurers’ niche product focus offers diversification. Of course, smaller companies should be aware of excessive expansion in a competitive market, i.e., they should not write too much business that appears profitable in the short term when the long-term prospect is questionable.

178


“Blame it on Isabel… and motor sports,” CSFB, P&C insurance equity research, September 2003.

162

31 March 2006

Exhibit 178. Small insurers such as Midland have a different product profile than larger ones Smaller players such as Midland Company (with market capitalization of $395mm as of Sept. 2003) have a very different product profile than larger insurers such as Allstate. The gross premiums written in 2002 (totaled $588 mm) can be broken down below respectively. While Midland (top chart) has larger exposure in manufactured homes and motor sport but very little in auto, larger P&C insurers provide more risk coverage to auto (about 38% as shown in the bottom chart).179

Midland Comapny Watercraft Commercial Long Haul Truck Property 3% 2% Mortgage Fire 3% 3%

Other 3%

Recreational Vehicle 3%

Collateral Protection 4% Credit Life & Related 8%

Motor Sport 11%

Site Built Dwelling 13%

Manufactured Homes 47%

Larger P&C Reinsurance 4%

Other 15%

Private passenger auto liability 22%

Accident & health 5% Commercial auto 5%

Liability other than auto 7%

Commercial multiple peril 7%

Workers' compensation 8%

Homeowners Private passenger auto physical 11% damage 16%

Source: Company Reports, Credit Suisse, S&P.

179 This is based on “Industry surveys – P&C Insurance,” S&P, July 17, 2003. The market share by product line is based on net premiums written and averaging over the A. M. Best P&C coverage universe. We think this is a reasonable proxy for larger insurers’ product profile, as the larger companies dominate the overall market.


163

31 March 2006

Insurer failure rates differ across states…

Geographical Diversification There is some evidence that average insurer failure rates differ across the state of domicile.180 While Wyoming, Louisiana, Montana, Puerto Rico and Florida experienced the highest insolvency rate, Connecticut, Idaho, Kansas, Mississippi, New Hampshire and North Dakota and the District of Columbia did not have any insolvency over the period studied by A. M. Best (1969-1990).

…Partly driven by the differences in state regulation

To some extent, the difference in insolvency rates is probably related to the effectiveness of state regulation, including licensing, regulatory and capital requirements, and the ratesetting mechanism, which vary among the states. Different state requirements make it easier to obtain licenses in some states than others.

There are two basic types of rate-setting regulation

Further, premium rates are regulated by individual states. There are two basic types of rate-setting regulation: use and file (competitive rate), 181 and prior approval (by state regulator). In jurisdictions where use and file is the law, rates are set on a competitive basis and are subject to later audit. In the US, states where prior approval is the law include California and the most heavily populated states in the Northeast, totaling 63.2% by population today (Exhibit 179).182

Exhibit 179: Rate regulation by state Competitive Rate

1.8% 0.9%

Michigan Minnesota

Colorado

1.5%

Missouri

2.0%

Wisconsin

Connecticut Idaho

1.2% 0.5%

Montana Nevada

0.3% 0.7%

Wyoming

Illinois Indiana

4.4% 2.2%

Ohio Oregon

Iowa Kentucky

1.1% 1.5%

Rhode Island South Dakota

Maryland 1.9% Utah % of Total US Population

3.6% 1.8%

Prior Approval

Arizona Arkansas

Vermont Virginia

0.2% 2.5%

Alabama Alaska

1.6% 0.2%

1.9%

California

12.2%

Mississippi

1.0%

South Carolina

1.4%

0.2%

Delaware Dist. of Columbia

0.3% 0.2%

Nebraska New Hampshire

0.6% 0.4%

Tennessee Texas

2.0% 7.4%

4.1% 1.2%

Florida Georgia

5.5% 2.9%

New Jersey New Mexico

3.0% 0.6%

Washington West Virginia

2.1% 0.7%

0.4% 0.3%

Hawaii Kansas

0.4% 1.0%

New York North Carolina

6.7% 2.8%

Louisiana

1.6%

North Dakota

0.2%

0.8%

Maine Massachusetts

0.5% 2.3%

Oklahoma Pennsylvania

36.8%

1.2% 4.4%

63.2%

The largest states in the United States from a population standpoint require prior approval.

Source: Insurance Service Office (ISO)

Combining small insurers domiciled in various states enhances CDO diversification

Because insurer performance can differ across states, combining insurance risk exposures in various states likely enhances CDO diversification. In addition, smaller insurers tend to be more localized in their risk coverage, partly due to their regional focus/knowledge and their ability to fill the gaps for larger insurers. For example, the largest P&C company in the US, State Farm, recently reduced voluntarily its insurance sales in certain states, offering opportunities for regional insurers (Exhibit 180).183

180

A. M. Best’s P&C Insolvency Study 1969~1990. Essentially, an insurer establishes and uses its rate prior to filing them with a state regulator who may then challenge and ultimately change them. 182 “Allstate corporate,” April 14 2003, P&C Insurance, Equity Research, CSFB. 183 2003 Property-casualty insurance primer – 18th edition, Page 123, CSFB, P&C insurance equity research, February 2003. 181


164

31 March 2006

Exhibit 180. Voluntary reduction in sales from larger insurers offers opportunities for smaller regional companies After a tough 2001, when State Farm (the largest US insurer) lost $75 on every car insured after tax and investment income, it took some corrective actions. These include higher rates and a moratorium (suspension of new sales) or limit on new homeowners’ sales in 26 states and on personal auto sales in 3 states (see the chart below). The largest of these states include Texas, California, and Florida, which collectively represent an estimated 28% of the total U.S. homeowners’ insurance market and 25% of the personal auto insurance market. In addition, the company announced a restructuring effort in August 2001 designed to consolidate its operations into 13 regions from 25. While these measures are designed to improve State Farm's profitability, these limitations on insurance sales provide opportunities for other players including smaller regional insurers.

WASHINGTON MONTANA MONTANA OREGON OREGON

MAINE

NORTH NORTHDAKOTA DAKOTA MINNESOTA MINNESOTA VT

IDAHO IDAHO

WYOMING

SOUTH SOUTH DAKOTA DAKOTA

WISCONSIN WISCONSIN

NEBRASKA NEBRASKA

NEVADA

IOWA IOWA

PAYLVANIA PENNS ILLINOIS ILLINOIS

UTAH UTAH

OHIO OHIO

KANSAS

NEW NEWMEXICO MEXICO

OKLAHOMA

MISSOURI

TENNESSEE TENNESSEE

ARKANSAS ARKANSAS

ALASKA TEXAS

Limits on Sales - Homeowners

Limits on Sales – Auto & Homeowners

RI NJ DE MD

VIRGINIA

NO. CAROLINA SO. CAROLINA

ALABAMA

GEORGIA

LA FL

HAWAII

Moratorium – Auto & Homeowners

MA CT

KENTUCKY

MISSOURI

MS

Moratorium - Homeowners

DC WV

KANSAS ARIZONA ARIZONA

IN IN

COLORADO COLORADO

CALIFORNIA

NEW YORK

MI N MICHIGA

WYOMING

NEVADA

NH

Does Not Operate

State Farm insures roughly one over every five cars and homes in the United States.

Source: Credit Suisse,


165

31 March 2006

Insurance Company Default Studies Data universe Data presented in this paper are mainly based on A.M. Best’s data. A.M. Best (www.ambest.com), located in New Jersey, has been the leading tracker of the insurance industry for over 92 years. It covers over 3,835 P&C and L&H companies (including 2,671 P&C companies), which represent 99% of the domestic industry’s assets and premium volume.

A likely source of over-counting

There are some discrepancies between industry convention and the rating agencies’ definition of default. For example, insurance industry convention for P&C failures is insolvency and for L&H the standard is financial impairment, while rating agencies’ definition of debt default is often payment impairment. We think defaults as defined by the insurance industry (used in A.M. Best’s insolvency and impairment study) can lead to a conservative measure for trust preferred and surplus note defaults, resulting in a higher number of defaults than rating agency definitions may have indicated. This likely over-counting is due to the fact while insolvencies or financial failures are recorded for individual companies and/or multiple times (if a company failed, reestablished itself and failed again), trust preferreds are issued at the holding company level. For example, Central National Insurance Co. of Omaha and of Puerto Rico failed in 1989 and 1991 (but the holding company survived), respectively, and were counted as two events by A.M. Best, while Commercial Standard Insurance Co. failed twice, in 1981 and 1985, which were recorded as two insolvencies by A.M. Best. 184 Multiple company insolvencies or financial failures under the same holding company thus could overstate the total number of trust preferred defaults.185 Historical failure statistics Having noted the differences between rating agency defaults and industry conventions, for simplicity, we address insolvency and financial impairment generically as "default". Exhibit 181 summarizes insurers’ historical default experiences.

Exhibit 181: Summary of historical insurer default experiences P&C L&H

Annual Average Default Rate 0.94% across 22 years, indicating a Ba1 credit* 0.48% across 26 years, indicating a low Baa3 credit*

Standard Deviation 0.55% 0.45%

Time frame 1981~2002 1976~2001

* Indicated ratings are based on Moody’s idealized annual default rates Source: A.M. Best, S&P and Credit Suisse

We offer the caveat that ideally these statistics should be re-evaluated, tailored to smaller insurers, the main participants of ITP CDO programs, and adjusted to the portfolio makeup of stock companies vs. mutuals.186 However, this task is formidable at this time due to limited data availability.

184

“Excess and surplus 2003,” special report, September 2003, A.M. Best. In addition, theoretically, insolvency is a much broader concept than payment impairment. For the purpose of A. M. Best’s study, the insolvency count includes any U.S. domiciled insurance company against which action has been taken by the insurance department in its state of domicile for reasons of financial impairment. State actions include administrative orders, supervision, receivership, conservatorship, liquidation or another form of action, which restricts or limits an insurance company’s freedom to conduct business. This is likely to be more extensive than payment impairment, which may result in the over-counting. 186 A. M. Best noted a significant greater insolvency rate for stock companies than mutuals in its study covering the 1969~1990 period. 185


166

31 March 2006

P&C companies P&C insolvency experiences can be summarized as follows: • The annual P&C company insolvency rate averaged 0.94% (with a standard deviation of 0.55%) across the 22 years. Roughly, this implies a 9.4% (=0.94%*10) 10-year default rate, assuming a constant annual default rate of 0.94%, which implies a high Double-B rating based on Moody’s corporate default rate. • Companies rated in the C and C- categories by A. M. Best (Appendix 2 illustrates A. M. Best's rating scale) experienced the highest insolvency rate three years later (Exhibit 182). Eliminating companies with low ratings, i.e., based on the eligibility criteria discussed before, from an ITP CDO pool should lead to more favorable default experience.

Exhibit 182: P/C company insolvency rates (1981 ~ 2002) 2.5 2.05

Rate of Insolvency

2

1.8

1.8

1.44

1.4

1.5

1.33

1.27

1.02 1.03

1

0.9

1

1.2

0.83

0.79 0.6

0.58

0.5

0.3 0.27

0.37 0.21

0.28

0.23

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

1984

1983

1982

1981

0

Source: A. M. Best

Exhibit 183: ‘C’ rated insurers experienced the highest insolvency/impairment rates three years later 3 2.61

Rate of Insolvency

2.5 2

1.72 1.45

1.5

1.25 0.93

0.86

1 0.57 0.5

0

0.02 A++/A+

A/A-

B++/B+

B/B-

C++/C+

C/C-

D/E

NR/NF

Source: A. M. Best


167

31 March 2006

P&C failures – a historical prospective Over the past 10 years, the number of insolvencies has peaks and troughs. After reaching a peak in 1992, when Hurricane Andrew hit local Florida property insurers, the failure rate decreased and has remained at much lower levels for years. In the late 1990s, reinsurers were under significant pressure from shareholders to expand market share to generate significant top-line growth. Due to a limited number of viable acquisition candidates in the reinsurance market, they began to offer cheap reinsurance protection to stimulate growth. Some weaker primary insurers benefited from this, taking advantage of lower reinsurance costs, and were able to remain in the market by passing on substantial losses to reinsurers. Subsequently, reinsurers raised their rates, leading to a series of insolvencies among insurers. The late 1990s was analogous to the mid 1980s, when primary carriers engaged in cash flow underwriting (a strategy which justifies pricecutting when the additional cash flow from increased market share provides investment income which offsets higher underwriting losses), which led to insolvencies. Over the past 10 years, insolvencies were predominantly driven by deficient loss reserves (51%), followed by rapid growth (10%), the strain of discontinued operations (9%), catastrophic losses (8%), the impairment of an affiliate (8%) and allegations of fraud (5%). Examples of defaults in trust preferreds or surplus notes


While there were a number of P&C insolvencies (i.e., 18, 7, 30, 30 and 38 insolvencies for 1998 to 2002, respectively), insurance debt and trust preferred defaults are somewhat harder to find, which may be partly due to the fact that not all insurers have issued debt, preferreds or surplus notes. However, to provide some color about distressed insurers/reinsurers and the reasons behind defaults, we describe one incident announced in November 2003, and three recent and rather significant insolvencies that resulted in debt defaults. Reasons for these failures include under-pricing, deficient reserves, aggressive underwriting and over-expansion.

168

31 March 2006

2003 PMA Capital Corp (PMACC), the holding company, has two major arms, the PMA Re and the PMA Insurance Group (PMAIG). PMA Re was established in 1970 to provide property, casualty and specialty reinsurance. The PMAIG was established in 1915 to provide specialized insurance in worker's compensation and disability insurance products and services in the eastern US. PMA Capital Corp issued $32.5 million trust preferred securities in June 2003 and $57.5 million in senior notes to help improve financial strength and flexibility, some of which were used to pay down the more restrictive credit facility. As of November 2003, the company has $4.5 billion in assets and $617 million in equity, along with $186 million in long-term debt. In November, the company took a $150 million pre-tax reserve charge that stemmed from the losses in its troubled reinsurance operations for the accident years 1997-2000. Following the reserve charge, PMACC has been looking into various alternatives to restructure the reinsurance arm. Some of the options include run-off, which means no new policies would be underwritten and existing policies would terminate through attrition, or to sell off renewal rights to another insurance company. Currently, PMACC has reached tentative agreements with Imagine to sell renewal rights to PMA Re's existing policyholders. The news of reserve charges also prompted lawsuit filings on behalf of the debt holders, accusing the company of providing inaccurate income information and maintaining inadequate reserves. Following the announcement and the suspension of common stock dividends, PMA's equity price dropped 62%. Moody’s downgraded PMA Capital Corp’s senior unsecured debt to Ba3 from Ba1, and preferred stock to B2 from Ba2, while Fitch downgraded the senior unsecured debt to B+ from BB+. Moody's also expressed concerns over PMACC's organizational structure that may result in regulatory constraints for PMACC to receive dividend payments from PMAIG, which may impair PMACC's ability to service it debt obligations, i.e., including likely reducing the chance for timely payments to the trust preferred holders. 2003 Lumbermen’s Mutual Casualty Co. is in default on $700 mm of surplus notes. Lumbermen’s primarily became distressed from its significant concentration in California workers' compensation business, a market that was severely under-priced from 1996-2000. Lumbermen’s also fell victim to the aggressive tort environment for asbestos. In 2001 and 2002, Lumbermen’s took very significant charges for workers' comp and asbestos. In April 2003, the California insurance regulator ordered the company to stop paying on the surplus notes given that the company had a deficit to pay claims on its written policies.

2003 A large reinsurer, Trenwick Group, defaulted on about $250 mm of senior debt and preferred securities. Trenwick had about $76 million of debt, $68 million of trust preferred securities, $75 million of preferred stock and the balance in convertible preferreds. Trenwick had very aggressively written business since 1995, and also did not properly price and reserve for the policies. Consequently, it became distressed when it incurred a very significant reserve charge (unrealized loss) in 2002.


169

31 March 2006

L&H companies We summarize L&H insurers’ historical financial impairment experiences as follows: • Exhibit 184 suggests that the percentage of financially impaired companies (FICs) dropped considerably throughout the 1990s, after peaking in 1991, as a strong economy, low interest rates, and robust stock and real estate markets helped to strengthen insurers. • The average annual insolvency rate for L&H companies was 0.48% (with a standard deviation of 0.45%) across the 26 years (Exhibit 184). Roughly, this implies a 4.8% (=0.48%*10) 10-year default rate, assuming a constant annual default rate of 0.48%, which implies a low Triple-B rating, according to Moody’s corporate default rate. • The number of financial-impaired insurers has averaged less than four per year since 1995 (excluding 1999),187 and most were relatively small, less efficient health insurers, which had inadequately priced their products or could not adapt to rapidly changing market conditions. Key contributors of financial impairments include inadequate pricing (24%), affiliate problems (22%) and rapid growth (16%) (Exhibit 185). • Impairments by product line indicate health insurance-related companies suffered the most (46%), followed by life insurers (39%) and annuity writers (15%). Difficult competitive and regulatory conditions continue today for health insurers. Consequently, there has been considerable consolidation among health carriers, as those that could not compete effectively have either been acquired, chosen other lines of business, or have shut their doors.

Exhibit 184: L&H financial impairment rates (1976~2001) 2.00%

1.8 6 %

1.80%

% L&H Imp airments

1.60% 1.40%

1.35 % 1.2 3 %

1.20% 1.00%

0 .8 8 %

0.80%

0 .68 %

0.4 4 %

0.4 2 %

0.40%

0 .28 % 0 .14 %

0 .2 7%0 .29 %

0 .2 9% 0 .20 % 0.19 % 0 .19%

0 .17%

0 .2 1%

0 .0 7%

0.3 1%

0 .13 % 0 .0 7%

0 .0 0 %

19 76 19 7 19 7 78 19 79 19 80 19 81 19 8 19 2 83 19 84 19 8 19 5 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 9 19 5 96 19 97 19 9 19 8 99 20 00 20 01

0.00%

0 .7 6%

0 .6 0 %

0.60%

0.20%

0 .77 % 0 .72 %

Source: AEGON IMD Structured Products Research, S&P, Fitch.

187

The impairments of 1999 were an anomaly. In spring of 1999, regulators were beginning to uncover the alleged theft of funds from the seven companies controlled by the fictitious Thunor Trust. According to A.M. Best, of the 21 documented FICs that year, eight were tied to the activities of Martin Frankel, who allegedly absconded with over $200mm of assets from these insurers and fled the country. These companies are either currently under regulatory supervision or are in the process of being liquidated. While alleged fraud has occurred from time to time, the size of the alleged theft and the incredible chain of events surrounding Martin Frankel were extraordinary. Chapter 3. Trust Preferred CDOs

170

31 March 2006

Exhibit 185: Primary causes for L&H financial impairments (1976~2000) 24%

25%

22%

20% 16%

15%

15%

10%

10%

6% 5%

4%

3%

fa il u re ins ur er

M is c

bu si ne in ch g

S

ig ni fic

an t

Re

ss

ud f ra ge d

ed rs ta t

Al le

as se ts

th gr ow O ve

R ap id

ms pr ob le

Af f il ia te

In ad eq

pr ic

in g

0%

Source: A. M. Best, Credit Suisse

Regulation and Disclosure Regulation of the insurance industry is done on a stateby-state basis

Regulation of the insurance industry is centered at the state level. There are about 50 state insurance departments (and one for the District of Columbia) that regulate industry activities. State regulators serve three primary functions. First, they monitor the financial condition and claims-paying ability of companies operating in their state. Second, they serve as consumer “watchdogs,” ensuring that policyholders aren’t overcharged or discriminated against. Finally, regulators try to ensure that essential risk coverage is readily available.

The NAIC coordinates the activities among states

The National Association of Insurance Commissioners (NAIC) coordinates the activities among the individual states. The NAIC proposed a bill, which later became known as the McCarran-Ferguson Act (enacted March 9, 1945), which laid the framework for insurance regulation. It declared the following: • It was the intent of Congress that state regulation of insurance should continue and that no state law relating to insurance should be affected by any federal law unless such law is directed specifically at the business of insurance; • All states impose investment limitations; • States regulate rates and expenses; • States control agents’ activities; and, • States have control over contractual provisions and their effects on the consumer.

