{
800 700 600
Rock -bottom less than market spread
500 400 300 200
{
100 AA
A
Rock -bottom spread
BBB
BB
EMBI Global with current rating outlooks 488bp …with stable rating outlooks 514bp
+26bp
900
Rock -bottom exceeds market spread
Positive liquidity spread
B
Mar ke t spread
…and with HY credit composition 671bp
+157bp
…and with historical HY recovery rate 473bp
-198bp
…and with historical HY credit migration 691bp
+218bp
…and with HY diversity 491bp
-200bp
…and with current HY recovery rate view 551bp
+60bp
…and with current HY credit migration view 648bp
+97bp
HY with current default view 648bp
3%
2%
1%
0%
-1%
I I 7 9 9 1
I 8 9 9 1
I I 8 9 9 1
I 9 9 9 1
I I 9 9 9 1
I 0 0 0 2
I I 0 0 0 2
I 1 0 0 2
e g a r e v A
12% 10% 8% 6% 4% 2% 0%
I I . 9 9 9 1
I . 0 0 0 2
I I . 0 0 0 2
I . 1 0 0 2
e g a r e v A
800 700
Rock-Bottom Spread
600 500 400 300
Market Spread
200
Illiquidity Spread
100 0 -100
-200 Spreads Market Rock-Bottom Illiquidity
AAA
AA
A
72 6 66
90 18 72
124 34 90
BBB
BB
B
16 5 99 66
300 296 4
510 713 -203
12 0 10 0
80 60 40 20 0 AAA
AA
A
BBB
BB
B
Roc k-B ott om S prea ds Credit Downturn Scenario 6
18
34
99
296
7 13
16 2
29 5
84 15
259 37
6 13 1 00
Historical Average Scenario Difference
6 0
Probability of Credit Quality Change
Portfolio Diversity
Probability of Default Recovery Rate
Credit Fundamentals Exposure
Rating a t year-end r AAA a e y f AA o t A r a t s BBB t a BB g n i t B a RCCC
AAA AA
A
BBB
BB
B
CCC Default
88.7
10.3
1.0
0.00
0.03
0.00
0.00
0.00
1.1
88.7
9.6
0.3
0.15
0.15
0.00
0.01
0.06
2.9
90.2
5.9
0.7
0.18
0.01
0.01
0.05
0.3
7.1
85.2
6.1
1.0
0.08
0.16
0.03
0.08
0.6
5.7
83.6
8.1
0.5
1.5
0.01
0.04
0.2
0.7
6.6
82.7
2.8
7.1
0.00
0.00
0.7
1.1
3.1
6.1
63.0
26.2
Source: Moodys. The figures are long run annual averages of the frequency of rating changes and defaults among rated issuers, 1980-98
Averag e Recovery R ate: $47 per $100 of principal
Volatility: $26 per $100 of principal
Averag e time to recov ery: 2.1 years Source: H.S. Wagner “The Pricing of Bonds in Bankruptcy and Financial Restructuring”, Journal of Fixed Income, June 1 996
Diversity Sco res AAA AA
A
BBB
BB
B
CCC
30
66
63
59
54
19
53
The diversity score is the number of uncorrelated exposures to which each sector is equivalent. See Appendix 1.
Corporate Bond Now pay...
1 year
At maturity receive ...
Credit Return
5% Government Bond
$100
Default
Recovery
=
$100
Credit Fundamentals Exposure
Risk Tolerance
Rock Bottom Spreads
No default
$100 + $5 + Spread
Corporate Return
$100 + $5
-
Government Return
1.5
(a) Average Credit Return (%)
1.0 0.5
Spread (bps)
0 50
-0.5
150
200
150
200
-1.0 -1.5
100
Divid ed by...
1.2 1.0 0.8
(b) Credit Return V olatility (%)
0.6 0
50
100
…equals... 1.0
(c) Information Ratio 0.5
Target Rock-Bottom Spread: 152bp
0 50
100
150
200
Breakeven Spread: 97bp
-0.5
First, some abbreviations: p denotes the probability of default during the year, d denotes the excess return over governments in the event of a d efault ( recovery-100-coupon) and s denotes the spread, n denotes the diversity score, or equivalent number of independent credit exposures in the portfolio (See Appendix 1). The average credit return is the average of the excess return over governments in Figure 6, weighted by their probabilities: p *d + (1-p )*s
Hence, average credit returns increase as spreads increase. As the probability of default increases, the line flattens and shifts downwards. The volatility of re turns is:
p * (1 − p ) * n
(s
−
d )
So volatility increases with spread (although not significantly, since( s -d ) is on the order of $68, and an extra 100bp of sprea d raises this by only $1). As diversity declines or the probability of default increases (up to one half), the volatility line shifts up.