All insurers must file annual statements


All insurance companies must file annual statutory statements of their income and financial condition in accordance with generally uniform statutes with the NAIC (www.naic.org). These statements, also known as convention statements, report statutory results. The accounting under which these results are compiled is termed statutory accounting. All public insurance companies are required to file a 10K with the SEC.

171

31 March 2006

Insurance sector outlook P&C companies: improvement in pricing and underwriting disciplines Moody’s outlook for the US personal lines insurance industry is stable, as US P&C insurers shift their focus towards restoring underwriting discipline, following a period of weak profitability.188 Results in the personal P&C lines started to show improvement in 2002 from the pricing and underwriting perspective, as the current market seems to be defined by participants ’ adoption of a “rate increase and profit ” versus “growth ” model. Even those insurers with business strategies that historically focused on market share growth have begun to exhibit a renewed sense of pricing discipline in the major product lines. These developments have not occurred in a vacuum. In fact, several favorable market characteristics have disappeared since the late 1990’s, including redundant reserve positions, benign automobile loss cost trends and high investment yields. Personal insurers have responded to the soft market cycle with important structural advances, namely fundamental improvements to their operational capabilities, in terms of both technology and underwriting. Moody’s expects that these changes will not only help firms achieve and sustain lower combined ratios,189 but may help to moderate the amplitude of the industry ’s inescapable cyclicality. With better information available sooner, carriers should be positioned to react more quickly to deteriorating pricing conditions that, if left unchecked, can choke profitability. An example - a bullish trend in auto premium rates

P&C companies have been imposing stricter underwriting standards and charging higher premiums. For example, the persistent bullish trend in auto premium rates as compared to auto repair costs is apparent. According to the consumer price index, personal auto insurance premiums rose at an annual rate of 7.9% in the 12 months ended July, and remain at a relatively high rate. In comparison, auto maintenance and repair costs, representing a little less than half of personal auto insurance costs, rose at a 3.3% annual rate for the 12 months ended July and remain low. The difference between personal auto insurance premiums and auto repair and maintenance costs is respectable, i.e., it stayed positive for the 26th straight month, though it has declined a bit. CREDIT SUISSE’s insurance analysts believe bond spreads in the P&C sector continue to benefit from strong technicals and healthy operating results across most of the companies due to the persistent “hard” market (as in not soft), a phase in the underwriting cycle where premium rates are increasing. 190 Second quarter 2003 earnings results showed good operating strength from the major insurers as a result of this persistently “hard” market, and most of the companies in the quarter beat consensus estimates.

Caution - premium increases are slowing

However, our analysts caution that evidence continues to emerge that the “hard” market may be softening in the form of companies’ elaborations on financial results, their stronger emphasis on growth through higher policy counts rather than through higher premium rates, and industry studies showing such trends. While premium rate increases are slowing, the current increases continue to build upon a sizable base of increases over the past three years, and current premium rates are contributing to favorable returns.

188

“US Property & Casualty Personal Lines Insurance Industry Outlook,” Moody’s, April 2003. The combined ratio is the sum of loss ratio and expense ratio. If the combined ratio is less than 100%, the difference is the underwriting profit margin. If the combined ratio exceeds 100%, underwriting was unprofitable - there was an underwriting loss. 190 CSFB Insurance Monthly, August 2003, fixed income research. 189


172

31 March 2006

L&H companies: strong core credit strength and more expected consolidations Moody’s believes that L&H companies continue to benefit from a number of core credit strengths. 191 These strengths include adequate capital supporting conservative balance sheets, predictable and profitable blocks of seasoned liabilities, and tax-favored product offerings. Credit profiles of US life insurers will continue to be driven by economic, demographic, and competitive trends and the related impact of customer preferences for various products and product delivery. Likely continued consolidation

Moody’s also suggested the strategic rationale for continued consolidation remains strong, despite the low level of such activity during 2002. A weak economy and slower revenue growth have negatively affected the valuation of many companies, creating opportunities for some larger, better capitalized companies to increase their scale, diversification, and distribution resources through acquisitions. Near-term acquisitions of entire companies may not be attractive for many companies, but Moody’s believes that block acquisitions will eventually become more prevalent. Larger diversified companies may seek to shed businesses that have limited scale and are not performing up to shareholders ’expectations, or sell units that are not part of their core competencies to free up capital for other operations. As a result, product-focused niche players should benefit from consolidation, as business line acquisitions could improve their competitive position.

ITP CDOs’ structural enhancement and other tidbits For ITP CDO investors, it is also important to focus on: 1) structural enhancement; 2) cash flow analysis; and, 3) the relative value comparison to other CDO products. We will discuss these aspects in turn. There are also some unique structural protection features common to these deals that are worth noting. These include: Diversion of excess spread

Diversion of excess spread. For some deals, a preset portion of the excess spread that is available for income note distribution will be used to pay down principal of the most senior notes (typically in year 8~10) until all senior notes have been paid in full.

192 Two common structural Shortening the ITP CDOs have a long legal final (typically 30 years). enhancement features seen in long-maturity CDOs are debt turboing and auction call, both average life of CDO of which are intended to reduce the average life of CDO debt. debt 193 Turbo Using excess spread to pay down the most expensive liability first, usually the Triple-B rated tranche in an ITP CDO, can increase the amount of future excess cash flow and shorten the Triple-B’s average life. For tranches senior to the Triple-B, credit enhancement is not affected, because only excess interest (which would have otherwise been paid to equity) is applied to pay down the Triple-B, and this is often conditional on the satisfaction of senior and mezzanine coverage tests. In essence, subordination is “replaced” with OC (i.e., over-collateralization).

Action call

Auction call. Most deals have the ability to solicit auction bids for the entire portfolio of securities whereby sale proceeds are used to pay off the notes. Typically beginning from year 8~10, the trustee will solicit auction bids for the purchase of all the remaining collateral. If the net proceeds from the highest bid are equal to or greater than the principal amount of the senior notes and mezzanine notes (including accrued and unpaid interest 191

“Credit issues and trends for US life insurance,” special comment, May 2003, Moody’s. In the generic deal that we illustrate later, we assume the collateral are called at a 5% annual rate after year five, the end of the non-call period, with 75% of the collateral being called at year ten, the first auction call date. This leads to an average life of 9.25 years for the collateral under a zero default assumption. The average life may extend if the collateral call rate declines. 193 This is often conditional on the satisfaction of preset equity return targets. 192


173

31 March 2006

and fees/expenses), the trustee will sell all the collateral. Sale proceeds will then be used to redeem the senior notes and mezzanine notes on the payment date immediately following the auction date with any additional amount going to the income noteholders. Barring any unexpected credit deterioration in the pool, it is likely that the auction call can be exercised. At the auction call date, two occurrences are likely to have happened: 1) the collateral would have seasoned and shortened its remaining average life, possibly being

sold at tighter spreads (and/or higher prices); 2) the Triple-B would have been partly paid down from debt turboing, reducing the amount of outstanding CDO liabilities. Both of these may result in an in-the-money auction call; i.e., the value of the collateral pool being greater than the value of the liabilities. Separately, after a CDO’s regular non-call period expires, equity holders are increasingly likely to call the deal, as the CDO should have de-levered from Triple-B turboing and collateral prepayment, which reduces the leverage and arbitrage (and the deal’s seasoned and shorter collateral could indeed be recycled into a new CDO). We caution that should collateral credit deteriorate, both the auction call and the regular call become less likely to be inthe-money. Additional principal pay down

Additional principal pay down. Similar to bank trust preferred CDOs, this allows payments to senior notes by the amount of defaulted or deferring assets even if senior OC tests remain in compliance. Payment for the additional principal paydown is made by using excess spread that otherwise would have been distributed to the income notes (equity).

IRR profile

A key part of CDO cash flow analysis is examining the internal rate of return (IRR) profiles. As a generic example, we look at a representative ITP CDO with a $300 mm capitalization, with 62% in ‘AAA’, 12% in ‘AA’, 10% in ‘A’, 6% in ‘BBB’ and 9% in equity. Exhibit 186 shows the internal rate return profile (IRR) for the CDO debt. Please see the footnotes of Exhibit 186 for modeling assumptions. Exhibit 186 indicates that the Triple-A, Double-A, Single-A and Triple-B can sustain about 9.3%, 7.4%, 4.5% and 3.5% constant annual collateral default rates (CDR), respectively, before each bond begins to lose yield. These breakeven rates suggest that the CDO debt has a very reasonable amount of protection against the historical default rates, 0.94% and 0.48% annually for P&C and L&H companies, respectively, and averaging about 0.80% for a typical 70/30 P&C and L&H blended ITP CDO collateral pool.

Exhibit 186: IRRs for a generic ITP CDO * AAA A

11% 9%

AA BBB

7% IRR

5% 3% 1% -2% 0% -4%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

-6% -8%

CDR

* We assume the collateral are called at a 5% annual rate after year five, the end of the non-call period, with 75% collateral being called at year ten, the first auction call date; no deferral of interest payment on the collateral; constant default starting immediately; 10% recovery with no lag; turbo ‘BBB’ with a 23% equity cap. Spread assumptions: collateral L+385bp, liability ‘AAA’ L+110bp, ‘AA’ L+140bp, ‘A’ L+205, ‘BBB’ L+375bp. Source: Credit Suisse


174

31 March 2006

Relative value: Spread pickup with greater credit enhancement

There are also attractive relative value opportunities, as ITP CDO notes offer a substantial spread pick-up over other more established CDO products. While bank trust preferred CDOs Triple-As reached 77 bps on average this year and more established CDO products such as HY CLOs and SF CDOs have typically priced below 60 bps, new issue ITP CDO Triple-As generally offer an above 100 bps spread. This also comes with a greater credit enhancement. For example, the subordination to Triple-As is on average 36%~44%, averaging 39% across the five outstanding ITP CDOs (which converts to 156%~179% OC),194 comparing to an average of 26% for a HY CLO.

Closing The application of the CDO technology to insurance risk creates a “win-win” in that it also provides an opportunity for mainstream fixed income investors to buy pooled insurance trust preferred risk at an attractive spread. In general, insurance deals have priced wider than bank trust preferred deals, partly attributable to a new product premium (including less investor familiarity with the collateral) and the perception of higher risk in stateregulated small insurers vs. federally regulated banks. ITP CDOs also offer a higher yielding investment opportunity, although one that comes with a give-up in liquidity. For ITP CDO investors, collateral due diligence is important. Some deals employ a manager to select/originate the initial collateral. To the extent that the manager has extensive expertise in the insurance industry, this can offer additional comfort to investors. We believe relatively well-capitalized smaller insurers with strong underwriting discipline will continue to outperform. As well, pooling a group of these small insurers (many with a niche product focus) should benefit CDO investors by creating product line and geographical diversification in the pool. In addition, some of these smaller insurers have a higher likelihood of being acquired, potentially enhancing ITP CDO performance.

194

The upfront cushion between actual OC and the triggers is also clear, as the senior OC trigger is typically set between 125%~128% for Triple-As, indicating a cushion greater than 30%. A larger cushion reduces the likelihood of early amortization.


175

31 March 2006

An Introduction to REIT Trust Preferred CDOs195 Trust preferred (TruPS) CDOs have grown from a niche market to a market mainstay since their inception in 2000. As CDOs are driven by innovation, it’s no surprise that TruPS CDOs have also evolved. The latest advancement in the TruPS CDO space is the inclusion of REIT-issued trust preferred securities in CDO portfolios. While some CDO pools have traditionally reserved small buckets for REIT TruPS, this year for the first time, the majority of a CDO’s portfolio was comprised of REIT TruPS. Three REIT TruPS CDOs totaling $2.6 billion have been issued so far (please see Appendix A), and we expect this asset class to continue to gain momentum and investor interest. In this section, we provide an introduction to REITs and REIT TruPS CDOs. As only a few REIT TruPS CDOs have been priced so far, our focus is on defining REITs and their historical performance and suitability as CDO collateral. We discuss the following: •

Define REITs – what are they from an equity and debt perspective;

•

Discuss trust preferred securities and why they are a suitable financing platform for REITs;

•

Outline the diversification benefits of REITs;

•

Discuss key credit considerations in evaluating REITs;

•

Review the credit performance of REITs;

•

Provide a REIT Sector Outlook; and

•

Discuss the REIT TruPS CDO platform.

REITs Defined What is a REIT? 196 A Real Estate Investment Trust (REIT) is a tax-efficient pass-through entity that functions like a mutual fund for real estate investments. REITs own, and in most cases, operate income-producing real estate. Additionally, some REITs also engage in real estate financing. REITs were created to provide smaller investors access to large-scale, incomeproducing real estate, with the benefit of diversification through a portfolio of real estate assets managed by experienced real estate professionals. REITs are exempt from corporate taxation by way of The Real Estate Investment Trust Act, subject to certain statutory requirements. These requirements include:197 •

At least 90% of taxable income must be distributed in common and/or preferred stock dividends each year;

•

At least 75% of the book value of total assets is invested in real estate equity and/or mortgages;

•

At least 75% of gross revenue is from rents and/or interest on mortgages; and

•

Not more than 50% of the REIT is owned by five or fewer individuals.

There are essentially three types of REITs: equity, mortgage and hybrid. •

Equity. Equity REITs own and operate income-producing real estate. Their activities may include leasing, development, and tenant services. Equity REITs must acquire and develop properties primarily to operate them as part of its own portfolio, and not to resell them once developed.

195

This section was originally published in "The CDO Strategist", Issue #8, September 30, 2005. This section makes extensive references to data and materials found in: "Frequently Asked Questions About REITs", The National Association of Real Estate Investment Trusts 197 "Real Estate Investment Trusts", presentation from CSFB REIT Debt Research, October 2004 196


176

31 March 2006

•

Mortgage. Mortgage REITs lend money directly to owners/operators of real estate or extend credit indirectly through the acquisition of loans or mortgagebacked securities (MBS). Some mortgage REITs may have their own loan servicing operations.

•

Hybrid. Hybrid REITs own properties and originate loans to real estate owners/originators.

Equity REITs account for the majority of publicly traded REITs, followed by mortgage and hybrid types (see Exhibit 187). As of September 2005, the National Association of Real Estate Investment Trusts (NAREIT) reports approximately 200 REITs registered with the Securities and Exchange Commission (SEC) in the United States that trade on one of the major stock exchanges, with total assets exceeding $400 billion. Additionally, approximately 800 REITs are not registered with the SEC and are not traded on a stock exchange. Exhibit 187 and Exhibit 188 show the breakdown of registered REITs by type and by market capitalization.

Exhibit 187: Registered REITs by Type Hybrid 2%

Exhibit 188: Registered REITs by Market Cap Sizes < $100 mm 8%

Mortgage 8%

> $2 bn 24%

$100 m m $2 bn 68%

Equity 90% Source: Credit Suisse, NAREIT. As of 9/1/2005.

Source: Credit Suisse, NAREIT. As of 9/1/2005

REIT Debt 198 A REIT, like any other corporation, issues a combination of equity and debt to finance its operations, acquisitions, and long/short term funding needs. Over $12 billion in REIT unsecured debt has been issued this year so far (as of 9/23/2005), well on track to another active year in the primary REIT bond market (Exhibit 189).

Exhibit 189: Historical REIT Corp. Bond Issuance – Another Strong Year in 2005 $18,000

His tor ical REIT Uns e cure d De bt Is s uance ($ m m )

$ 16,2 50

$16,000 $13,786

$14,000

$ 12,353

$12,000

$ 10,733

$10,000

$9,240 $ 7,951

$8,000 $6,000 $3,459

$4,000 $2,000

$1,680

$8,583

$9,570

$10,157

$4,426

$2,140

$0 1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Source: Credit Suisse. As of 9/23/2005.

198

This section makes extensive references to a presentation from CSFB's REIT Debt Research: "Real Estate Investment Trusts", October 2004


177

31 March 2006

REIT debt has traditionally been favored by (predominately) buy-and-hold investors because of two qualities differentiating them from corporate bonds. They include: 1) 2)

Strict, protective bond covenants; and Relatively stable and predictable cash flows.

Unlike a typical corporate bond, REIT bonds have strict covenants designed to keep overall leverage to a safe minimum, enforce financial discipline, and ensure that some portion of the assets are unencumbered, which protects the bondholder from being fully subordinated to mortgage lenders. A typical bond covenant package includes: 1) 2) 3) 4)

Total Debt/Total Assets < 60%; Total Secured Debt/Total Assets < 40%; EBITDA/Interest Expense > 1.5%; Unencumbered Assets > 150% of Unsecured Debt.

The first three covenants are on an incurrence basis, which means additional debt cannot be incurred if any of these covenants would be violated. By contrast, the unencumbered asset test is on a maintenance basis, which means the covenants must be met at all times, not just on an incurrence basis. Combined, these covenants help maintain the bond’s rating stability. Moreover, the covenants, along with SEC oversight of REIT equity, enhance the market transparency of REIT investments. Because of the nature of a REIT’s assets, CREDIT SUISSE REIT Analysts view REIT cash flows as more predictable compared to other corporate bonds. For example, sales revenue is a primary source of cash flow for some corporate issuers and this source may be highly volatile or subject to seasonal fluctuations in some industries.199 By contrast, cash flow from real estate assets is contractual and generated on a property by property basis. In addition, other sources of cash flow include: • • • • • • •

Advisory and management fee income; Retained cash flow from operations; Sale of assets; Equity issuance; Mortgage financing; Private capital; and Use of bank lines.

Investors should note however, that market shocks and company-specific difficulties could impact cash flow negatively. Furthermore, occupancy rates, lease expirations, tenant credit quality, prospects for rental growth, and the overall quality of a REIT’s portfolio all contribute to the health of anticipated cash flows. Please see the section, REIT Evaluation, for key considerations in evaluating REITs.

199


"Bonds - REIT Bonds", NAREIT Features, September/October 2004

178

31 March 2006

REIT Trust Preferred What Are Trust Preferred Securities and How Do They Work? 200 Since their inclusion as Tier 1 capital in 1996, trust preferred securities (TruPS) have been a popular financing mechanism for banks, utility companies, REITs, the insurance sector and more. TruPS are hybrid securities comprised of preferred equity issued by a special purpose trust, and debt issued by the company. For an overview of the trust preferred issuance structure, please see Appendix B. A TruPS promises to make periodic coupon payments and has a stated maturity (debt like), generally 30 years. Unlike debt, it is required to make the coupon payment only when the issuer is financially able (equity like). Otherwise, interest may be deferred for up to fiveyears, and the deferred interest is paid back on a cumulative basis. A TruPS is a bullet bond (not amortizing) with a 5- or 10-year non-call period. After this period, it is callable, typically at par (but not always). The “equity like” nature enables a TruPS to be qualified as equity for regulatory capital purposes. Its “debt like” attribute enables the coupon payment on the security to be taxdeductible for issuers, unlike other forms of equity. TruPS have been created by companies for their favorable accounting treatments and flexibility. Specifically, these securities are taxed like debt obligations by the IRS while maintaining the appearance of equities in a company's accounting statements in accordance with GAAP procedures. Upon liquidation of the issuing company, TruPS rank senior to the company’s preferred and common stock and junior to the company’s debt. Applying Trust Preferred to REITs For small to medium sized (SMS) REITs (< $2 bn market cap – see Exhibit 188), which account for the lion’s share of registered REITs, accessing the unsecured capital markets may prove difficult and costly. Often, the capital requirements of SMS REITs do not meet the market minimums for new-issue securities and the cost associated with underwriting and marketing equity can be expensive. Furthermore, since REITs must maintain certain leverage ratios, borrowing from the unsecured debt market may not be an option. Trust preferred financing is a natural fit into a REIT’s funding alternatives. Just like pooled bank and insurance trust preferred, REIT TruPS offer a more level playing field for smaller REITs (vs. larger ones), as the TruPS platform allows smaller REITs to achieve lower financing costs and faster execution. Exhibit 190 shows available aggregate REIT trust preferred issuance data for the past three years. There are several interesting take-aways from the table:

200 201


•

While the legal maturity of REIT TruPS is 30-years, it is likely that the REIT issuer will call the TruPS and refinance at the end of the non-call period, typically 5 or 10 years. Because of this feature, spread levels over both the 10-year and 30-year UST are provided.

•

REIT TruPS offer very attractive dividend and spread levels. This is partially due to the liquidity premium from the relatively small size of the REITs. Focusing only on rating and spread, even at a Single-B rating, which is many notches lower than the weighted average rating (WAR) of REIT TruPS, leveraged loans currently offer around 250 bps of spread compared to 324 bps on average for BB-/BB REIT TruPS.201

•

26 REITs were repeat issuers in the TruPS space, including one REIT that issued nine times over the three year period.

•

Nearly half the REIT TruPS in each vintage were unrated.

"Diversified Bank Trust Preferred CDOs", CSFB CDO Research, October 2003 Based on CSFB's Leveraged Loan Index

179

31 March 2006

Exhibit 190: Aggregate REIT Trust Preferred Issuance Data by Vintage since 2003

Vintage

Total REIT TruPS Issuance ($mm)

Total # Issued

Avg. Size

2003 2004 YTD 2005

$5,256 $5,871 $2,463

56 61 27

$94 $96 $91

Min Max Dividend Dividend 6.450% 6.125% 6.180%

11.000% 9.750% 9.125%

Weighted Avg. Dividend

Avg. Avg. Spread vs Spread vs 10yr UST 30yr UST

7.742% 7.483% 7.459%

375 339 324

283 260 294

% Rated

WAR Largest Sector

53.6% BB+/BBBRetail (29%) 54.1% BB/BB+ Diversified (18%) 51.9% BB-/BB Diversified (28%)

Source: Credit Suisse, SDC. As of 9/23/2005. Note that: WAR is calculated based on the S&P/Fitch rating for rated REIT TruPS.

While REIT TruPS do not typically have explicit covenants protecting holders, they do benefit indirectly from the implied protective covenants of REIT senior unsecured debt mentioned in the previous section, assuming the REIT is also an issuer of debt. This implied protection should support stable ratings and sufficient cash flow, barring any industry or company shocks.

Diversification Benefits – A Look at Total REITurns One of the benefits of REITs is their ability to provide portfolio diversification due to their low return correlation with returns of other assets. Not only are REITs diversified by type and geographic concentration, but also by industry distribution. Exhibit 191 shows the industry distribution among registered REITs.

Exhibit 191: Industry Distribution of Registered REITs

Health Care 5%

Home Mortgage Specialty Financing 6% 4%

Commercial Mortgage Financing 2%

Office 17%

Self Storage 4% Lodging/Resort 5% Diversified 8% Manufactured Homes 1%

Industrial 6% Mixed Office/Industrial 3%

Apartments 14%

Retail 25%

Source: Credit Suisse, NAREIT. As of 9/1/2005.

Performance among REIT industries varies considerably as not all real estate act alike. Exhibit 192 shows the monthly total return correlations among constituent industries in SNL Financial’s REIT Index from 1990 to August 2005. It is evident that certain industries are much less correlated than others. Excluding Diversified REITs, Office and Hotel REITs displayed the most negative return correlation at –0.059 while Multifamily and Residential REITs showed the highest return correlation at 0.993. It’s also worthy to note that Diversified REITs, which are typically comprised of multi-industry portfolios, were negatively correlated with nearly every other industry.


180

31 March 2006

0.993 0.498 0.610

0.473 0.605

Manuf Homes

0.798 0.784 0.482 0.652

Multifamily

0.556 0.590 0.564 0.285 0.495

Residential

Diversified/ Other

Industrial

Retail

Industrial Diversified/Other Office Retail Residential Multifamily Manuf Homes Self-storage

Office

Hotel

Hotel

Healthcare

Exhibit 192: Monthly Total Return Correlations of REIT Industries (1990-2005)

0.363 0.362 0.545 - 0.024 - 0.015 0.046 0.024 0.015 0.019

0.530 0.445 0.057 - 0.059 0.008 0.007 0.046 0.039

0.533 0.125 0.080 0.104 0.090 - 0.001 - 0.005

- 0.102 - 0.089 - 0.005 - 0.011 - 0.039 - 0.072

0.431

Source: Credit Suisse, SNL Financial. Figures reflect SNL’s REIT Index.

The diversification available within REITs translates into relatively low return correlation with other asset classes. Exhibit 193 shows the monthly total return correlations between several major market indices and the total returns of the NAREIT index and the CREDIT SUISSE Liquid US Corporate Index (LUCI) for REITs, separately.202 Examining the LUCI REIT bond index first, its correlation with other fixed income indices is very high while correlation with equity and high yield indices appears relatively low. Note that the LUCI REIT data only dates back to 2000/2001. The NAREIT index, which provides a more compelling story, has a much longer history. Over the 13-year time period between 1992 and 2005, return correlation between NAREIT and the major market indices was relatively low across nearly all sectors. According to Exhibit 193, the total return correlation between NAREIT and other market sectors was among the lowest in each sector examined. The lowest correlations, 0.061 and 0.107, occurred with the Merrill Lynch ABS and Mortgage indices, respectively, while the highest correlation, 0.389 and 0.336, occurred with the CREDIT SUISSE High Yield and JPMorgan Emerging Markets indices.

202 For more information on CSFB's LUCI bond index, please refer to "Introducing the Liquid U.S. Corporate Index (LUCI)", CSFB Index Research, November 15, 2002


181

31 March 2006

0.873

ML Corp LB Aggregate Bond S&P 500 DJ Wilshire 5000 JPM Emerging Markets CREDIT SUISSE Conv Securities CREDIT SUISSE High Yield Index CREDIT SUISSE Leveraged Loan Index NAREIT* CREDIT SUISSE LUCI – REIT**

0.843 0.929 0.077 0.045 0.407 0.043 0.190 -0.100 0.107 0.807

0.053 0.023 0.403 0.026 0.193 -0.054 0.153 0.894

0.979 0.513 0.751 0.489 0.137 0.291 -0.306

0.519 0.846 0.534 0.168 0.328 -0.292

0.472 0.516 0.046 0.336 0.279

CREDIT SUISSE Conv Secs CREDIT SUISSE HY Index CREDIT SUISSE Lev. Loan Index

JPM Emg. Markets

DJ Wilshire 5000

0.957 0.158 0.139 0.478 0.155 0.362 0.071 0.238 0.859

S&P 500

0.834 0.910 -0.066 -0.100 0.305 -0.073 0.055 -0.138 0.061 0.801

LB Aggregate Bond

ML Corp

ML ABS

ML ABS

ML Mortgage

Exhibit 193: Monthly Total Return Correlations Among Other Market Sectors

0.604 0.235 0.486 0.278 0.389 -0.138 0.133

0.258 -0.007

*NAREIT & all other market correlations reflect period from 1992-2005; **CREDIT SUISSE LUCI REIT correlations reflect period from 2001-2005. Source: Credit Suisse, CREDIT SUISSE Leveraged Finance Strategy, NAREIT.

Exhibit 194: Return Correlation Among Bank, Insurance and REITs (1992-2005)

SNL Insurance

0.7834

NAREIT

0.4820

SNL Insurance

SNL Bank & Thrifts

We also compare the total return correlations among bank, insurance, and REIT equity (Exhibit 194). Again, REITs show relatively low equity return correlation with bank and insurance, based on the SNL and NAREIT indices between 1992-2005. While we note that this is not the same as default correlation, REITs may provide diversification benefits when pooled with bank and insurance securities.

0.4276

Source: Credit Suisse, SNL Financial. As of 9/23/2005.

REIT Evaluation Key Credit Considerations In general, the evaluation of REIT credit should include a thorough analysis of the company’s fundamentals. CREDIT SUISSE’s REIT Debt Analysts have selected a number of key credit considerations worth assessing.203 These include: •

Management – reviewing the creditability, operating history, strategies, and possible succession issues of the managers of real estate held by the REIT. The REIT’s length of time as a public company is also worth considering.

•

Ownership/Corporate Structure – reviewing the REIT’s structural features, which may impact credit quality: traditional REIT versus UPREIT or downREIT, and any joint venture agreements.204

203

"Real Estate Investment Trusts", presentation from CSFB REIT Debt Research, October 2004 An UPREIT is a structure in which the REIT does not own a direct interest in properties, but rather in an umbrella partnership that owns interests in properties. For this reason, this umbrella partnership is generally referred to as the operating partnership. A side benefit of the UPREIT structure is that operating partnership units can be used as currency to acquire properties from owners who would like to defer taxes that would come due if the property(ies) were sold or swapped for stock. In response to this advantage of the UPREIT structure, a number of non-UPREITs have created so-called downREITs. This makes it possible for them to buy properties using downREIT partnership units. The effect is the same, however the downREIT is subordinate to the REIT itself, hence the name. (Source: Realty Stock Review) 204


182

31 March 2006

•

Asset/Property Profile – assessing the property types, portfolio age and quality, geographic distribution and tenant quality relative to the markets and locations that the REIT and its competitors operate in.

•

Financial Flexibility – assessing the REIT’s ability to provide short/long-term funding; the refinancing risk of near-term obligations, secured debt (long dated and free-and-clear properties will enhance flexibility), and debt covenants, which could be too restrictive.

•

Liquidity – assessing the cash flow and available borrowings under the bank credit facility relative to near term obligations, including debt maturities and capital expenditures.

•

Capital Structure/Leverage – assessing the level of leverage; leverage varies by property type, but REITs generally strive to maintain debt levels below a percentage of total market capitalization, often between 40% and 50%.

•

Cashflow Considerations – unlike most corporations, REITs are required to distribute 90% of their taxable income. Therefore, common and preferred dividends should be considered a fixed charge.

Besides these credit considerations, it’s also worthwhile to evaluate a few key equity ratios to gauge the REIT’s operating performance. Specifically, the industry standard methodology for evaluating a REIT's earnings potential is to review the Funds from Operations (FFO). FFO excludes the following from the net income figure: depreciation and amortization costs; gains and losses from extraordinary items; gains or losses from debt restructuring; and, gains or losses from sales of real estate. In this way, the FFO provide a more accurate assessment of real estate value versus the standard GAAP.

Credit Performance From a ratings and default standpoint, REITs have faired well. While REITs have been in the market since the 1960’s, it was not until the early 1990’s that they experienced significant growth and maturation into today’s REITs (Exhibit 195). For this reason, it makes sense to focus on the last decade or so in evaluating the credit performance of REIT debt.

Market Capitalization ($mm)

Exhibit 195: REIT Growth Picked Up Steam in the Early-Mid 90’s $350,000 $300,000

Hybrid Mortgage Equity

$250,000 $200,000 $150,000 $100,000 $50,000

19 81 19 82 19 83 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04

$0

Source: Credit Suisse, NAREIT


183

31 March 2006

Standard & Poor’s published its first rating transition study for U.S. REITs in June 2005, covering the 11-year period from 1994-2004. 205 Exhibit 196 shows the average 5-year cohort transition matrix for REIT debt:

Exhibit 196: Average 5-Year Cohort REIT Transition Matrix (1994-2004) From/To A (%) BBB (%) BB (%) B (%) CCC/C (%)

A 74.1 1.7 0.0 0.0 NA

BBB 20.7 64.5 22.8 0.0 NA

BB 0.0 5.1 40.4 100.0 NA

B 0.0 1.7 5.3 0.0 NA

CCC/C 0.0 0.0 0.0 0.0 NA

D 0.0 0.0 0.0 0.0 NA

N.R. 5.2 27.0 31.6 0.0 NA

Source: S&P, Credit Suisse

The matrix reveals several interesting observations: •

There were no downgrades to CCC or below and no issuer defaults during the 11year study period.

•

Of the 41 REIT ratings that were withdrawn (set to N.R. – not rated) by S&P during the study period, 76% were because of mergers & acquisitions among REIT issuers, reflecting the consolidation wave of the late 90’s

•

REIT ratings are clustered in the BBB category; nearly 70% of all original ratings were in the BBB bucket. While only 64.5% remained at BBB (largely attributed to the 27% withdrawn BBB ratings), only 6.8% of BBB ratings were actually downgraded on average during a 5-year period.

•

There were little or no REITs in the best and worst rating categories. Of the few that were initially rated B, all were upgraded to BB. 22.8% of REITs originally rated BB were upgraded to investment grade.

While the results reflect a subset of the REIT universe (those actually rated), the rating transitions study does point to favorable results for REIT credit since its expansion in the early 90’s. Most promising is the absence of defaults and the ratings stability of the asset class. Exhibit 197 compares the 5-year cohort ratings stability of REITs with that of corporate bonds and CMBS, after removing withdrawn ratings. REIT ratings stability at the BBB level, which accounts for the majority of rated-REITs, is significantly higher than corporates and just slightly below CMBS. Interestingly, REIT ratings stability actually increases as you go down in credit, but this may be due to the small sample size.

Exhibit 197: Comparative Stability Ratios (1994-2004)* Stable/Upgrade Ratio

REITs (%)

Corporate (%)

CMBS (%)

NA NA 76.9 89.2 94.1 100.0 NA

82.9 62.4 77.3 80.9 64.3 53.2 20.0

98.5 97.2 94.5 91.4 77.2 74.2 76.2

AAA AA A BBB BB B CCC/C *Based on Average 5-Year Cohort REIT Transition Matrix, N.R. removed Source: S&P, Credit Suisse

205


"Rating Transitions: A Generally Favorable First Decade for U.S. REIT Ratings", S&P, June 8, 2005

184

31 March 2006

REIT Outlook REITs have performed well over the last five years. REIT credit spreads are trading at historically tight levels and the trend is expected to continue. CREDIT SUISSE’s REIT Debt Analysts currently recommend the sector as “Overweight” on the heels of strong sector fundamentals and technicals, stable economic growth, and limited supply in REIT paper.206 As rates remain low and economic growth remains steady, CREDIT SUISSE Analysts believe that REIT bonds at current levels have value. Although investment-grade spreads widened earlier in the year, the Analysts view this as a result of interest rate concerns, inflation fears, and corporate headline news, rather than weakness in REIT fundamentals or technicals. Credit ratings are expected to remain stable or improving throughout the remainder of the year. For specific REIT sectors, CREDIT SUISSE Analysts observe declining vacancy rates and growing rents in a few property markets as signs of recovery in real estate fundamentals. Specifically: •

Industrial and Office sectors appear to have bottomed out. Office vacancies should continue to decline in 2005 but it may take another year or more to see landlords regain pricing power. Demand in Industrial REITs appears to be strengthening but landlords have no pricing power; speculative development still hurts near-term prospects.

•

Multifamily appears headed toward recovery, although supply/demand fundamentals are still out of balance in many regions. Occupancy rates show improvement in 2005, although near-term supply should continue to exceed demand as new construction continues unabated.

•

Retail outlook is robust as retailers are expanding, bankruptcies and store closings are running below 2004 levels, and a lack of new mall construction and consolidation have changed leasing dynamics.

The rating agencies share similar views as CREDIT SUISSE REIT Debt Analysts. As mentioned, S&P recently published its rating transitions for REITs, reflecting the first decade of performance.207 S&P views REITs as stable to positive, reflecting the generally favorable ratings stability and absence of defaults over the last 11 years. Also reflecting the favorable default history, Fitch has a stable to positive outlook on REITs as well, particularly for mortgage/hybrid and lodging REITs. According to Fitch, REIT performance has and will continue to benefit from macroeconomic factors, such as job growth, and improving fundamentals. Moody’s has a slightly less positive outlook on REITs, but still stable. However, on September 28, 2005, Moody’s upgraded Simon Property Group, a retail REIT, to Baa1 citing strong performance in the retail sector and sound fundamentals.208 This may be a signal for a more positive outlook from Moody’s.

Pooling it All Together: REIT TruPS CDOs The application of CDO technology with REIT TruPS creates a “win-win” for both SMS REITs and investors in that it provides an opportunity for mainstream fixed income investors to buy pooled REIT risk with industry and geographic diversity at an attractive spread while providing REIT issuers, particularly those with non-investment grade ratings, relatively cheaper and more efficient access to the capital markets. While the number of issued REIT TruPS CDOs has been limited so far, there are some common characteristics of these deals, which we discuss briefly. 206

"REITs: 2005 Outlook", presentation from CSFB REIT Debt Research, August 2005 "Rating Transitions: A Generally Favorable First Decade for U.S. REIT Ratings", S&P, June 8, 2005 208 "Moody's Upgrades Simon Property Group's Senior Debt to Baa1; Stable Outlook", Moody's, September 28, 2005 207


185

31 March 2006

Collateral Composition and CDO Structure Exhibit 198 shows some basic details of the REIT TruPS CDOs issued so far:

Exhibit 198: Basic Details of REIT TruPS CDOs issued so far Deal/Structural Information Average Deal Size ($mm): AAA Credit Enhancement (%): AA Credit Enhancement (%): A Credit Enhancement (%): BBB Credit Enhancement (%): BB+ Credit Enhancement (%): Average Equity Size:

$850.67 42.4% 28.6% 18.0% 8.8% 7.8% 8.8%

Management Type: Auction Call: Non-Call Period: Maturity:

Static Pool 10 Years 5 Years 30 Years

Collateral Information Pool Concentration REIT/REOC TruPS * REIT/REOC Snr/Sub Notes CMBS

87% 10% 3%

WAS: WAC: Max Issuer Concentration:

306 bps 5.13% 3.75%

Source: Credit Suisse, Fitch Presale Reports, Bloomberg, MCM, IFR * REOCs (Real Estate Operating Companies) are similar to REITs except they are taxed as ordinary corporations, but are not subject to the same restrictions as REITs. REOCs do not need to distribute any dividends. This allows REOCs to have superior operating flexibility under certain stressed circumstances compared to equity REITs. (Source: Fitch)

For the most part, the majority of REIT TruPS collateral in CDO pools have been issued by registered REITs. In addition, approximately 50% of the pools pay floating-rate, 13% pay fixed-rate, and the remainder pays hybrid, whereby the coupon is fixed for the first 5-10 years and switches to floating thereafter. The structural features of the deals are similar to other CDOs in the market. The cash flow waterfall pays sequentially with an equity cap currently around 18%: excess spread is used to turbo the BBB tranches. Like other CDOs, cash flow is diverted from junior tranches to senior tranches if overcollateralization tests fail. A few variations from typical CDOs include:209 •

OC haircuts for REITs that fail to meet two out of the following three financial performance tests: 1) interest coverage tests; 2) total debt to total capitalization tests; or 3) tangible net worth tests.

•

Additional OC haircuts for REITs that violate two out of the following three tests: 1) if the REIT eliminates the common dividend payout or does not pay for two consecutive quarters; 2) if the REIT is unable to maintain a certain fixed-charge coverage ratio; or 3) if any monetary covenant is not cured for 30 days.

REIT TruPS CDOs currently price with a new product premium. Compared to recently issued hybrid bank & insurance TruPS CDOs, REIT TruPS CDOs offer a 5 to 45 bps spread pickup and offer higher credit enhancement levels across the capital structure.

209


Fitch Presale Reports.

186

31 March 2006

A Note on Rating Agency Methodologies The rating agencies have not yet formally published their rating methodologies for rating REIT TruPS CDOs. We do not provide details for each methodology however, it is important to review a few key differences across agency approaches. Moody’s uses a more stringent approach by taking a pool wide perspective of the REIT TruPS collateral to generate a pool wide rating and default probability across all unrated REITs (which accounts for the majority of REIT collateral in the CDO) in addition to the public Moody’s ratings where available, and assumes a 15% recovery rate across all REIT TruPS.210 By contrast, Fitch and S&P will have their respective REIT sector specific analysts review each trust preferred issuer and determine suitable ratings, default probabilities, and recovery rates for each unrated issuer. We expect rating agency treatment of REIT TruPS CDOs to become more refined as the product develops and structures become more established. What’s Next? While REIT TruPS CDOs are still in the early stages of their development, we believe the asset class is positioned for robust growth over the next year. REITs have a strong and stable track record over the last decade. Their relatively low correlation within REIT industries and across broader market sectors makes them suitable for CDOs. Given the attractive asset level spreads, new product premiums, relatively higher equity returns, and a positive REIT outlook, investors should consider REIT TruPS CDOs. Because of the limited registered REIT universe (about 200 REITs), we expect more hybrid pools to be issued. These hybrid pools may consist of other trust preferred securities, including bank and insurance TruPS, and/or possibly other structured finance credits. REITs should provide added diversification benefits to these assets classes. Furthermore, CDO issuers may move into more private, non-registered REITs to source trust preferred collateral.

210 "Trust Preferred Market Update and REIT CDOs", Moody's 5th Annual U.S. CDO Investor Briefing, September 7, 2005.