RockAnnual Default
Breakeven
bottom
Risk
probabili ty (%)
spread (bp)
spread (bp)
premium (bp)
AAA
0.000
0
0
0
AA
0.005
0
4
3
A
0.010
1
5
4
BBB
0.16
10
28
18
BB
1.46
97
152
55
B
7.06
489
632
143
26.16
2282
2959
677
CCC
Maturity 1
3
5
10
AAA
0
1
2
6
AA
4
6
8
16
A BBB BB B CCC
5
9
15
29
28
42
56
84
152
191
220
259
632
645
642
613
2959
2558
2239
1759
40
Rat ing a ctivi ty
Credit Fundamentals Scenario
30
Historical 20
Average
Downswing
4.10%
6%
20%
20%
-8.50%
-12%
5.75%
4%
14.25%
16%
Speculative Grade Defaults
10 Aver age 20 %
Activity
0 Dec 82
Dec 86
Dec 90
Dec 94
Dec 98
Credit
Drift Which implies
Upgrades Downgrades
10 5
Rat ing dr ift
0
Ave ra ge -8. 5%
-5 -10
-15 -20
Ra tin g a t ye ar- en d
-25
AAA r AAA a e y AA f o t A r a BBB t s t BB a g B n i t a CCC R
Speculative Grade Defaults 10 8 6 4 2
Av erag e 4.1%
0 Dec 82
Dec 86
Dec 90
Dec 94
Dec 98
AA
A
BBB
BB
B
CCC
D
+0.0
+0.0
+0.0
+0.0
-0.7
+0.6
+0.1
+0.0
-0.4
-0.9
+1.3
+0.0
+0.0
+0.0
+0.0
+0.0
+0.2
+0.0
+0.0
+0.0
+0.0
+0.0
-1.8
+1.5
-0.0
-0.1
-2.5
+1.0
+1.3
+0.2
+0.0
+0.1
-0.0
-0.3
-3.1
+0.1
+2.5
+0.2
+0.7
-0.0
-0.0
-0.1
-0.3
-3.4
-0.7
+2.0
+2.5
+0.0
+0.0
-0.3
-0.5
-1.4
-2.8
-2.0
+7.0
-0.0
800 700
Rock-Bottom Spread
600 500 400 300
Market Spread
200
Illiquidity Spread
100 0 -100 -200 A AA
AA
A
BBB
BB
B
72 6 66
90 18 72
12 4 34 90
16 5 99 66
30 0 29 6 4
51 0 71 3 -20 3
Spreads Market Rock-Bottom Illiquidity
700
Rock-Bottom Spread
600
500 400 Market Spread Spre ad (10 yr)
300
Illiquidity Spread
200 100 0 -100 -200 Spreads Market Rock-Bottom Illiquidity
AAA 65 6 59
AA
A
BBB
80 16 64
111 29 82
143 84 59
BB 275 259 16
B 460 613 -153
100 Rock-Bottom Spread Change
80 Market Spread Change
60 40 20 0 AAA
AA
A
BBB
BB
B
Spread Changes Market
6
5
12
22
25
50
Rock-Bottom
0
2
5
15
37
100
New Issue Spread
Secondary Issue Spread
Rating
Rating
LTV ’09
586
Ba3/BB-
LTV ’07
4 90
Ba3/BB-
IASIS Healthcare ’09
689
B3/B-
Triad ’09
5 09
B3/B-
Lifepoi nt ’09
4 87
B3/B-
Sbarro ’09
625
Ba3/BB-
Domi no’s Pizza ’09
5 00
B3/B-
Unilab ’09
725
B3/B-
Dynacare ’06
5 85
B2/B+
10 0 50 0 -5 0 -100 -150
Ea rly ’97 conditions pe rsist
{2forever years
-200 A AA
AA
A
BBB
BB
B
AAA AA A BBB Aerospace HiTech
4 3
18 16
89 31
74 25
BB 75 28
Service Leisure Health Building Energy Utility Telecom Transport Finance Insurance
4 0 5 0 10 1 9 3 43 43
47 9 18 4 24 50 32 5 136 77
96 29 55 33 34 133 27 27 376 83
89 34 41 39 43 107 8 47 133 40
85 81 43 41 30 18 8 29 34 23
109 84 33 28 27 2 16 24 11 8
5 3 3 0 1 0 5 3 3 1
125
436
1013
680
495
445
29
30
53
66
63
59
54
19
Total Issuers Diversity Score
B CCC 76 4 27 1
Downgrades Slope Change AAA AA A BBB BB B CCC
0.38 0.79 1.00 0.89 1.52 1.13
0.7 1.4 1.7 1.6 2.7 2.0
Upgrades Slope Change
Speculative Defaults Slope Change
0.25 -0.01 1.51 1.96 2.18 2.89
0.00 0.00 0.01 0.07 0.36 1.31 3.71
-0.4 0.0 -2.6 -3.4 -3.8 -5.1
0.00 0.00 0.01 0.12 0.69 2.50 7.05
Rock-bottom spread mechanics • •
A bond’s rock-bottom spread prices its credit exposure We explain with examples what goes into calculating rock-bottom spreads, emphasizing: o o
o
•
how credit risk is accounted for the key role of views on default and recovery rates, and how to formulate them the minor effects of interest rates and recovery rate uncertainty
how the combination of your investment performance goals and a bond’s credit fundamentals determine its rock-bottom spread. Then we explain how the rock-bottom spread is affected by each element of credit fundamentals: coupons, maturity, recovery rates, default rates, and so on. We also describe a simple framework for translating your own views of future credit fundamentals trends into rock-bottom spread numbers that you can compare with market spreads. Figure 1 Rock-bottom spreads versus market spreads ( bp)