187

31 March 2006

Appendix A. REIT TruPS CDOs Priced as of September 2005 Taberna Preferred Funding I - $729mm

Priced: 2/24/05

Lead: Merrill Lynch Tranche A1 A2 B1 B2 C1 C2 C3 D E P/S

Size $371,000,000 $87,000,000 $64,000,000 $10,000,000 $37,750,000 $25,750,000 $4,500,000 $13,500,000 $37,500,000 $77,800,000

% of Deal 50.9% 11.9% 8.8% 1.4% 5.2% 3.5% 0.6% 1.9% 5.1% 10.7%

Manager: Taberna Capital Management Rating WAL Pricing (Moody's/S&P/Fitch) (Years) Level --/AAA/AAA 8.3 L + 47 --/AAA/AAA 10.1 L + 70 --/AA/AA 10.1 L + 110 --/AA/AA 10.1 ---/A/A 10.1 L + 180 --/A/A 10.1 ---/A/A 10.1 ---/BBB+/BBB+ 10.1 L + 235 --/BBB/BBB 8.8 L + 315 ----

Source: CREDIT SUISSE, Bloomberg, IFRmarkets & MCM

Taberna Preferred Funding II - $1043mm Lead: Merrill Lynch Tranche A1A A1B A1C A2 B C1 C2 C3 D E1 E2 F PS

Size $400,000,000 $106,500,000 $10,000,000 $86,500,000 $120,500,000 $73,750,000 $26,000,000 $15,000,000 $31,250,000 $31,750,000 $10,000,000 $42,500,000 $89,000,000

% of Deal 38.4% 10.2% 1.0% 8.3% 11.6% 7.1% 2.5% 1.4% 3.0% 3.0% 1.0% 4.1% 8.5%

Priced: 6/10/05 Manager: Taberna Capital Management Rating WAL Pricing (Moody's/S&P/Fitch) (Years) Level Aaa/AAA/AAA 8.2 L + 43 Aaa/AAA/AAA 8.2 L + 43 Aaa/AAA/AAA 8.2 ---/AAA/AAA 10.0 L + 65 Aa2/AA/AA 10.0 L + 90 --/A/A 10.0 L + 170 --/A/A 10.0 ---/A/A 10.0 ---/A-/A10.0 L + 190 --/BBB/BBB 9.4 L + 290 --/BBB/BBB 9.4 ---/BB+/BB+ 10.0 L + 500 ----


Taberna Preferred Funding III - $780mm Lead: Merrill Lynch Tranche A1A A1B (DDraw) A1C A2 B1 B2 C1 C2 D E PS

Size $188,500,000 $210,000,000 $10,000,000 $53,500,000 $91,250,000 $7,500,000 $36,500,000 $52,000,000 $43,750,000 $31,500,000 $55,100,000

% of Deal 24.2% 26.9% 1.3% 6.9% 11.7% 1.0% 4.7% 6.7% 5.6% 4.0% 7.1%

Priced: 9/14/05 Manager: Taberna Capital Management Rating WAL Pricing (Moody's/S&P/Fitch) (Years) Level Aaa/AAA/AAA 8.4 L + 40 Aaa/AAA/AAA 8.4 L + 40 Aaa/AAA/AAA 8.4 -Aaa/AAA/AAA 10.1 L + 52 Aa2/AA/AA 10.1 L + 80 Aa2/AA/AA 10.1 ---/A/A 10.1 L + 160 --/A/A 10.1 ---/BBB/BBB 10.1 L + 265 --/BB+/BB+ 10.1 L + 450 ----



188

31 March 2006

Appendix B. An overview of trust preferred issuance structure A typical issuance structure for trust preferred securities can be illustrated below: 1)

The HC establishes a special purpose subsidiary (Trust), the sole purpose of which is to issue trust preferred securities. The HC purchases all of the common stock of the Trust (usually at least 3% of the total capitalization of the Trust).

2)

The Trust issues trust preferred securities into the CDOs, or other outside parties.

3)

The Trust receives proceeds from the trust preferred securities offering.

4)

The Trust uses the proceeds to purchase from the HC long-term junior subordinated debt with terms matching those of the trust preferred securities. The Trust distributes interest it receives on the long-term subordinated debt to pay dividends on the trust preferred securities.

Holdings Company (“HC”) (Parent Company) Junior Subordinated Debt #4

Proceeds #3

Special Purpose Subsidiary (Trust) #1 Trust Preferred Securities #2

Proceeds #3

Trust Preferred CDO Source: Credit Suisse


189

31 March 2006

Bank TruPS: Fine Tuning Historical Bank Failure Rates211 Rating agencies have traditionally taken a conservative view on bank default rates in rating bank trust preferred security (TruPS) CDOs, implying a mid-to-low-BBB cumulative default rate based on historical FDIC intervention rates, with emphasis on the last three decades of banking history. However, with bank TruPS CDOs performing as well as they have, we believe the derivation of bank default rates can be fine tuned to imply better ratings, to more accurately reflect the credit quality of the issuing institutions and the banking industry in general. In this section, we take a closer look at default rates of bank trust preferred issuers.212 Since the creation of the agency in 1933, the Federal Deposit Insurance Corporation (FDIC) has monitored and addressed risks to deposit-insurance funds and limited the impact of failed bank or thrift institutions on the economy and financial systems. Through the application of various resolution strategies, the FDIC intervenes on distressed institutions to insure depositors up to certain statutory limits. Rating agencies and underwriters approximate bank default rates based on these FDIC interventions. However, not all interventions result in bank failures and not all failures should be treated equally. The main issues with existing treatment of bank failures using intervention rates are two-fold: 1)

The inclusion of “Open Bank Assistance” transactions as part of the failure rate; and,

2)

Overemphasis of the banking crisis of the 1980s in deriving failure rates that reflect the “modern” banking industry (and going forward).

We address each of these issues below, focusing our analysis on commercial banks in FDIC’s coverage universe.213 We begin with a brief review of the 1980s banking crisis and the actions that were taken in its wake.

The ‘80s Banking Crisis – Still Applicable?214 By far, the 1980s to early 1990s accounted for the lion’s share of bank failures since the FDIC’s inception (Exhibit 199). The banking crisis of the 1980s was not caused by a single event, but rather a combination of forces. These forces included:

•

National economic and legislative forces: Volatility in exchange rates of major currencies in the ‘70s and interest rate variability by the Federal Reserve to combat inflation challenged the banking industry in the ‘80s. Smaller banks, which depended on deposit funding, were particularly pressured by rising interest expenses. Additionally, on the legislative front, the industry saw widespread deregulation and relaxation of statutory restrictions in an attempt to modernize the banking industry.

211

This section was originally published in "The CDO Strategist", Issue #10, October 31, 2005. This analysis follows a similar study conducted in 2002 in our Bank Trust Preferred primer. For a general overview of bank TruPS, please refer to "Diversified Bank Trust Preferred CDOs", CSFB CDO Research, October 2003. 213 We exclude savings (thrift) institutions in this analysis. Savings institutions represent a minority of the overall banking industry (about 15% in 2004) relative to commercial banks (85%). Available data on savings institutions is also limited. This study is based on FDIC’s Historical Statistics on Banking, which provides comprehensive lists of individual banks that failed or received financial assistance from the FDIC since 1934. 214 This section makes extensive references to the FDIC publication, "History of the Eighties - Lessons for the Future". 212


190

31 March 2006

•

Regional recessions: Regional economic stresses resulted in clear geographic patterns of bank failures. During the 1980-94 period, five states accounted for nearly 60% of all failures. 215 Some of the regional stresses included: severe downturns related to the collapse of energy prices, real estate related stresses, especially on the commercial side, and the agriculture recession of the early ‘80s.

•

Increased risk with insufficient and untimely oversight: As a result of deregulation in the ‘80s, banks began taking greater risks without additional supervision to restrict their discretion and behavior. Any oversight in place was untimely and infrequent. Examinations of banks declined from 12,300 examinations in 1981 to 8,300 in 1985. Also, the average length of time between subsequent examinations increased from 13 months in 1979 to 20 months in 1986.

Exhibit 199: Distribution of Commercial Bank Failures, 1934-2004 (by count) 225

$10bn or more $1bn to $10bn $100mm to $1bn Less than $100mm

200

Number of Failures

175 150 125 100 75 50 25 0 1934

1939

1944

1949

1954

1959

1964

1969

Year

1974

1979

1984

1989

1994

1999

2004


While some of these forces are outside the control of any regulatory body, the FDIC has put in place many changes to address the lessons learned from the industry’s most severe crisis. Some of these changes include:

•

Adoption of regulatory capital requirements and risk-based deposit insurance premiums to make risky behavior less attractive. Prior to 1990, regulators were limited in their ability to restrain risky lending behavior of profitable banks in the absence of penalties or costs, which resulted in an abundance of speculative lending, particularly in commercial real estate.

•

Limiting the use of forbearance by requiring more-timely and less-discretionary intervention of failing banks. While this may result in more closures earlier by the FDIC, it limits the severity of losses and the potential impact on the rest of the banking industry.

•

Significant improvements in supervision and oversight of banks, and enforcement of CAMELS ratings. 216 Volume and frequency of examinations have improved considerably with an annual full-scope examination required since 1991 for most banks. Additionally, studies have shown that accurate and up-to-date CAMELS ratings generally identify most of the banks requiring increased supervisory attention.217

215

By count/occurrence. The five states include: California, Kansas, Louisiana, Oklahoma, and Texas. The acronym “CAMEL” stands for Capital, Assets, Management, Earnings, and Liquidity, five components of a bank’s financial operation that are examined by regulators. In the late 1990s a sixth component was added to the CAMEL rating system, recognizing bank and thrift Sensitivity to interest-rate or market risk (CAMELS). CAMELS ratings are assigned on a scale of 1 to 5 with 1 being the highest and 5 the lowest. “FDIC Banking Review", FDIC. 217 “The Banking Crises of the 1980s and Early 1990s: Summary and Implications”, FDIC 216


191

31 March 2006

The banking environment over the last decade suggest that the response to the ‘80s crisis was fruitful. Since 1994, the banking industry has undergone more than a decade of relatively benign credit and performance, despite fluctuations in interest rates, turbulence in the financial markets, and the economic cycle. While it is difficult to predict future performance and the emergence of new problems with few precedents in the past, we are encouraged by the changes that have been made since the ‘80s banking crisis and the solid performance of the industry since. We believe that the last eleven years represent the “modern” banking era and should be considered so in the calculation of bank default rates. But more on this, later.

Inferring the Default Rate When a Failure Isn’t a Failure Since 1934, the FDIC has intervened on commercial banks 2,159 times.218 While most studies of bank defaults include any intervention as a bank failure, not all interventions are failures and an ultimate default of obligations. An example of this is the open bank assistance (OBA) intervention, where a distressed financial institution remains open with government financial assistance.219 In an OBA, the FDIC seeks to minimize the costs of a failing institution to depositinsurance funds. The institution is kept open for public policy motivations, such as preserving public confidence and maintaining banking services to a community. At the resolution of an OBA, the bank’s charter continues and creditors are repaid at the expense of the FDIC, shareholders, and various private sector participants.220 Because ultimate losses are not realized by debt holders (trust preferred included), this type of intervention should not be included in approximating the default rate. Since the first OBA transaction on commercial banks in 1971, there have been 126 instances of OBA interventions. While the number is small (about 8% of FDIC interventions since 1971), netting out these transactions does provide a more accurate default picture. To approximate the default rate using FDIC interventions, we take the following steps: 1)

Calculate the number of FDIC interventions, by occurrence and per year, for the most recent 30-year period from 1975 – 2004, netting out open bank assistance interventions.

2)

Derive the intervention rate for each year, using the total number of outstanding commercial banks in each year (with failed institutions that year added back on) as the denominator. Calculate the cumulative intervention rates by summing the rates of each year. We refer to this as the “failure rate”.

3)

Additionally, we estimate the credit quality by comparing the failure rates to Moody’s idealized cumulative corporate default rates. The results are shown in Exhibit 200. As shown, excluding OBA transactions from the failure rate results in a small improvement (black line compared to dashed-brown line), with the 30-year cumulative rate (11.7%) just below that of Baa1 corporates (12.4%).

218

Through 12/31/2004, according to FDIC's Historical Statistics on Banking "Managing the Crisis: The FDIC and RTC Experience", Chapter 5 - Open Bank Assistance, FDIC, August 1998 220 There are cases where an institution's charter survives the OBA but is later closed under a different intervention. 219


192

31 March 2006

Exhibit 200: Cumulative Bank Failure Rates, 1975-2004 A3 rated corporate Baa2 rated corporate Commercial banks (ex. OBA)

20.0%

Baa1 rated corporate Baa3 rated corporate Commercial banks (inc. OBA)


17.5% 15.0% 11.690%

12.5% 10.0% 7.5% 5.0% 2.5%

0.361% 1.591%

20 03

20 01

19 99

19 97

19 95

19 93

19 91

19 89

19 87

19 85

19 83

19 81

19 79

19 77

19 75

0.0%

Source: Credit Suisse, FDIC, Moody’s

Reducing the Weight of the ‘80s Crisis The curve in Exhibit 200 suggests lower overall failure rates than that of Baa3 corporates based on curve shape, however we believe the credit quality is better than this. The primary driver of higher cumulative failure rates in the back-end of the curve stems from the sharp rise in bank failures during the banking crisis of the 1980s to early-1990s, the most severely distressed period in US banking history. An alternative approach, which dilutes the impact of the 1980s’ banking crisis, is to consider the entire history of bank failures. In Exhibit 201, we show cumulative bank failure rates from 1934-2004, using every observation available from the FDIC, to generate the curve. For example, to calculate the 30-year cumulative rate, we take the cumulative failure rates (as calculated for Exhibit 200) for every consecutive 30-year period since 1934 and derive the average across time. This process is repeated for each period (1-year, 2-years, 3-years, etc.).

Exhibit 201: Cumulative Bank Failure Rates – All Observations, 1934-2004 A1 rated corporate A2 rated corporate A3 rated corporate Baa1 rated corporate Commercial banks (all history)

11.3%


10.0% 8.8% 7.5%

5.499%

6.3% 5.0% 3.8% 2.5%

1.108%

2.212%

1.3% 0.0% 1

2 3 4

5 6

7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Years


The chart suggests a better credit outlook for banks in terms of failure rates. The curve (black line) points to lower overall failure rates than Baa1 corporates and flattens towards the back-end, arriving at a cumulative 30-year failure rate of 5.5%, just under the A1 cumulative corporate default rate of 5.9%.


193

31 March 2006

However, we note two main problems with this approach, as a result of data shortcomings: 1)

Ideally, we’d like to calculate the failure rate based on cohort. Unfortunately, this data is unavailable.

2)

We assume that the banking industry in different periods of time are comparable to each other, however, we realize that the industry has gone through significant changes since 1934.

Still, expanding the methodology to include all available bank failures produces a more level view of the banking industry by diluting the negative effects of the 1980s banking crisis. As discussed earlier, many changes and improvements were put in place following the 1980s banking crisis to prevent, or at least to predict, a similar repeat period of distress. If we take into account only the last 11 years since the end of the banking crisis, which we consider the “modern” banking era, the resulting failure rates are broadly better. Using the same methodology as in Exhibit 200, we derive the cumulative bank failure rates from 1994-2004. As shown in Exhibit 202, the curve suggests lower cumulative failure rates than A2 rated corporates and similar rates as A1 rated corporates. The higher oneyear rate in 1994 reflects some carry-over affect from the 1980s banking crisis.

Exhibit 202: Cumulative Bank Failure Rates, 1994-2004 – The “Modern” Era 1.60%


1.40% 1.20%

Aa3 rated corporate A1 rated corporate A2 rated corporate Commercial banks (ex. OBA)

1.00% 0.80%

0.6061%

0.60% 0.40%

0.2630%

0.20% 0.00% 1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004


As we saw in Exhibit 199, small banks (under $100 million in assets) represent the overwhelming majority of commercial bank failures. According to a recent Fitch study on bank TruPS CDOs, about 53% of the issuers in 2004-vintage CDOs had assets of $100 million to $1 billion, while issuers with under $100 million in assets accounted for about 8.5%.221 In Exhibit 203, we contrast the failure rates and implied credit quality, across asset sizes, over two periods in the last two decades: 1) 1994-2004 (which excludes the 1980s banking crisis), and 2) 1984-2004 (which includes the 1980s banking crisis).

221


“Trust Preferred CDO Performance Update”, Fitch, March 1, 2005

194

31 March 2006

Exhibit 203: Annual Failure Rates for Commercial Banks by Asset Class

Bank Asset Size

% of issuers in 1984-2004* 2004 BTruPS Annual Failure Implied Credit CDOs Rate ** Quality ***

Less than $100 mm $100 mm to $1 bn $1 bn to $10 bn $10 bn or more Weighted Average ****

8.5% 53.0% 32.5% 6.0% 100%

0.59% 0.31% 0.26% 0.25% 0.31%

Baa2/Baa3 A3 A2/A3 A2/A3 A3

1994-2004 Annual Failure Rate

Implied Credit Quality

0.069% 0.046% 0.083% 0.000% 0.057%

Higher than A3 Higher than A3 Higher than A3 Higher than A3 Higher than A3

Source: Credit Suisse, FDIC, Moody’s, Fitch * 1984 is used as the starting point because data on the number of banks by asset class was only available from this point ** Annual failure rate is calculate as the cumulative rate divided by the number of years *** Implied credit quality is derived from Moody’s idealized corporate default rates **** Weighted Average uses Fitch’s 2004 bank TruPS CDO issuer asset compositions as the weights

As shown, commercial bank failure rates imply a weighted average credit rating of A3, when including the 1980s banking crisis, and even better when excluding, using the actual breakdown by issuer asset sizes for all 2004 bank TruPS CDOs as the weights. This suggests that the implied credit quality of bank TruPS CDO collateral may warrant a better rating than Baa2/Baa3. Finally, in Exhibit 204, we provide the 5-year, 10-year, and 30-year cumulative commercial bank failure rates from each of our methodologies above (notice the red boxes in Exhibits 201, 202 and 203 above) since most bank TruPS have either a 5- or 10-year non-call period and a 30-year legal maturity.

Exhibit 204: Select Cumulative Failure Rates Using Different Methodologies 1975-2004 Most Recent Only (30yrs)

1934-2004 All History (30yrs)

1994-2004 The “Modern” Era (11yrs)

Cumulative

Implied Rating

Cumulative

Implied Rating

Cumulative

5-year

0.36%

A1/A2

1.11%

Baa1

0.26%

A1

10-year 30-year

1.59% 11.70%

A2/A3 A3/Baa1

2.21% 5.50%

A3/Baa1 Aa3/A1

0.61% NA

Aa3/A1 NA

Bank Asset Size

Implied Rating


Closing Thoughts The old adage goes: “Only time will tell”. While it remains to be seen whether the banking industry has learned enough from its past to avoid similar difficulties in the future, we view the last eleven years of benign credit and low intervention rates as a good start. With a surge in bank TruPS CDO issuance expected in 2006-2007 (many older bank TruPS are reaching the end of their 5-year non-call period and are expected to refinance), we think the asset class is worth considering. The purpose of this piece is to provide investors with a closer look at one aspect of bank TruPS CDOs. While our analysis took a less conservative approach than rating agencies, we also note that there are many other considerations in evaluating the credit quality of bank TruPS. For example, because TruPS are deeply subordinated obligations, recovery rates may be very low if defaults occur. That said, the relatively higher average subordination levels in bank TruPS CDOs should reduce the impact of losses (Exhibit 205). Also, trust preferred issuance has helped fuel ongoing industry consolidation and M&A activity. It remains to be seen whether issuers can successfully manage all the risks associated mergers and growth.


195

31 March 2006

Exhibit 205: Average Subordination Levels of BTruPS CDOs vs. Other CDO Types 40%

T rip l e- A A verag e Sub o rd inat io n

30%

35%

D o ub le- A A verag e Sub o rd inat io n

25%

30% 20%

25%

15%

20% 15%

10%

10% 5%

5% 0%

0% BTruPS CDO

18%

HY CLO

CRE CDO

Mezz SF CDO

BTruPS CDO

HG SF CDO

Sing l e- A A verag e Sub o rd inat i o n

12%

16%

HY CLO

CRE CDO

Mezz SF CDO

HG SF CDO

T ri p le- B A verag e Sub o rd inat io n

10%

14% 12%

8%

10%

6%

8%

4%

6% 4%

2%

2% 0%

0% BTruPS CDO

HY CLO

CRE CDO

Mezz SF CDO

HG SF CDO

BTruPS CDO

HY CLO

CRE CDO

Mez z SF CDO

HG SF CDO



196

31 March 2006

Bank TruPS CDOs: Calling the Underlying222 Common to all trust preferred securities (TruPS) is a non-call feature during the first five or ten years of the securities’ life, after which the TruPS are callable, typically at par.223,224 In 2006, bank trust preferred securities in early vintage (2001) bank TruPS CDOs will reach their five-year non-call period and we expect a surge in prepayments and deal redemptions. Given that most bank TruPS CDOs are priced to the auction-call date (typically 10 years, longer than the five-year non-call date of most of the underlying TruPS securities), the valuation could be misleading if the deal were terminated earlier due to prepayment/call of the underlying collateral. Due to tightening liability spreads of new-issue TruPS CDOs and the favorable performance history of bank TruPS, most seasoned bank TruPS CDO tranches are priced at a premium in the secondary market. It is crucial to assess the termination date of the bank TruPS CDO accurately, i.e., the expected life of the tranche, to calculate the fair price of the bond. In this section, we’ll provide some comments on why it makes sense for banks to call their early vintage TruPS, review the unique features of bank TruPS CDOs, and provide a numerical example for bank TruPS CDO investors. We will focus on the 2001 and 2002 vintages of TruPS CDOs, as the collateral in these deals will be exiting their five-year noncall periods over the next 24 months.

Calling the Collateral – Why it Makes Sense Quite simply, the cost savings for bank issuers are too good to ignore. The cost to fund trust preferred securities has cheapened significantly since 2001 as a result of solid performance in the banking sector, significant industry consolidation, investor comfort in the asset class, and the benign credit environment. 225 Exhibit 206 shows average collateral cost-of-funding attributes of 2001 and 2002 vintage bank TruPS CDOs versus that of recent deals (2005). On a weighted-average basis across all pools in the aforementioned CDO vintages, the cost savings for an issuer that calls its more expensive, early vintage trust preferred securities and refinances at today’s rates is 161 bps for 2001 TruPS and 123 bps for 2002 TruPS.

CDO Liabilities

CDO Collateral

Exhibit 206: Average cost savings: too good to ignore Average Cost Savings 2005* 2005 vs. 2001 2005 vs. 2002

2001

2002

Average WAS (over LIBOR)

384 bps

347 bps

223 bps

161 bps

123 bps

Avg. WAC (for fixed)

9.32%

9.22%

7.76%

156 bps

146 bps

Avg. WA Hybrid (5-yr fixed)**

---

---

6.28%

Avg. % floating rate

90.21%

95.40%

67.85%

78 bps

59 bps

Avg. % fixed

9.79%

4.60%

5.70%

Avg. % hybrid

---

---

26.45%

CDO Avg. Cost of Liabilities (over LIBOR)

144 bps

125 bps

65 bps

Source: Credit Suisse, Moody’s, Fitch * 2005 features deals backed by both bank and insurance trust preferred securities. **Hybrid Coupon typically includes a fixed rate for 5-years, followed by a floating-rate coupon.

222

This section was originally published in "The CDO Strategist", Issue #11, November 16, 2005. Nearly all bank TruPS in CDOs feature a five-year non-call, as opposed to ten-year. We note that there are certain TruPS that feature a call premium on the first callable date and the premium decreases on a schedule as the security seasons. However, this is less common. 225 Please see our commentary on bank failure rates, "The CDO Strategist - Bank TruPS: Fine Tuning Historical Bank Failure Rates", Issue #10, October 31, 2005. 223 224


197

31 March 2006

However, the cost savings for bank issuers is likely to be even higher. The figures for 2005 vintage TruPS CDOs in Exhibit 206 include the weighted-average of all pools this year. Since late 2004, however, most TruPS CDOs have included insurance TruPS collateral (up to 33% in recent deals), which offer higher spread coupons than banks. Focusing only on bank issuers, we estimate that the cost to issue bank trust preferred is more in the range of 150 bps – 180 bps over LIBOR. This suggests a cost savings for bank issuers that may exceed 230 bps (= 384 bps – 150 bps) if refinanced today, depending on vintage and issuer credit quality. Additionally, widespread industry consolidation through mergers and acquisitions (M&A) may encourage the acquiring issuers to call their outstanding trust preferred securities. According to Fitch, trust preferred securities in CDOs from the 2001 and 2002 vintages experienced the highest levels of M&A activity (relative to all vintages from 2000-2004), with up to 16% of the underlying being acquired as of Q1 2005.226 With the majority of acquiring banks being large banking institutions ($10 billion or more) with better financial profiles than the acquirees, it would be economical for the acquirer to retire the more expensive TruPS (inherited through M&A) and either refinance at cheaper levels or use alternative forms of funding.

Call attributes unique to bank TruPS CDOs Most trust preferred paper in TruPS CDO pools come from the primary market through pooled issuance whereby the underwriting process is largely standardized and simplified across individual banks and each individual bank participating in the pooled issuance issues trust preferred securities directly into the CDO vehicle, cutting out the costs of marketing, road showing, etc. Unlike other CDOs, the fact that it is pool-issued gives the arranger or issuer of the CDO some additional options that are unique to TruPS CDOs. All of the TruPS in a pooled issue look identical in structure and terms. For example, they share the same legal maturity, call provisions, default events, etc. These similarities facilitate the CDO arranger/issuer in executing a pool-wide refinancing of the underlying securities following the end of the TruPS’ non-call period. The arranger can approach each bank in the pool and offer to refinance the TruPS into a new CDO vehicle at current rates. This shares the same effect in terms of terminating the CDO, with the optional redemption call usually reserved for the equity holder. Only in the case of collateral that has not yet exited the non-call period or those where calling may be uneconomical (such as securities requiring significant call premiums) does the arranger/issuer not have the right to refinance or sell into a new transaction. However, with the CDO likely de-levered significantly as a result of the majority of the collateral being prepaid, it might be in the equity holders’ best interest to liquidate the remainder of the collateral. Additionally, like the underlying TruPS collateral, bank TruPS CDO liabilities have tightened in considerably since 2001 as much of the new-issue premium has dissipated and secondary liquidity has improved for the asset class. The last row of Exhibit 206 shows the spread difference between recent TruPS CDOs and those of 2001 and 2002, a savings of 78 bps and 59 bps, respectively, for the transaction. In Exhibit 207, we provide a list of 2001 and 2002 vintage bank TruPS CDOs with a few attributes.

226


Please see "Trust Preferred CDO Performance Update", Fitch Ratings, March 1, 2005.

198

31 March 2006

Exhibit 207: 2001 and 2002 vintage bank trust preferred CDOs Issue Name Preferred Term Securities II MMCapS Funding I MM Community Funding Preferred Term Securities III MM Community Funding II Preferred Term Securities IV Preferred Term Securities V MM Community Funding III Preferred Term Securities VI TPerf Funding I Preferred Term Securities VII TPref Funding II Trapeza CDO I TPref Funding III Preferred Term Securities VIII

Amt % New % 2ndary % Subord. ($mm) Pricing Date Issue TruPS TruPS Debt $347 2/9/2001 97.04% 2.96% 0.00% $294 3/21/2001 NA NA NA $525 6/28/2001 100.00% 0.00% 0.00% $516 7/16/2001 93.84% 6.16% 0.00% $766 11/15/2001 84.62% 5.05% 10.32% $927 12/4/2001 98.00% 0.00% 2.00% $564 3/14/2002 94.54% 2.83% 2.63% $540 3/26/2002 94.79% 5.21% 0.00% $554 6/24/2002 100.00% 0.00% 0.00% $492 7/11/2002 94.52% 5.48% 0.00% $532 9/18/2002 95.01% 0.00% 4.99% $578 10/16/2002 89.80% 5.27% 4.93% $337 10/25/2002 79.53% 20.47% 0.00% $372 12/11/2002 89.25% 7.93% 2.82% $534 12/19/2002 80.19% 9.00% 10.81%

WAC 8.85% NA 10.25% 8.75% 9.79% 9.88% 10.46% 9.13% n/a 9.21% n/a 9.65% 8.34% 9.05% 8.68%

WAS 4.10% NA 3.75% 3.92% 3.75% 3.60% 3.60% 3.70% 3.45% 3.63% 3.40% 3.45% 3.38% 3.34% 3.24%

% Fixed % Floating 2.96% 97.04% NA NA 45.00% 55.00% 18.09% 81.91% 16.41% 83.59% 1.70% 98.30% 2.83% 97.17% 4.63% 95.37% 0.00% 100.00% 4.47% 95.53% 0.00% 100.00% 0.73% 99.27% 14.86% 85.14% 6.23% 93.77% 7.62% 92.38%

Static of Managed Static Static Static Static Static Static Static Static Static Static Static Static Managed Static Static

Source: Credit Suisse, Fitch , Moody’s, trustee reports

Numerical Example Here, we use a sample bank TruPS CDO from 2001 to illustrate the impact of calling/refinancing the underlying trust preferred securities on the valuation of the CDO. The CDO is a static deal priced in November 2001 with semiannual payments, the first of which was in June 2002. Exhibit 208 shows the capital structure and some characteristics of this sample deal.

Exhibit 208: Sample TruPS CDO Tranche A B Equity Auction-Call WAS

Rating Aaa A3

Coupon 6M LIBOR + 100 6M LIBOR + 220

Stated Maturity 12/15/31 12/15/31

10 years 6M LIBOR + 375

End of Non-Call/1st Call WAC

December 2006 9.89%

Source: CREDIT SUISSE, Intex

The composition of the collateral of this deal is very simple, as it was pool issued: all floating securities share the same coupon spread of 6M LIBOR + 375 bps and almost all fixed securities share the same fixed coupon of 9.95% with one exception. The non-call period of the underlying securities and the CDO is the same: December 2006, or five years after closing.227 Currently, new issue Aaa TruPS CDO is priced at about L+ 33 bps and A3 is priced at around L+140 bps. If priced to the auction-call date and at these DM levels, Tranche A would be priced at $103.37 and Tranche B would be priced at $104.14 (see Exhibit 209). However, as we discussed previously, it is rational to believe, and very likely, that the entire collateral may be called/prepaid once the non-call period is over. As a result, the CDO may terminate in December 2006 and thus the tranches should be priced to this date instead of the auction-call date. Assuming the same DM levels, now the fair prices would be significantly lower: Tranche A at $100.71 and Tranche B at $100.88. This illustrates how tranches may be over-valued if priced to the auction-call date if it is very likely that the CDO could be terminated much earlier – at the end of non-call date. 227

Some deals may have more complicated collateral compositions: more seasoned/secondary trust preferred securities and less homogeneous. The entire collateral pool may not necessarily be called/prepaid at the same time, but the idea and analytics are similar. Chapter 3. Trust Preferred CDOs

199

31 March 2006

However, even when priced to the end of the non-call (December 2006), we think it is still a very attractive trade. Take Tranche A as an example: one can earn L+33 bps on a very short AAA bond with WAL of about 1.1 years.

Exhibit 209: Comparison of valuations: priced to different dates Scenarios

Tranche

DM (bps)

Fair Price

WAL

Priced to 12/2011

A B

33 140

$103.37 $104.14

5.77 6.15

Priced to 12/2006

A B

33 140

$100.71 $100.88

1.10 1.15

Source: CREDIT SUISSE, Intex

Summary In closing, we anticipate a surge in prepayments of early vintage bank trust preferred securities in the next 24 months, as the securities exit their five-year non-call periods and the cost savings to bank issuers are very attractive. Furthermore, the unique position of bank TruPS CDO arrangers/issuers may pave the way for a spike in CDO issuance as well. Investors in the asset class should be aware of potential pricing inaccuracies in valuating bank TruPS CDOs. While future cash flows are effectively cut short by the underlying collateral redemptions, we believe that vintage TruPS CDO tranches still offer considerable value given their relatively high spread over a shorter average life.


200

31 March 2006



201

31 March 2006

Secondary Valuation Models of Cash Flow CDOs – Review and Pitfalls228 The secondary CDO market has seen tremendous growth in recent years. However, valuating seasoned/secondary CDO tranches remains a major challenge confronting CDO investors. Several valuation models exist in the market with each bearing its own pros and cons. We review several popular valuation approaches to secondary cash flow CDO analysis and comment on their pitfalls. We think it is important for investors to understand the nuances of each model and hope this commentary helps foster the development of better valuation technologies.

General Approaches to Asset Valuation In finance, regardless of the asset class under analysis, there are generally 3 basic approaches to valuation: 1.

Market comparability approach. This approach derives the value of the target asset from comparable assets with similar characteristics. An example is real estate property appraisals, which base target house values on similar houses in the same neighborhood. This approach is most suitable for illiquid assets.

2.

Adjusted discount factor approach. The key to this approach is to determine a risk premium such that future cash flows are discounted at the risk-adjusted rate. The resulting present value is the asset value. A simple example is a corporate bond. We discount future coupon and principal payments at a rate incorporating a credit spread commensurate with the credit risk for this bond. Obviously, the challenges with this approach include finding the right risk premium and separating the liquidity premium from the risk premium.

3.

Adjusted cash flow approach. Also known as the “risk-neutral” valuation, the idea behind this approach is to assign probabilities – of receiving or not receiving – to future cash flows, in order to make the investor indifferent between investing in this risky asset and a risk-free asset. If we discount the probability-weighted cash flows at the risk-free rate, the present value will be the value of the asset. The key here is to find the “probabilities” – also called “risk neutral probabilities.” The famous Black-Sholes Model of option pricing is essentially built upon this approach.

As we will show later, many of the valuation approaches we discuss here can find their roots in one of these three basic approaches.

Laying Out The Questions First and foremost, we lay out some common questions posed by secondary CDO market participants in making relative value decisions. These include:

228

1.

Within the same CDO deal, which part of the capital structure offers the best value?

2.

Within the same CDO sector, such as mezzanine SF CDOs, and rating category, which tranche offers the best value?

3.

Across different types of CDOs, which type offers the best value – for example, a BBB-rated mezzanine SF CDO tranche versus a BBB-rated CLO tranche?

This section was originally published in "The CDO Strategist", Issue #14, February 16, 2006.


202

31 March 2006

In traditional finance theory, such as CAPM, investors make investment decisions by comparing expected return versus a risk measurement – typically the standard deviation or variance of the return. Measurements based on this kind of mean-variance analysis, such as the Sharpe Ratio – calculated as the ratio of excess return over the standard deviation of return – are widely used, especially in equity investment. For CDOs however, this approach may not work mainly because of the following two reasons: 1.

The mean-variance analysis is based on the assumption that returns follow a normal distribution. For fixed income securities, especially CDOs, this is hardly the case.

2.

Even if we can assume the normal distribution, there is insufficient return data to calculate any meaningful risk measurements, given that the CDO market is still relatively new and information is not very transparent.

In turn, investors have taken alternative approaches to valuation. We discuss these in the next section.

Existing Valuation Models of Secondary CF CDOs Approach 1 – Comparing Spreads Spread comparison is probably the most widely-used and easiest valuation approach. Two popular methodologies compare spreads across different CDO types, as shown in Exhibit 210, and relative to historical means, as shown in Exhibit 211 where historical spreads of the BBB tranche of mezzanine SF CDOs are used. Based on the credit curves in Exhibit 210, AAA spread levels across different CDO sectors are similar, while A and BBB spread levels show wider dispersion.229 For example, the BBB tranche of mezzanine SF CDOs has the widest spread at L+350 bps, followed by high grade SF CDOs and bank trust preferred CDOs, while BBB CLO tranches offer the tightest spread at L+180bps. Market participants often make the argument that one asset type offers relative “spread pick-up” versus another type. In this case, can we argue that mezzanine SF CDOs offers the best value at BBB level? The answer is not so obvious. Why? Because this approach fails to address one very important variable – the risk. The rating only reflects the level of expected default and loss coverage. It does not necessarily reflect the “volatility” of the default risk and loss rate, i.e., it does not tell how likely the “realized” defaults/losses will miss the expected numbers. Plus, not all ratings are created equal – different collateral have different characteristics and different deals have unique structures.

229 We use new-issue spreads to make our points even though we are addressing issues in secondary valuation. Certainly we can use secondary spreads instead.


203

31 March 2006

Exhibit 210: CDO Credit Curves by rating (as of the end of January 2006) 350 300

Spread (bps)

250 200 150 100 50 0 Sr. AAA

Jr. AAA CLO

AA

MZ SF CDO

A

HG SF CDO

CRE CDO

BBB BTRUPS CDO


Exhibit 211: Historical spreads of BBB tranche of MZ SF CDOs 360

BBB MZ SF CDO Spread (bps)

340 320

Hist Avg + 1 Std. Dev.

300 280

Historical Average Spread

260 240 220

12/7/05

9/7/05

6/7/05

3/7/05

12/7/04

9/7/04

6/7/04

3/7/04

12/7/03

9/7/03

6/7/03

3/7/03

12/7/02

9/7/02

6/7/02

3/7/02

12/7/01

9/7/01

200


Comparing current spreads versus historical levels is another popular approach. The underlying premise for this approach is, over the long run, value – or in this case, spread – will revert to its long-term mean. Exhibit 211 suggests the BBB tranche of mezzanine SF CDOs currently looks cheap as its level is higher than the historical average. In addition, to make the argument more compelling, the level is even higher than the historical average plus one standard deviation of historical spreads. However, this approach fails to address some risk factors, such as the risk characteristics of the underlying collateral changing over time due to changes in collateral composition, and forward-looking factors, such as future US housing prices.


204

31 March 2006

Therefore simply comparing spreads should be performed on a first-cut analysis; more indepth and rigorous analysis is needed. Approach 2 – NAV-based Analysis NAV, or “Net Asset Value”, is probably the most widely used concept in secondary CDO valuations. The idea is simple: NAV is the market value of the CDO collateral minus any hedging costs and the outstanding balance of the notes senior to the target tranche. We show the NAV calculation of a very distressed seasoned SF CDO in Exhibit 212: the average market value of the underlying portfolio is 90 cents on the dollar. NAV is expressed in both a dollar amount and as a percentage of the outstanding balance of the tranche. For the AAA tranche, the $ NAV is the same as the net market value of the collateral, or 108% of its outstanding balance, while for the BBB tranche the % NAV is only 3%. These “liquidation prices” may be considered as the upper limit of the price for these tranches. We also show MV (market value) OC which is also often used by traders in the secondary market.

Exhibit 212: Calculation of NAV (1) Total Collateral Par (2) Weighted Average Market Price (3) Market Value of Collateral (4) Swap (5) Net MV

$

278,949,670

$ $ $

90.00% 251,054,703 (10,781,253) 240,273,450

Tranche Name

(1) X (2) (3) + (4)

Original Balance

Current Balance Rating

NAV ($)

NAV (%) MV OC

A

$

248,000,000

$

221,665,195

Aaa $

240,273,450

108%

108%

B C Equity

$ $ $

18,000,000 22,000,000 12,000,000

$ $ $

18,000,000 22,000,000 12,000,000

Aa2 $ Baa2 $

18,608,255 608,255

103% 3%

100% 92%


The NAV-based analysis is straightforward and intuitive, however, it has the following shortcomings: 1) It may be difficult to get accurate collateral market value, especially for distressed and illiquid assets; 2) The value of the tranche derived from NAV analysis may not be realistic, because to liquidate the entire deal requires the proceeds be sufficient to pay down all outstanding notes at par. The rule of thumb is the NAV analysis is relatively more reliable for first-priority notes. Approach 3 – Cash Flow-based Analysis All cash flow-based approaches start with generating future cash flows on the collateral side based on certain sets of assumptions on parameters such as prepayment, default, recovery, and reinvestment rate (for managed deals still in the reinvestment period). There are usually two levels for this exercise: 1.

At the asset level. For example, we assign assumptions on each home equity bond in a SF CDO. If a constant default rate is used, this number is called the CADR (constant annual default rate) and it is widely used by Wall Street dealers;

2.