A new rock-bottom spread calculator on Morganmarkets lets you replicate and further dissect the examples
{
Corporate bonds have two principal drawbacks relative to swaps or government bonds: greater credit exposure, and lower liquidity. Investors need to assess whether market spreads pay enough for these drawbacks. This task is more manageable if the exposures can be translated int o spread terms. JP Morgan’s rock-bottom spread framework does just this for credit exposure. Rock-bottom spreads are built around the idea of a reservation price: the highe st price at which you can buy an asset and remain consistent with your investment performance goals. A bond’s rock-bottom spread is the amount you need to be paid for bearing its potential for downgrade or default, and expected recovery rate, taking into account your ability to diversify these risks. If the bond’s market spread is below its rock-bottom spread, on average it will not deliver sufficient return for the credit risk it entails. Similarly, the difference between its market spread and rock-bottom measures how much you are getting compensated, if at all, for its lower liquidity. Figure 1 illustrates. In several other research pieces, we have used the rock bottom spread framework a s a common yardstick for disparate asset classes such as high yield and investment grade corporate bonds and emerging markets sovereigns. Similarly, the approach makes it simple to place a value on credit-driven features of individual securities, such as call provisions in high yiel d bonds, and coupon step-up clauses triggered by rating changes. The mechanical steps involved in calculating rock-bottom spreads are explicitly laid out in this note. We first show
900
Rock-bottom exceeds market spread
800 700 600
Rock-bottom less than market spread
500 400 300
Positive liquidity spread
200
{
100
AA
A
Rock-bottom spread
BBB
BB
B
Market spread
Spreads over US Treasuries curve for (duration-weighted) averages of 510yr senior, unsecured bonds in the JP Morgan High-Yield index (BB and B-rated), and liquid investment grade bonds. Market spreads are as of June 1, 2001. Rock-bottom spreads incorporate the negative credit view for the next 12 months that is described in the last section of the paper. Recovery rates on defaulted bonds are assumed to be $35 per $100 of principal, in line with current traded prices of defaulted debt.
Of course, this is scarcely vacation reading. Rather, it is intended as a reference that will make it possible to take apart the rock-bottom spread calculations in our publications, and that can now be carried out painlessly using our new web calculators. All but a few of the calculations in this research note used these calculators. In the text, we provide the recipe that will enable you to replicate each calculation. An accompanying spreadsheet, available from our website [10]1 , demonstrates how to build a simple rock-bottom spread calculator. Thus armed, you will be able to take apar t and rationalise any rock-bottom spread valuation. 1
Numbe rs is square brac kets refe r to the public ations lis ted on p.12
Valuation Valuing an asset means determining a reservation price at which you are prepared to buy it. The reservation price is the highest price consistent with achieving your investment objectives, given your views of how the asset will perform. Thus, implicit in any valuation of a financial asset are:
• • •
the prices at which you believe the asset can be sold in each possible future scenario; your view of the relative likelihood of each scenario; a performance target, typically relating to the asset’s risk and return
We will now explain the role of each of these components in the rock-bottom spread valuation framework.