At the underlying loan level, each home equity loan in the underlying pool for each home equity bond is assigned certain prepayment, default and recovery assumptions. The loan-level analysis offers better accuracy, however at the cost of longer computing time and power.

Once the cash flows of the underlying collateral are generated, the next step is to generate cash flows of the CDO tranches based on the deal structure and waterfall. Thanks to the growing usage of analytical packages such as Intex, conducting cash flow analysis is straightforward and no longer a daunting task.


205

31 March 2006

Once the cash flows are generated, a price-yield analysis follows: for floating bonds, the discount margin (DM) – a spread over forward LIBOR curve, at which future cash flows are discounted to be equated to the price of the bond – is usually used. The higher the DM, the better the investment at a particular price. Or, if there is a targeted DM, it is used to calculate the present value of future cash flows; the sum of which is the bond price. This is essentially the same approach as the “Adjusted Discount Factor Approach” introduced earlier. However, the question remains: what is the right DM or risk spread to use? The most common practice is to use the new-issue spread. Exhibit 213 shows an example of a BBB-rated CLO tranche. The original coupon spread of this bond is LIBOR + 250bps, while the current new-issue spread is about LIBOR + 180bps. Using 180bps as the DM, the price of this bond is $105.19. 230 If this price is actually traded in the market, then on a mark-to-market basis, this bond has appreciated about 5 points. However, this type of analysis has two weaknesses: 1. Simply applying the generic new-issue spread level to all bonds does not capture the uniqueness of each CDO deal. It seems relatively reasonable for pristine deals whose underlying collateral have no credit issues but misleading for others. Even for pristine deals, it would be difficult to concludes that they should all be trading at the same spread. 2.

Between two bonds trading at different DM’s, can we just pick the one with the higher DM? Unfortunately, there is still something missing: the risk factor.

Exhibit 213: Price-Yield Analysis based on Cash Flows General Information Type

DM (bps)

Price ($)*

HY CLO

160

106.72

Vintage

2004

180

105.19

Rating

Baa

200

103.67

Coupon

3-M LIBOR+250 bps

220

102.17

Current Baa Spread of HY CLO (as of Jan 2006)

3-M LIBOR+180 bps

240

100.72

250

100.00

Main Assumptions Variable CPR CDR Recovery Rate

Bond

Loan

5%

20%

2%

2%

30%

75%

Source: Credit Suisse * Priced to maturity

One popular approach to solve the second issue is to use the so-called sensitivity or scenario analysis. In Exhibit 214, we compare two DM profiles against different CADR scenarios: a BBB CLO tranche versus a seasoned (2004) BBB mezzanine SF CDO tranche. It is harder to simply pick the bond with the higher DM, as risk factors are considered via different CADRs. The SF CDO tranche offers higher DM at lower CADR but the DM drops when 4% CADR is reached – much earlier than the CLO tranche, whose DM – albeit lower – does not drop until around 9% CADR. The decision to use which CADR is contingent on one’s estimation on the default risk of the underlying collateral. 230

Also note that the DM at par is the same as the original coupon spread of 250 bps.


206

31 March 2006

One closely-related concept is the “Break-even CADR”, which is either a default rate causing the first break in yield/DM – below the coupon yield/spread – or a default rate resulting in zero yield. The Break-even CADR may be one potential candidate for risk measurement, similar to using variance to measure risk in traditional portfolio theory. If so, the reasoning is as follows: given the same expected returns – as measured as DM – the bond with the higher break-even default rate is more attractive. What if one bond offers a higher DM but has lower Break-even CADR? Again, the default risk needs to be estimated for the underlying collateral to answer this question. Approach 4 – Implied Multiplier Analysis The Implied Multiplier approach is just one step further than the “break-even” analysis we just discussed in Approach #3. The first step is to derive the expected default/loss rate, usually from historical default and recovery statistics of each asset type. The “multiplier” may be expressed as the ratio of the break-even CADR over the expected default rate. This approach helps make comparisons across different CDO types. Aside from all the shortcomings associated with the cash flow-based approach mentioned previously, the multiplier approach has some additional problems of its own: historical default rates may not be correctly calculated – yes, even at an aggregate level – and they may not reflect future risk factors. Another pitfall is, although the break-even CADR is different for different tranches of a CDO deal, the expected default rate based on historical experiences is the same for the entire underlying collateral. In other words, within the same CDO structure, the multiplier of a higher-rated tranche is always higher than that of lower-rated tranche. Therefore, it can not be used to assess relative value of tranches with different ratings within the same deal. Approach 5 – IRR Analysis for Equity Tranches Equity valuation is arguably one of the biggest challenges in secondary valuation. Internal Rate of Return (IRR) analysis is the most common way to evaluate an investment in an equity tranche. The first step is nearly identical to the aforementioned cash flow-based approach, the only difference is the cash flows of the equity tranche are used. The IRR is calculated from the resulting cash flows and is usually tested against different assumptions used on the underlying collateral, such as the CADR.231 As an example, we picked one CLO equity tranche and one mezzanine SF CDO equity tranche – both issued in late 2004 – and show their equity IRR profiles in Exhibit 215. In this case, the decision is fairly straightforward: the CLO equity seems to be a better investment as its maximum IRR is similar to that of SF CDO equity, while also holding up much better than the IRR of the SF CDO through various CADR scenarios.

231

Same kind of analysis can be found in almost all equity marketing books of new-issue CDOs.


207

31 March 2006

Exhibit 214: DM versus CADR – comparison of BBB SF CDO vs. BBB CLO tranches 400

BBB SF CDO tranche

300 Discount Margin (DM, bps)

BBB CLO tranche 200 100 0 -100 -200 -300 0

1

2

3

4

5

6

7

8

9

10

CADR (%) Source: Credit Suisse

The result is not surprising, however, as the tight spread environment and shrinking arbitrage across most CDO asset classes in 2004-2005 forced similar – among CLOs and HG SF CDOs – baseline IRR’s to around the low teens. If defaults rise in tandem for both the leveraged loan and ABS (mostly subprime home equity) markets, the higher recovery rates of leveraged loans suggest CLO equity will out-perform SF CDO equity. In order for SF CDO equity to be more attractive, it has to have a higher baseline IRR. The pitfall here resides in the different leverage ratios: it is difficult to compare two IRR profiles as – when keeping all else equal – the one with higher leverage will always have a steeper profile. Thus we may have a similar dilemma as the one shown in Exhibit 215. The same question emerges: how do we balance the trade-off? Investors sometimes wish to express the value of the equity tranche as the present value of future cash flows. The challenge again is to determine the right discount rate and the most common solution is to use the current market expected equity IRR of new-issue CDOs with similar characteristics as the target deal. One important thing to keep in mind is that, as time goes by, the value of the equity tranche – expressed as a percentage of its original balance – will always go down even without any credit deterioration, given its IOlike nature and pay-down over time. This approach shares all the shortcomings we raised regarding the cash flow-based approach.


208

31 March 2006

Exhibit 215: IRR analysis of equity tranches* 2 0 .0 0 1 5 .0 0

E quity of a s am ple CLO

1 0 .0 0

IRR (%)

5 .0 0 0 .0 0 -5 .0 0

E quity of a s am ple M Z S F CDO

-1 0 .0 0 -1 5 .0 0 0

0 .2 5

0 .5

0 .7 5

1

1 .2 5

1 .5

2

2 .5

3

3 .5

4

4 .5

C AD R (% ) Source: Credit Suisse * The 2 sample CDOs are both 2004 vintage deals. The recovery rate assumed for CLO is 75% and it is 50% for SF CDO.

Approach 6 – Simulation-based Approach CADR-based analysis ignores default timing and the impact of correlation. Since the value of CDO tranches is path-dependent, the timing of defaults and losses could have significant impact on the final price. Loan-level analysis (for SF CDOs, for example) can, to some extent, mitigate this issue as the assumed prepayment and default curves would dictate the timing of bond defaults. However, loan-level analysis considers only one particular scenario, ignoring the full spectrum of risk factors. While we discussed the use of scenario or sensitivity analysis to gauge the risk factor, these scenarios could be arbitrarily specified and may not reflect reality. As we discussed at the beginning of this section, one of the main valuation approach in finance is the so-called “Adjusted Cash Flow” approach – or sometimes called “Risk Neutral Valuation”. The fair value of a CDO tranche can be computed as the risk-neutral expectation of its discounted cash flows. The key to this type of analysis is to derive the “market implied” default probability. And the structural complexity and path-dependent nature of cash CDOs turns our attention to Monte Carlo simulation for a solution. The main steps for the simulation process can be summarized as follows: 1.

Derive market-implied default probabilities/intensities from market prices/spreads for underlying assets.

2.

Specify a dependence structure – i.e., correlation structure – of either asset returns or default occurrences, and estimate the parameters such as asset correlations or default correlation.

3.

Simulate the default timing of the collateral assets.

4.

Run cash flow model to generate discounted cash flows for each default path.

5.

Use the discounted cash flows from thousands of paths to estimate the fair value of the subject bond, including the standard error of the estimation.

This framework works relatively well for CDOs backed by corporate bonds or loans. However, for SF CDOs or CRE CDOs, it is still an open topic as to how to conduct similar analysis. Maybe with the development of the CDS market, it will help to derive the market implied default probabilities of SF and CMBS securities.


209

31 March 2006

Approach 7 – Re-rating Approach While the re-rating process is more widely used for monitoring an existing CDO portfolio – such as managing a CDO^2 deal – it can also be used for relative value analysis. To re-rate CDO tranches based on an in-house rating system, a typical process may look like the following: 1.

Collect market prices of the underlying assets and calculate the cost/value of hedges – this is very similar to the NAV approach.

2.

Pay close attention to distressed assets – those already rated “CCC” and below, or assets trading at distressed levels. If necessary, certain haircuts may be applied, or distressed assets will be assumed to be liquidated at market price.

3.

For assets on negative watch list by any rating agency, notch the rating down.

4.

Certain reinvestment assumptions have to be made on the principal proceeds and proceeds from liquidation of distressed assets.

5.

If necessary, an in-house criteria can be used to classify the underlying assets into different industry category, which may not be exactly the same as the rating agencies’. The difference may cause discrepancy in ratings as different industry groups have different correlation assumptions.

6.

Re-rate the subject bond using rating agencies’ models based on aforementioned assumptions.

Once the rating is determined, it could be incorporated into the decision process of relative value and predicting future rating actions. Approach 8 – Option-like Approach For many distressed CDO tranches in the secondary market, sometimes it is useful to treat them like options. Take a mezzanine tranche of a very distressed SF CDO as an example. The tranche is PIK-able: as the coverage tests have been breached substantially, all the interest – after paying the coupon on non-PIK-able tranches – is captured to repay the principal of the senior most class in the capital structure. We can split this mezzanine tranche into a PO and an IO piece. In this case, the likelihood of receiving any future interest cash flow is very low and the IO piece is probably worthless. However, the PO might be worth something. It can be thought of as an out-of-money call option. Given that the size of these mezzanine tranches tend to be relatively small compared to the entire deal, it does not take too much reduction in the realized default/loss rates in order to go from getting paid nothing to being paid in full in principal. An estimation of the value of this option can be made if we can figure out the probabilities of various loss rates and then calculate the probability-weighted principal payment to the bond. The price can be viewed as the premium for the option. A simulation-based approach can also be adopted.


210

31 March 2006

Other Considerations in Secondary Valuation There are many other factors investors need to consider when making investment decisions in the secondary market. We focus on the two important ones: call probability and the CDO manager’s expertise in managing the CDO. Throughout our discussion we assumed the CDO tranches are priced to the legal maturity date. However, there are two very important call features in CDO structures: the optional redemption by equity investors and the mandatory auction call. The exercise of either call option can dramatically change the fair value and average life of a bond. Imagine an investor buys a floating CDO tranche at a premium priced to maturity, if this deal gets called by the equity holders after the non-call period and the bond gets paid off at par, the investor will lose the premium paid on the bond. So it is very important to estimate the probability and timing of the call when evaluating the CDO tranche. We have discussed the optional redemption and auction call in our previous CDO Strategist and we encourage our readers to review it.232 The second issue we want to discuss is the CDO manager. Manager performance and selection are intriguing issues. We believe managers add value to the CDO investment. However, evaluating a manager’s capabilities and separating the good ones from the mediocre ones is no easy task, especially for SF CDO managers given the relatively short history of past performance data. We think the “manager effect” is probably more relevant for performing and slightly stressed deals, but not so much for very distressed deals, as all the restrictions and rules embedded in the indenture will probably restrain the manager from doing anything at all. Nevertheless, we think it is important to take the manager into the consideration of CDO value.

Closing Thoughts The growing challenge of using the right risk measurement in CDO analysis becomes increasingly important as the secondary market expands from a handful of players to an active fixture in the bond markets. Based on our discussion, several potential candidates for valuation could be considered such as: break-even CADR and the Implied Multiplier of break-even CADR over the expected default rate. However, each model has its own pitfalls and nuances. Before improvements and advancements in valuation technologies can be developed in the future, we encourage investors to fully understand the nuances of these methodologies and incorporate them into the valuation process.

232

Please refer to The CDO Strategist, May 31, 2005 and The CDO Strategist, July 28, 2005.


211

31 March 2006

2003 Vintage Mezz. SF CDOs – One of a Kind233 What Makes the 2003 Vintage Special? We think the 2003 vintage of mezzanine SF CDOs offer unique risk-return profiles because of the following collateral and structural features:234 235 1.

Limited exposure to “troubled” ABS sectors;

2.

Wider (or Attractive) spreads on both asset and liability sides ;

3.

Limited share of non-traditional and higher levered mortgage products such as IO loans; and

4.

Relatively modest concentration of residential mortgage loans originated in higher price growth areas.

On a risk-adjusted basis, we think 2003 vintage of mezzanine SF CDOs are attractive to secondary CDO investors. Exhibit 216 details a general profile of the 2003 SF CDO deals used in our analysis. We discuss each point in more detail.

The underlying collateral – limited exposure to troubled ABS sectors In CDO investing, picking the right asset classes is the most important step. It is wellknown that many older vintage mezzanine SF CDOs (1999-2002) suffered downgrades and losses because of significant exposure to “troubled” sectors such as manufactured housing, aircraft leasing, etc. Since 2003, the diversity of SF CDO collateral has decreased and there has been a shift in the composition - from highly diversified pools with “troubled” sectors to more concentrated pools with mortgage-related assets. This trend is illustrated in Exhibit 217; most 2003 vintage deals don’t have significant exposure to sectors such as MH and aircraft leasing, with the exception of deals such as Deal 13. 236 Before 2003, on average, SF CDO collateral included around 10% MH and 4-5% aircraft leasing. On the other hand, for most of the 2003 vintage mezzanine SF CDOs, the exposure to residential mortgage-related assets, residential B&C mortgage and home equity and residential A mortgage combined, jumped significantly.237 As shown in Exhibit 217 more than half of the deals have greater than 50% exposure to residential B&C and home equity collateral. 238 Combined with residential A, the total exposure could reach close to 90%, such as Deal 6. In earlier vintages, the share is around 20% on average.

233

This section was originally published in "The CDO Strategist", Issue #5, July 15, 2005. The SF CDOs discussed include only mezzanine, multi-sector SF CDOs, excluding high-grade SF CDOs, CRE (or CMBS) CDOs, and CDO-Squared. 235 The term, "2003 vintage mezz. SF CDOs", represents a group of CDO deals with specific characteristics and not just a time frame. For example, if a deal is done in late 2002 or early 2004 but contains similar characteristics as discussed, our arguments can be applied to it as well. 236 To date, Deal 13 is the only one that has been downgraded by any of the rating agencies. 237 We combine residential B&C mortgage and home equity in our discussion as there was some confusion in the market regarding the classification of these two sectors, and so we use “home equity” for convenience. Please see CSFB special report, “Classification Conundrum: Residential Mortgage Classifications in SF CDOs”, December 23, 2004. 238 This number could be even higher for more recent deals, such as 2004 and 2005 vintages. 234


212

31 March 2006

Exhibit 216: General Profile of 2003 Vintage SF CDOs* Deal Deal 1 Deal 2 Deal 3 Deal 4 Deal 5 Deal 6 Deal 7 Deal 8 Deal 9 Deal 10 Deal 11 Deal 12 Deal 13 Deal 14 Deal 15 Deal 16 Deal 17 Deal 18 Deal 19 Deal 20

Closing Date May-03 Nov-03 Jul-03 Sep-03 Jan-03 Aug-03 Aug-03 Oct-03 Jul-03 Jun-03 Jan-03 Jun-03 Dec-03 Nov-03 Nov-03 Dec-03 May-03 Feb-03 Jul-03 Oct-03

Static/ Managed

Minimum Diversity-Score

Managed Managed Managed Managed Managed Managed Static Managed Static Managed Managed Managed

18 19 16 25 16 15 16 20

Managed Managed Managed Managed Managed Managed Managed

24 16 15 18 18 20 20

22 21 20

Original WAR

Turbo

Equity Cap

Reinvestment Period

Non-Call Period

Baa1/Baa2 Baa1/Baa2 Baa1/Baa2 Baa2/Baa3 A3 A3/Baa1 Baa1 Baa2 A3 Baa3 Baa2/Baa3 Baa1/Baa2 Baa1/Baa2 Baa2/Baa3 Baa1/Baa2 Baa1/Baa2 Baa1/Baa2 Baa1/Baa2 Baa2 Baa1

Y

18.0%

Y N Y

23.0%

Y N Y Y Y N Y Y Y Y

18.0%

48 48 36 60 36 36 36 48 108 36 36 48

Y

20.0%

48 48 36 42 36 36 0 48 0 36 48 48 0 24 36 36 36 36 48 60

10.0% 25.0%

14.0% 23.0% 16.0%

36 36 36 36 36 48

Source: Credit Suisse, Intex, Moody’s, S&P, Fitch * The SF CDOs listed here only include mezzanine, multi-sector SF CDOs, while excluding high-grade SF CDOs, CRE (or CMBS) or real estate CDOs, and CDO-Squared.

The macro economic condition – high spread environment In 2003, HEL spreads were at their widest levels in the last 5 years. As shown in Exhibit 218, 5-year BBB spreads started widening in the second half of 2002, reaching a high of LIBOR + 350 bps, before retreating to 160-170 bps in the second half of 2003. We believe most of the tightening is attributed to the CDO bid; most deals in Exhibit 216 closed in the second half of 2003.239 As most HEL bonds in 2003 vintage SF CDOs are issued in late 2002 or in 2003, the wide spread provides an attractive return on the asset side of a CDO. In addition, the liability spread of SF CDOs was similarly wide, in tandem with the asset side. However, the arbitrage spread was also at its historic high for SF CDOs (Exhibit 218). Based on CREDIT SUISSE’s excess spread measure, the Multi-Sector Arbitrage Pointer (or MAP), as shown in Exhibit 219, the arbitrage spread for equity holders was twice the current level.240 Wider spreads on the underlying assets also reduced the incentive for CDOs to move down the credit spectrum to Baa3 and below, which represent greater risks, such as rising interest rates and slowing-down in the housing market.

239 240

It normally takes 6 to 12 weeks between warehousing and deal closing. Please note MAP does not consider default and is only for indicative purposes.


213

31 March 2006

Exhibit 217: Original Collateral Allocation of 2003 Vintage SF CDOs

Deal Deal 1 Deal 2 Deal 3 Deal 4 Deal 5 Deal 6 Deal 7 Deal 8 Deal 9 Deal 10 Deal 11 Deal 12 Deal 13 Deal 14 Deal 15 Deal 16 Deal 17 Deal 18 Deal 19 Deal 20

Residential B&C + Home Equity Residential A 54.8% 57.8% 46.4% 31.5% 56.9% 59.5% 55.0% 58.8% 38.9% 54.6% 49.8% 37.7% 40.9% 54.7% 54.3% 56.2% 57.1% 47.2% 50.4% 32.7%

10.67% 14.3% 15.5% 14.6% 28.5% 27.4% 15.9% 11.0% 19.7% 14.6% 10.2% 16.8% 6.8% 11.0% 5.4% 18.2% 9.4% 13.1% 15.6% 7.8%

MH

Aircraft Leasing

CBO

CMBS

Corporate

Auto & Credit Card

1.85% 0.0% 5.1% 3.3% 9.8% 1.8% 0.0% 0.0% 5.0% 7.8% 6.7% 2.3% 12.1% 0.8% 0.0% 0.0% 4.1% 6.9% 0.0% 0.5%

1.3% 0.0% 0.0% 1.7% 0.0% 0.0% 0.0% 0.0% 1.0% 0.0% 6.6% 0.8% 5.1% 0.9% 0.0% 0.0% 0.0% 0.0% 0.0% 1.1%

5.1% 8.6% 4.9% 7.5% 0.0% 1.8% 1.0% 5.6% 5.1% 5.0% 8.3% 10.9% 10.3% 1.5% 22.8% 4.9% 3.6% 4.0% 7.0% 9.6%

3.8% 9.1% 9.1% 13.6% 0.3% 1.7% 7.4% 16.9% 15.0% 10.3% 5.7% 10.1% 8.8% 13.1% 1.1% 10.0% 4.0% 13.7% 7.9% 33.6%

3.4% 3.8% 0.0% 2.0% 3.0% 0.0% 0.0% 0.8% 1.0% 1.2% 6.0% 0.0% 0.0% 7.3% 0.0% 0.0% 7.9% 0.0% 0.0% 8.8%

16.9% 4.9% 10.4% 28.0% 0.0% 0.0% 9.2% 3.7% 9.8% 0.0% 9.1% 14.7% 14.1% 7.1% 2.53% 4.3% 3.1% 1.9% 3.4% 4.1%

Source: Credit Suisse, Intex, Moody’s, S&P, Fitch

Limited share of non-traditional and more levered mortgage products Compared to newer vintages HELs, HEL deals issued in 2003 do not have as large a share of IO (interest only) loans. Exhibit 217 shows the shares of IO loans of each vintage at an aggregate level. It is clear that in 2004 and 2005, the share of IO loans jumped dramatically: from 1-4% in 2002 and 2003 to 14% in 2003 and 21% in 2005, based on the composite. For investors concerned about high concentration risk of IO loans, 2003 vintage contains less exposure. Given the short history and limited empirical evidence of this product type, a track record of performance is still being established.241 In the prime mortgage and Alt-A universes, we see similar patterns. Although the IO share in these asset classes had already jumped to high levels in 2003, it is not as high as 2004 or later.242

241 For a detailed discussion on IO loans, please refer to CSFB special report, "Subprime Interest-Only Loans: Attributes and Early-Stage Performance", January 2005. 242 Please refer to CSFB special report, "Spotlight on Interest-Only Loans: Prime and Alt-A Fixed-Rate MBS", May 2005.


214

31 March 2006

90.00

400

80.00

350

SF CDO Liability Sread (bps)

70.00

300

60.00 250 50.00 200 40.00 150 30.00 100

20.00

50

10.00 0.00 Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05

5-Year HEL Spread over LIBOR (bps)

Exhibit 218: BBB HEL Spread vs. SF CDO Liability Spread

0

Date SF CDO Aggregate Liability Spread

5-Year HEL Floating Spread


Exhibit 219: Multi-Sector Arbitrage Pointer (MAP) 160 140 120

MAP

100 80 60 40 20 0 8/31/01

2/28/02

8/31/02

2/28/03

8/31/03

2/29/04

8/31/04

2/28/05


Relatively modest concentration of subprime loans generated in high HPA areas than more recent HEL deals Given the dramatic increase in US housing prices, the concentration of loans generated in higher Home Price Appreciation (HPA) areas rose significantly recently. Such a concentration may represent higher risks in the face of a housing market slow-down. Going forward, we believe a slower growth rate of housing prices could increase the loss severity rate of HEL loans significantly, as well as increase default and delinquency rates.


215

31 March 2006

Exhibit 220: Share of IO Loans* Vintage

Composite

2001

2002

2003

2004

2005

0%

1%

4%

14%

21%

Source: Credit Suisse, Intex * These figures are directly from CREDIT SUISSE’s “Subprime HEAT Update”, June 2005.

Exhibit 221: HPI % Change Annualized Quarterly (=Quarterly Growth*4) 25%

20%

15%

10%

5%

0% 1997Q1 1997Q4 1998Q3 1999Q2 2000Q1 2000Q4 2001Q3 2002Q2 2003Q1 2003Q4 2004Q3 Source: Credit Suisse, OFHEO, Bureau of Labor Statistics

As shown in Exhibit 221, the Housing Price Index (HPI) jumped dramatically around the end of 2003 to close to 14.4% and further up to 19.2% in 2004. Based on this evidence, we believe most HEL deals issued in late 2002 and 2003 should have moderate concentration of loans generated in high HPA areas relative to more recent deals, and thus less risk for 2003 vintage mezzanine SF CDOs.

Implications for secondary valuation Most secondary valuations should be done on a deal-by-deal basis, especially for SF CDOs given their heterogonous nature. However, the 2003 vintage possesses some unique characteristics. These attributes we discussed above have significant implications for secondary valuation and sensitivity analysis. Characteristics such as wider spreads on CDO liabilities imply higher return for CDO investors, holding everything else equal. Some factors, such as low exposure to troubled ABS sectors and low share of IO loans, imply lower risks in potential adverse scenario. Therefore, on a risk-adjusted basis, we think the 2003 vintage is attractive.243 For example, based on Moody’s index, the mezzanine OC cushion of 2003 vintage is the most stable among all vintages. Similar to wine collecting, this is one vintage you may not want to miss.

243

As we emphasize repeatedly, these conclusions are on an aggregate level. For certain deals, such as Deal 13 which is more like an older vintage deal, the performance profile may not be similar to the rest of the vintage. Chapter 4: Relative Value and Secondary CDO Market

216

31 March 2006

Finding Value in Senior Tranches of Distressed SF CDOs244 Since early 2004, SF CDO downgrades have increased. Most downgrades are from early vintage SF CDOs – the 1999 to 2001 vintages and select 2002 deals. The main driver for these downgrades is the poor performance of certain ABS sectors such as manufacturing housing (MH), aircraft leasing and franchise loans. We find 78% of 2000 vintage SF CDOs experience at least one downgrade; 58% and 30% of 2001 and 2002 vintages, respectively, have been downgraded.245 This doesn’t suggest bad news for all the SF CDO investors because it depends on the tranche. We believe the senior tranches from early vintages of SF CDOs may offer attractive value, especially if they are trading at a discount. We analyze an actual transaction to illustrate this opportunity. The deal was issued in 2001 and is currently failing all performance tests.

Exhibit 222: Distribution by Asset Type (Based on Balance as of 4/29/2005)

Recreation Vehicle 2% Receivables 6%

RMBS 11%

Airplane 11%

Auto Loans 3%

CDO 2%

NA 7%

Manufactured Housing 15%

CMBS 14%

Credit Card 6% Home Equity 18%

Franchise 4%

Equipment 1%


Exhibit 222 shows the asset allocation of this deal as of 4/29/2005. About 30% of the collateral is in a combination of MH, aircraft leasing and franchise loans. Exhibit 223 shows the rating distribution; the share of below-Caa1 is about 13%. Undoubtedly, this is a very distressed deal.

244 245

This section was originally published in "The CDO Strategist", Issue #3, June 15, 3005. Based on deal count and as of 6/10/2005.


217

31 March 2006

Exhibit 223: Distribution by Ratings (Based on Balance as of 4/29/2005) Caa1 0% Ca 3%

C 4%

Caa2 2% Caa3 4%

NA 3%

A1 1%

A2 5%

A3 0%

Aa2 2% Aa3 Aaa 1% 3%

B1 4% B3 8%

Baa3 18%

Ba2 5% Baa1 8% Baa2 26%


To generate the cash flows, we apply asset-level prepayment, default and recovery assumptions. One of the biggest challenges of evaluating seasoned SF CDO deals is to come up with these assumptions for esoteric and off-the-run asset types such as aircraft leasing and franchise loans. We rely on our internal models and expertise to generate prepayment, default and recovery assumptions for home equity, MH, RMBS, CMBS, auto, and credit card deals. For franchise loans or aircraft leasing, we used conservative assumptions: for franchise loans, we use a prepayment speed of 30% CPR, a default rate of 20% CDR, and a severity rate of 60%; for aircraft leasing, we assume no prepayment, a default rate of 80% CDR246 and a severity rate of 80%.247 By running these assumptions through Intex, we generate the cash flows for each tranche.

Exhibit 224: Capital Structure of the Sample Deal (as of 4/29/2005) Tranche A B C Equity

Original Balance

Current Balance

Original Moody's

Current Moody's

Coupon

OC Target

IC Target

177,500,000 50,000,000 12,500,000 12,000,000

100,843,494 50,000,000 11,952,287 12,000,000

Aaa Aa3 Baa2

Aaa Aa3 Baa2

L+48 L+100 L+168

105% 102%

117.50% 107.50%


Exhibit 224 shows the capital structure, the ratings of each tranche, and the OC/IC targets. This deal has an embedded Turbo structure: the return on the equity tranche is capped at 26.75% and any remaining interest proceeds are then used to pay down Classes C, B and A, in that order. This explains why Tranche C has paid down some principal while Tranche B has not. Also, the deal has exited the reinvestment period. Because of failing OC/IC tests, both interest and principal proceeds are redirected to pay down Tranche A until the tests are satisfied. As Exhibit 225 and Exhibit 226 show, the IC and OC tests will never be cured, based on the projected cash flows.

246

Most aircraft leasing bonds are rated CCC in this deal. Almost all of these franchise loans and aircraft leasing deals are not modeled by Intex. As a result, the assumption provided will be applied at the bond level, instead of at the underlying collateral level. 247


218

31 March 2006

Exhibit 225: Projected Class B IC Test

Exhibit 226: Projected Class B OC Test 120%

140% 120%

100%

100%

OC Ratio

IC Ratio

80% 80% 60%

40%

40%

20%

20% 0% Jan-04

60%

0% May-05

Oct-06

Feb-08

Jul-09

Threshold

Nov-10

Apr-12

Aug-13

Dec-14

May-16

Jan-04

May-05

Oct-06

Actual


Feb-08

Jul-09

Threshold

Nov-10

Apr-12

Aug-13

Dec-14

May-16

Actual


Because of the de-levering effect,248 even for a severely distressed deal like this, the Tranche A can still provide value. As Exhibit 227 indicates, even under very conservative assumptions, if traded at par, Tranche A can offer a discount margin of 48 bps over 3Month LIBOR, which is the same as its coupon spread. If traded at discount, this bond represent more attractive returns. For a bond with a WAL of 1.54 years, we view this is a good investment and believe many other senior tranches of seasoned and distressed SF CDOs may offer similar opportunities.

Exhibit 227: Price/Yield Table for Tranche A of Sample SF CDO Price

Yield (%)

Discount Margin (bps)

99 99.25 99.5 99.75 100 100.25 100.5 100.75

5.2271 5.0524 4.8785 4.7054 4.5332 4.3619 4.1914 4.0217

119 101 83 66 48 30 13 -5


248 The subordination level at the beginning of our analysis is about 42%, based on Table 1. As Class A continues to de-lever, the subordination level will get higher.


219

31 March 2006

Seasoned Senior CLOs Should Trade Even Tighter249 The Idea In the secondary market, many seasoned AAA-rated CLO bonds are trading at the same level as new-issue bonds, which stands at around LIBOR plus 25 bps. We think many bonds nearing the end of the non-call period (less than two years) with clean collateral should be trading at tighter levels.

Negative Basis Trade A negative basis trade occurs when the bond spread is trading wider than the credit default swap (CDS) spread (the cost of protection): one can capture the net spread by going long the cash bond and simultaneously hedging out the credit risk by buying protection through a CDS contract. Currently, the spread of a CDS on a AAA-rated CLO bond is a little under 10 bps. Investors can hedge out the counterparty (of the CDS) risk by buying additional protection against the counterparty’s default risk. If an investor buys the AAA bond offered at 25 bps and buys protection from a CDS at around 10 bps and additional insurance against counterparty risk, the investor is locking in a near-risk-free return of 13-15 bps over the next 7.5 to 8.5 years, the average life of typical new-issue AAA CLO bonds.

What Does This Mean For Seasoned AAA CLO Bonds? We think seasoned AAA-rated CLO bonds, with less than or equal to two years remaining in the non-call period, should trade close to the low-teen level, or at least tighter than the 25 bps level priced to the first call date. Our reasons for this belief are as follows: 1.

Given that the first call date is approaching within two years, these are very short bonds if called. Compared to a 7.5- to 8.5-year bond at 13-15 bps, a two-year or shorter bond at 25 bps is evidently very attractive.

2.

From a credit perspective, most of these CLO deals are performing well. Under normal conditions, it is unlikely that an AAA-rated bond from these currently wellperforming deals will result in losses in a very short time period.

3.

Even if these bonds are not called, it could be even better, assuming the credit situation does not deteriorate disastrously, as we will explain later.

An Example To back up our point, we use a real CLO deal as an example. Exhibit 228 shows the detailed information of this deal – a 2002 vintage CLO whose non-call period will end in two years. This deal, along with almost all the CLO deals in the same vintage, is performing well: it is passing all performance tests and the market value of the collateral is 101.4%.250

249 250

This section was originally published in "The CDO Strategist", Issue #4, June 29, 2005. Please refer to Moody's Deal Score Report, June 2005.


220

31 March 2006

Exhibit 228: Sample CLO Deal Deal Information Issue Date Reinvestment End Date Non-Call End Date Legal Maturity Total Size

10/1/02 7/15/07 7/15/07 10/15/16 450,000,000

WAC of Fixed Assets WAS of Floating Assets Floating Rate Assets Payment Frequency Market Price of Collateral

9.08% 3.03% 77.42% Quarterly 101.4%

Capital Structure Tranche Name

Current Balance

Spread/Coupon

Rating

346,000,000 15,250,000 24,000,000 11,000,000 6,000,000 13,000,000 34,750,000

L+44 bps L+140 bps 7.045% L+240 bps 8.055% 12.78%

Aaa A2 A2 Baa2 Baa2 Ba2

A B1 B2 C1 C2 D Equity

Expiration Date of Make-Whole Premium N/A N/A 4/15/2012 N/A 7/15/2012 1/29/2012 N/A

Base Case Assumptions Prepayment of HY Loans Default of HY Loans Recovery of HY Loans

15% CPR 0.5% CDR 70%

Prepayment of HY Bonds Default of HY Bonds Recovery of HY Bonds

5% CPR 2% CDR 30%


Using our call option model, we can determine whether a deal will be called or not on each call date from an economic perspective, and calculate the price at each call date as well as the price if never called.251

Exhibit 229: Cash Flows on the First Redemption Date Value Asset Notional (on redemption date) Market Price of Assets* Market Value of Assets (on redemption date) Swap Termination Payment (on redemption date) Principal and Premium to Liabilities Cash flow to Equity (on redemption date if called) IRR of Equity** PV of cash flow to equity on call date PV of cash flow to equity before call date Total PV of cash flow to equity if called Cash flow to Equity (on redemption date if not called) Total PV of cash flow to equity if not called To Call or Not to Call?

$450,578,483 $101.40 $456,886,582 ($1,218,128) ($421,288,570) $34,379,884 12.00% $27,052,134 $16,603,442 $43,655,576 $37,417,291 $46,045,588 Not Call

Source: Credit Suisse, INTEX * Assume dirty price with accrued interest for simplicity ** The current IRR available to equity holders from alternative investments

251 For a detailed discussion on CDO call options, please see our The CDO Strategist (Issue #2), May 31, 2005.


221

31 March 2006

Exhibit 230: Results of Base Case on the First Redemption Date Tranche Name A

B1

B2

C1

C2

D

(1) WAL of Tranche if no call

4.37

6.8

6.79

7.05

7.04

7.65

(2) (3) (4) (5) (6) (7)

2.04

2.04

2.04 5.0 96 3.69% 3.58% 3.69%

2.04

2.04 5.25 148 3.69% 3.58% 3.70%

2.04 4.75 389 3.66% 3.58% 3.70%

0.25%

0.75%

1.20%

1.80%

2.20%

5.15%

0.44%

1.40%

2.40%

346,000,000 346,000,000 318,594,460 28,718,781 347,313,241 $100.38 $100.79

15,250,000 15,250,000 13,901,979 1,541,284 15,443,263 $101.27 $103.91

7.05% 10.64% 24,000,000 26,554,593 24,145,315 3,206,626 27,351,941 $113.97 $112.69

8.06% 13.21% 6,000,000 6,792,326 6,055,348 906,618 6,961,966 $116.03 $112.63

12.78% 20.71% 13,000,000 15,691,651 13,201,475 3,018,718 16,220,192 $124.77 $122.07

(8) (9) (10) (11) (12) (13) (14) (15) (16) (17)

WAL of Tranche if called Remaining Maturity to Make-Whole Expiration Date (Year) Make-Whole Spread (bps) Treasury Rate for Make-Whole Premium (based on (3)) Treasury Rate for Pricing if Called (based on (2)) Treasury Rate for Pricing if No Call (based on (1)) Pricing Spread over LIBOR (for floating)/over Treasury (for fixed) Coupon Rate (Fix)/LIBOR Spread (Float) Make-Whole Premium Remaining Notional (on Redemption Date) Optional Redemption Payout = (11)*(1+(10)) PV of Optional Redemption Payout PV of cash flow before call Total PV of cash flow if called Price if called Price if not called

11,000,000 11,000,000 9,819,083 1,308,555 11,127,638 $101.16 $103.57


Priced at $100.38 to the first call date, the A tranche offers a discount margin (DM) over forward LIBOR of 25 bps with an average life of two years (see Exhibit 230). As discussed, this is attractive compared to where the negative basis trades are being done. We think it should be trading tighter. If priced to the first call date at 13 bps DM, the price should be $100.61. The above discussion is based on the assumption that the deal will be called on the first call date. How likely is it that this deal will actually be called? Based on the baseline assumptions and our model, it turns out that this deal will not be called on the first call date (see Exhibit 229).252 The good news is that the later the deal is called, the better. As a matter of fact, for floating bonds, as the call date moves closer to the maturity date, the price if called will converge up to the price if never called. As it turns out, economically, this deal should be called on 4/15/2009. If it does get called on this date, the AAA bond at $100.38 will give the investor a DM around 32 bps for a bond with 2.9-year average life.

Conclusion The risk is that the deal does not get called and something disastrous happens causing a loss on the AAA bond. However, even in our most stressed scenario,253 the AAA bond did not suffer any loss and still looks cheap at the 25 bps level. We believe seasoned AAA CLO bonds close to the end of the non-call period provide good value at the current pricing of LIBOR plus 25 bps.

252

Faster prepayment speeds and higher market price will increase the probability of call. For HY bonds: CDR at 15 and recovery at 25%; for HY loans: CDR at 8 and recovery at 50%. The CDRs used here are historical highs since 1992 and the recovery rates are historical lows since 1995. For more details on historical rates, please see CSFB’s Leveraged Finance Research, “An Introduction to Cash Flow CLOs”, May 3, 2005. 253


222

31 March 2006

Junior AAA of HG SF CDOs Offers Attractive Value254 Most investors are required to adhere to certain investment guidelines and eligibility criteria, which can vary by credit rating, sector, investment horizon and more. Therefore, we discuss relative value by risk/return profiles. And in this issue’s Strategy section, we focus on investors seeking AAA-rated assets with 7-9 year weighted average lives. We think the junior AAA tranches of high grade SF CDOs present some very attractive opportunities. In a typical HG SF CDO, there are usually two (or more) AAA-rated tranches: the seniorAAA and the junior-AAA. The senior-AAA usually accounts for 70%-90% of the deal and is funded either as short-term notes, such as ABCP or money-market tranche, or as term notes. The junior-AAA usually accounts for 5%-6% of the CDO and is offered at a higher spread, with an average life from 7 to 9 years. We think the junior-AAA’s of HG SF CDOs are attractive for the following reasons: 1.

They offer attractive spread pick-up over almost all other AAA bonds in the primary markets of structured finance. Currently, the spread of junior-AAA’s of HG CDOs is around 45 bps. The all-in funding cost of ABCP tranches is around L+24 bps while the spread on term-funded senior-AAA’s is around 27 bps in HG SF CDOs. As shown in Exhibit 231, the spread pick up of junior-AAA over seniorAAA is around 20 bps. Compared to the AAA bonds in other sectors, as shown in Exhibit 232, junior-AAA’s in HG SF CDOs offer more spread as well.

Exhibit 231: Junior AAA Spread vs. Senior AAA Spread* 90

Snr AAA Spread

Jnr AAA Spread

60

Difference

55

80

50 45

60

40 35

50

30

40

25

30

Difference (bps)

Spread (bps)

70

20

Aug-05

Jul-05

Jul-05

Apr-05

Mar-05

Feb-05

Nov-04

Nov-04

Nov-04

Oct-04

Sep-

10 Jul-04

10 Apr-04

15 Feb-04

20

Source: Credit Suisse * For ABCP tranches, we use a float all-in spread of 24 bps.

254

This section was originally published in "The CDO Strategist", Issue #7, September 15, 2005.


223

31 March 2006

Exhibit 232: AAA Spreads of Select Structured Products Sector

AAA Floating Spread (over LIBOR, bps)

HY CLO AAA

25

Bank Trust Preferred CDO Junior AAA

43

Mezz SF CDO Junior AAA

45

HG SF CDO Junior AAA

45

CRE CDO Junior AAA

39

5-year HEL (Float) AAA

23

7-year Credit Card (Float) AAA 10-year CMBS (Fixed)

7 27*

Source: Credit Suisse * Over swap

2.

Sufficient loss coverage Because of the higher credit quality of the underlying pools in HG deals, loss coverage ratios of most junior-AAA’s are sufficient enough to withstand principal losses for the given rating. Similar to Exhibit 38 (see Insight section), we can use the expected loss rates derived from Moody’s impairment rates and calculate the loss coverage ratios of junior-AAA tranches. The results are in Exhibit 233. Most of the coverage ratios fall in the range of 13 to 20 times, sufficient to cover potential losses. Another check is to use “Break-even Default Rates”, defined here as the annual default rate resulting in a break in yield (for floating bonds, a break in discount margin, i.e. a discount margin below the coupon spread of the notes). We compare the Break-even Default Rates to the annual default rates of each deal, calculated from the expected loss rates derived in Exhibit 38, assuming a recovery rate of 55%.255 As shown in Exhibit 234, the ratio of Break-even Default Rate over the implied annual default rate is very high for most of the deals: at least 20 times in a faster prepayment scenario.256 To put these numbers into perspective: for a resulting loss on the junior-AAA tranche, the annual default rate has to be at least 20 times higher than the empirically implied default rate! We view this as a very remote event. That said, the existence of a high coverage ratio does not entirely eliminate the possibility of a loss on the tranche. This analysis is based on poollevel assumptions; more robust asset-level analysis is needed for further investigation.257

In summary, we think the junior-AAA tranche of HG SF CDOs offer an attractive risk/return profile. Investors of AAA-level risk should take a close look at this asset class and explore potential investment opportunities. As shown in Exhibit 231, junior-AAA spreads have followed a tightening trend and we believe given a robust risk/return profile, spreads should remain tight or continue to grind in. Furthermore, the spread between senior-AAA and junior-AAA is likely to converge. We note that there could be downgrade risk on the junior AAA tranches in extreme adverse situations.

255 55% is the recovery rate (45% severity rate) we used to calculate the expected loss rates. We also use the forward LIBOR curve. 256 When prepayment is faster, it is less likely to suffer greater losses from back-loaded defaults, and thus more likely to have a higher break-even default rate. 257 Given the fact that the "room for error" is smaller for HG deals, in some sense it is even more crucial to conduct asset-level analysis.


224

31 March 2006

Exhibit 233: Subordination Levels and Loss Coverage of Junior AAA Tranches Deal Name CDO 3 CDO 5 CDO 6 CDO 7 CDO 8 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 25

WAR AA

Expected Loss Rate 0.2228%

Junior AAA Subordination Loss Coverage Ratio 5.00% 22.44

AA-

0.6008%

7.00%

AA/AAAA/AAAA/AAAAAA-/A+ AA/AAAAAA/AAA+ AA/AAAA AAA+ A+ AA/AAAA+

0.4003% 0.2773% 0.3918% 0.2620% 0.6328% 0.4045% 0.6112% 0.3771% 0.8035% 0.6505% 0.4203% 0.4522% 0.7245% 0.7522% 0.4083% 0.3955%

6.00% 6.00% 10.00% 5.00% 10.00% 6.00% 7.00% 8.00% 9.00% 9.00% 6.00% 6.00% 12.00% 10.00% 7.00% 5.00%

11.65 14.99 21.64 25.52 19.09 15.80 14.83 11.45 21.21 11.20 13.84 14.27 13.27 16.56 13.29 17.14 12.64

Source: Credit Suisse, Intex, Bloomberg

Exhibit 234: Break-even Default Rate vs. Implied Annual Default Rate Implied Annual Deal Name CDO 3 CDO 5 CDO 6 CDO 7 CDO 8 CDO 11 CDO 12 CDO 13 CDO 14 CDO 15 CDO 16 CDO 18 CDO 19 CDO 20 CDO 21 CDO 22 CDO 23 CDO 25

Default Rate* 0.10% 0.27% 0.18% 0.12% 0.17% 0.12% 0.28% 0.18% 0.27% 0.17% 0.36% 0.29% 0.19% 0.20% 0.32% 0.33% 0.18% 0.18%

Break-even

Break-even

Default Rate (20% CPR) 7.40% 6.80% 5.20% 4.60% 8.20% 3.40% 9.40% 4.30% 8.50% 4.70% 6.30% 5.80% 4.20% 5.70% 7.80% 5.70% 4.30% 7.60%

Default Rate (30% CPR) 8.50% 7.90% 5.80% 5.10% 10.00% 3.60% 12.40% 5.00% 10.10% 5.40% 7.30% 6.90% 4.90% 6.20% 8.90% 6.70% 4.80% 8.10%

Ratio (20% CPR) 74.74 25.47 29.23 37.33 47.09 29.20 33.42 23.92 31.29 28.04 17.64 20.06 22.48 28.36 24.22 17.05 23.69 43.24

Ratio (30% CPR) 85.85 29.59 32.60 41.38 57.43 30.92 44.09 27.82 37.18 32.22 20.44 23.87 26.23 30.85 27.64 20.04 26.45 46.08

Source: Credit Suisse, Intex * This is the annual default rate implied from the expected loss rates calculated by using a recovery rate of 55% and dividing by 5 years.


225

STRUCTURED PRODUCTS RESEARCH

Gail Lee, Managing Director

Bunt Ghosh, Managing Director

Global Head of Structured Products Research

Global Head of Fixed Income Research

+1 212 325 1214

+44 20 7888 3042

NORTH AMERICA

Eleven Madison Avenue, New York, NY 10010

Asset-Backed Securities (ABS) Rod Dubitsky, Managing Director Senior Strategist, Group Head +1 212 325 4740 [email protected]

Rajat Bhu, Vice President

Chris Fenske, Vice President

Jay Guo, Vice President

+1 212 325 5410 [email protected]



Shumin Li, Vice President

Lidia Dumitrascu, Associate

Larry Yang, Associate

Christopher Mellia, Analyst





Collateralized Debt Obligations (CDO) David Yan, Vice President

Stephen Chow, Associate

Neil Desai, Analyst

Willie Green





Commercial Mortgage Backed Securities (CMBS) Gail Lee, Managing Director Senior Strategist, Group Head +1 212 325 1214 [email protected]

Paul Fitzsimmons, Vice President

Manish Rajguru, Vice President

Serif Ustun, Vice President




Mortgage Backed Securities — Residential (MBS) Satish Mansukhani, Managing Director Senior Strategist, Group Head +1 212 325 5985 [email protected]

Mahesh Swaminathan, Director

Adama Kah, Vice President

Chandrajit Bhattacharya, Vice President




Sergei Ivanov, Vice President

Mutaz Qubbaj, Associate



EUROPE – Structured Products (All) Recai Güneşdoğdu, Director European Head +44 20 7883 7978 [email protected]

Tim Francis, Associate

Michael Tian, Associate



JAPAN – Structured Products (All) Kenji Toukaku, Director Japan Head + 81 3 4550 7172 [email protected]

One Cabot Square, London E14 4QJ, United Kingdom

Izumi Garden Tower, 1-6 Roppongi 1-Chome, Minato-ku, Tokyo 106-6024

Kaoru Kondo, Associate [email protected] +81 3 4550 7171

For general inquiries or to be added to a distribution list, please contact: Angela Chuang ([email protected]) or Werner Pauliks ([email protected])


226

Disclosure Appendix Analyst Certification David Yan and Stephen Chow each certify, with respect to the companies or securities that he or she analyzes, that (1) the views expressed in this report accurately reflect his or her personal views about all of the subject companies and securities and (2) no part of his or her compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this report. Important Disclosures Credit Suisse's policy is only to publish investment research that is impartial, independent, clear, fair and not misleading. For more detail, please refer to Credit Suisse's Policies for Managing Conflicts of Interest in connection with Investment Research: http://www.csfb.com/research-andanalytics/disclaimer/managing_conflicts_disclaimer.html Credit Suisse’s policy is to publish research reports as it deems appropriate, based on developments with the subject issuer, the sector or the market that may have a material impact on the research views or opinions stated herein. The analyst(s) involved in the preparation of this research report received compensation that is based upon various factors, including Credit Suisse's total revenues, a portion of which are generated by Credit Suisse's Investment Banking and Fixed Income Divisions. Credit Suisse may trade as principal in the securities or derivatives of the issuers that are the subject of this report. At any point in time, Credit Suisse is likely to have significant holdings in the securities mentioned in this report. As at the date of this report, Credit Suisse acts as a market maker or liquidity provider in the debt securities of the subject issuer(s) mentioned in this report. For important disclosure information on securities recommended in this report, please call +1-212-538-7625. For the history of any relative value trade ideas suggested by the Fixed Income research department over the previous 12 months, please view the document at http://research-and-analytics.csfb.com/docpopup.asp?docid=35321113&type=pdf. Credit Suisse clients with access to the Locus website may refer to http://www.credit-suisse.com/locus. For the history of recommendations provided by Technical Analysis, please visit the website at http://www.credit-suisse.com/techanalysis. Credit Suisse does not provide any tax advice. Any statement herein regarding any US federal tax is not intended or written to be used, and cannot be used, by any taxpayer for the purposes of avoiding any penalties. Emerging Markets Bond Recommendation Definitions Buy: Indicates a recommended buy on our expectation that the issue will deliver a return higher than the risk-free rate. Sell: Indicates a recommended sell on our expectation that the issue will deliver a return lower than the risk-free rate. Corporate Bond Fundamental Recommendation Definitions Buy: Indicates a recommended buy on our expectation that the issue will be a top performer in its sector. Outperform: Indicates an above-average total return performer within its sector. Bonds in this category have stable or improving credit profiles and are undervalued, or they may be weaker credits that, we believe, are cheap relative to the sector and are expected to outperform on a total-return basis. These bonds may possess price risk in a volatile environment. Market Perform: Indicates a bond that is expected to return average performance in its sector. Underperform: Indicates a below-average total-return performer within its sector. Bonds in this category have weak or worsening credit trends, or they may be stable credits that, we believe, are overvalued or rich relative to the sector. Sell: Indicates a recommended sell on the expectation that the issue will be among the poor performers in its sector. Restricted: In certain circumstances, Credit Suisse policy and/or applicable law and regulations preclude certain types of communications, including an investment recommendation, during the course of Credit Suisse's engagement in an investment banking transaction and in certain other circumstances. Corporate Bond Risk Category Definitions In addition to the recommendation, each issue may have a risk category indicating that it is an appropriate holding for an "average" high yield investor, designated as Market, or that it has a higher or lower risk profile, designated as Speculative and Conservative, respectively. Credit Suisse Credit Rating Definitions Credit Suisse assigns rating opinions to investment-grade and crossover issuers. Ratings are based on our assessment of a company's creditworthiness and are not recommendations to buy or sell a security. The ratings scale (AAA, AA, A, BBB, BB, B) is dependent on our assessment of an issuer's ability to meet its financial commitments in a timely manner. Within each category, creditworthiness is further detailed with a scale of High, Mid, or Low – with High being the strongest sub-category rating: High AAA, Mid AAA, Low AAA – obligor's capacity to meet its financial commitments is extremely strong; High AA, Mid AA, Low AA – obligor's capacity to meet its financial commitments is very strong; High A, Mid A, Low A – obligor's capacity to meet its financial commitments is strong; High BBB, Mid BBB, Low BBB – obligor's capacity to meet its financial commitments is adequate, but adverse economic/operating/financial circumstances are more likely to lead to a weakened capacity to meet its obligations; High BB, Mid BB, Low BB – obligations have speculative characteristics and are subject to substantial credit risk; High B, Mid B, Low B – obligor's capacity to meet financial commitments is very weak and highly vulnerable to adverse economic, operating, and financial circumstances. Credit Suisse's rating opinions do not necessarily correlate with those of the rating agencies.


227

References in this report to Credit Suisse include all of the subsidiaries and affiliates of Credit Suisse operating under its investment banking division. For more information on our structure, please use the following link: http://www.credit-suisse.com/en/who_we_are/ourstructure.html. This report is not directed to, or intended for distribution to or use by, any person or entity who is a citizen or resident of or located in any locality, state, country or other jurisdiction where such distribution, publication, availability or use would be contrary to law or regulation or which would subject Credit Suisse or its affiliates (“CS”) to any registration or licensing requirement within such jurisdiction. All material presented in this report, unless specifically indicated otherwise, is under copyright to CS. None of the material, nor its content, nor any copy of it, may be altered in any way, transmitted to, copied or distributed to any other party, without the prior express written permission of CS. All trademarks, service marks and logos used in this report are trademarks or service marks or registered trademarks or service marks of CS or its affiliates. The information, tools and material presented in this report are provided to you for information purposes only and are not to be used or considered as an offer or the solicitation of an offer to sell or to buy or subscribe for securities or other financial instruments. CS may not have taken any steps to ensure that the securities referred to in this report are suitable for any particular investor. CS will not treat recipients of this report as its customers by virtue of their receiving this report. The investments and services contained or referred to in this report may not be suitable for you and it is recommended that you consult an independent investment advisor if you are in doubt about such investments or investment services. Nothing in this report constitutes investment, legal, accounting or tax advice, or a representation that any investment or strategy is suitable or appropriate to your individual circumstances, or otherwise constitutes a personal recommendation to you. CS does not advise on the tax consequences of investments and you are advised to contact an independent tax adviser. Please note in particular that the bases and levels of taxation may change. Information and opinions presented in this report have been obtained or derived from sources believed by CS to be reliable, but CS makes no representation as to their accuracy or completeness. CS accepts no liability for loss arising from the use of the material presented in this report, except that this exclusion of liability does not apply to the extent that such liability arises under specific statutes or regulations applicable to CS. This report is not to be relied upon in substitution for the exercise of independent judgment. CS may have issued, and may in the future issue, other reports that are inconsistent with, and reach different conclusions from, the information presented in this report. Those reports reflect the different assumptions, views and analytical methods of the analysts who prepared them and CS is under no obligation to ensure that such other reports are brought to the attention of any recipient of this report. CS may, to the extent permitted by law, participate or invest in financing transactions with the issuer(s) of the securities referred to in this report, perform services for or solicit business from such issuers, and/or have a position or holding, or other material interest, or effect transactions, in such securities or options thereon, or other investments related thereto. In addition, it may make markets in the securities mentioned in the material presented in this report. CS may have, within the last three years, served as manager or co-manager of a public offering of securities for, or currently may make a primary market in issues of, any or all of the entities mentioned in this report or may be providing, or have provided within the previous 12 months, significant advice or investment services in relation to the investment concerned or a related investment. Additional information is, subject to duties of confidentiality, available on request. Some investments referred to in this report will be offered solely by a single entity and in the case of some investments solely by CS, or an associate of CS or CS may be the only market maker in such investments. Past performance should not be taken as an indication or guarantee of future performance, and no representation or warranty, express or implied, is made regarding future performance. Information, opinions and estimates contained in this report reflect a judgement at its original date of publication by CS and are subject to change without notice. The price, value of and income from any of the securities or financial instruments mentioned in this report can fall as well as rise. The value of securities and financial instruments is subject to exchange rate fluctuation that may have a positive or adverse effect on the price or income of such securities or financial instruments. Investors in securities such as ADR’s, the values of which are influenced by currency volatility, effectively assume this risk. Structured securities are complex instruments, typically involve a high degree of risk and are intended for sale only to sophisticated investors who are capable of understanding and assuming the risks involved. The market value of any structured security may be affected by changes in economic, financial and political factors (including, but not limited to, spot and forward interest and exchange rates), time to maturity, market conditions and volatility, and the credit quality of any issuer or reference issuer. Any investor interested in purchasing a structured product should conduct their own investigation and analysis of the product and consult with their own professional advisers as to the risks involved in making such a purchase. Some investments discussed in this report may have a high level of volatility. High volatility investments may experience sudden and large falls in their value causing losses when that investment is realised. Those losses may equal your original investment. Indeed, in the case of some investments the potential losses may exceed the amount of initial investment and, in such circumstances, you may be required to pay more money to support those losses. Income yields from investments may fluctuate and, in consequence, initial capital paid to make the investment may be used as part of that income yield. Some investments may not be readily realisable and it may be difficult to sell or realise those investments, similarly it may prove difficult for you to obtain reliable information about the value, or risks, to which such an investment is exposed. This report may provide the addresses of, or contain hyperlinks to, websites. Except to the extent to which the report refers to website material of CS, CS has not reviewed any such site and takes no responsibility for the content contained therein. Such address or hyperlink (including addresses or hyperlinks to CS’s own website material) is provided solely for your convenience and information and the content of any such website does not in any way form part of this document. Accessing such website or following such link through this report or CS’s website shall be at your own risk. This report is issued and distributed in Europe (except Switzerland) by Credit Suisse Securities (Europe) Limited, One Cabot Square, London E14 4QJ, England, which is regulated in the United Kingdom by The Financial Services Authority (“FSA”). This report is being distributed in Germany by Credit Suisse Securities (Europe) Limited Niederlassung Frankfurt am Main regulated by the Bundesanstalt fuer Finanzdienstleistungsaufsicht ("BaFin"). This report is being distributed in the United States and Canada by Credit Suisse Securities (USA) LLC; in Switzerland by Credit Suisse; in Brazil by Banco de Investimentos Credit Suisse (Brasil) S.A; in Japan by Credit Suisse First Boston Securities (Japan) Limited; elsewhere in Asia/ Pacific by whichever of the following is the appropriately authorised entity in the relevant jurisdiction: Credit Suisse (Hong Kong) Limited, Credit Suisse Equities (Australia) Limited, Credit Suisse Securities (Thailand) Limited, Credit Suisse Securities (Malaysia) Sdn Bhd, Credit Suisse Singapore Branch, and elsewhere in the world by the relevant authorised affiliate of the above. Research on Taiwanese securities produced by Credit Suisse, Taipei Branch has been prepared by a registered Senior Business Person. Research provided to residents of Malaysia is authorised by the Head of Research for Credit Suisse Securities (Malaysia) Sdn Bhd, to whom they should direct any queries on +603 2723 2020. This research may not conform to Canadian disclosure requirements. In jurisdictions where CS is not already registered or licensed to trade in securities, transactions will only be effected in accordance with applicable securities legislation, which will vary from jurisdiction to jurisdiction and may require that the trade be made in accordance with applicable exemptions from registration or licensing requirements. Non-U.S. customers wishing to effect a transaction should contact a CS entity in their local jurisdiction unless governing law permits otherwise. U.S. customers wishing to effect a transaction should do so only by contacting a representative at Credit Suisse Securities (USA) LLC in the U.S. Please note that this research was originally prepared and issued by CS for distribution to their market professional and institutional investor customers. Recipients who are not market professional or institutional investor customers of CS should seek the advice of their independent financial advisor prior to taking any investment decision based on this report or for any necessary explanation of its contents. This research may relate to investments or services of a person outside of the UK or to other matters which are not regulated by the FSA or in respect of which the protections of the FSA for private customers and/or the UK compensation scheme may not be available, and further details as to where this may be the case are available upon request in respect of this report. Copyright © 2006 CREDIT SUISSE GROUP and/or its affiliates. All rights reserved.

CDO Handbook Final

Recommend Documents