Credit scenarios For bonds that pay cash, the future scenarios are quite simple to lay out, because we have an “anchor” at the maturity date. For example a one-year (annual-paying) 8% bullet promises $108. Of course, the key word here is “promises”, because the bond can also default. The payout in the event of default is uncertain, and will be the result of a complicated liquidation or restructuring process. For concreteness, we shall assume that the bond is worth an average of $45 per $100 of principal, in line with the historical average prices of bonds that have just defaulted 2 . So, at maturity, two credit scenarios are possible (see Figure 2). Figure 2
Credit scenarios for a 1-year 8% bond
No default $108
Default $45 Today
In 1 year
The value you place on the bond will depend on how likely you view each scenario to be. For example, your view could be in line with the frequency of default that has been observed historically (see Table 1). We shall use these figures to illustrate how to calculate rock-bottom spreads, but it is worth stressing that there is nothing sacred about them. They simply describe past experience, and have no automatic claim to represent your view of future credit conditions. They are just one possible set of input values that really only should be used if you have no strong feelings about credit trends. 2 Of course, this is a simplification; recovery rates are anything but certain once a bond has gone into defau lt. The full rock-botto m spread calcul ation price s in uncertainty about recovery rates.
Table 1 Moody's 1-year default rates Averages, 1983-2000 AAA AA A BBB BB B CCC
0.00% 0.03% 0.00% 0.18% 1.52% 7.46% 29.21%
Performance criterion The performance criterion behind rock-bottom spreads is based on the information ratio . In general, an asset’s information ratio measures its return relative to a benchmark, adjusted for risk. It is just the difference between the expected returns of the asset and ben chmark, divided by the asset’s return volatility around the benchmark, or tracking error. The higher the information ratio, the better the asset is expected to perform. Requiring your investments to attain a target level of the information ratio is a sensible performance criterion. It corresponds to setting a target rate of return on capital. Taking risk around your benchmark costs capital in one form or another, and a low information ratio implies that you are getting a low return on capital. Here, we set the target annual information ratio at 0.5, which has become something of a standard in the investment management industry. In particular, we can point to investment strategies, such as active management of global government bond funds, which have achieved this target in the past. Why pursue a strategy that produces a lower information ratio than the available alternatives?
From target information ratio to rock bottom How does setting a target level for the information ratio enable you to put a value on credit exposure? Via its dependence on returns, an asset’s information ratio also depends on its current price: the higher the price, the lower the information ratio. So there is some price at which the information ratio will just equal 0.5. This price is precisely the value you place on the asset. It is the highest you can afford to pay and still satisfy your performance criterion. In the context of valuing credit exposure, this defines the rockbottom price , from which the rock-bottom spread follows via a conventional price-to-yield calculation. To calculate rock-bottom spreads, we thus need to assemble the components of the information ratio provided by credit exposure. In our case, the relevant benchmark is an investment on which there is no chance of default, which we shall call a governmen t bond . Our 8% bond’s credit return
in a scenario (default or no default) is the excess of its return over the government bond: price in current − gov t credit return = scenari o price − return in scenari o current price
So, the information ratio we are interested in is:
inf ormation = ratio
average credit return credit return volatility
The numerator of the information ratio averages across the credit return scenarios, while the volatility in the denominator is the standard deviation of credit returns across the scenarios. The information ratio depends on the price you pay for the bond today, because credit returns depend on the price today. Since we know the prices in each future scenario (see Figure 2), and the probabilities of each scenario, the only unknown quantities in this equation are the information ratio and the current price. Once we set the information ratio at its target level, there is only one unknown, the current price. The value of the current price that satisfies the equation is the rock-bottom price: it is the price consistent with the target information ratio, under the assumed credit conditions As a practical matter the rock-bottom price could be solved from the information ratio equation by trial and error. However, it is easier and more revealing to reexpress this equation as a definition of the rock-bottom price. First, we deal with the average credit return across scenarios. To calculate this, you multiply the credit return in each scenario by its probability, and sum across scenarios. We assume for the moment that the government return does not change across scenarios. So, the “price in scenario” term is the only element of the credit return that changes from one scenario to another. The average of the government return across scenarios is just the government return, and the same goes for the current price. Consequently, the average credit return is: average credit = return
average price across scen ari os current price
− 1 +
gov t
return
A similar rule holds for the volatility of credit returns, which is just price volatility credit return = across scen ari os volatility current price
Why is the (1+govt return) term absent from volatility? Since it has the same effect in each scenario, its level does not affect the range of variation across scenarios, which volatility measures. Why is the current price present in the denominator? It would not be there if we were just looking at the volatility of profit and loss (future price minus current price). But returns are scaled P&Ls: the more you pay currently, the smaller the proportionate return (in absolute terms) resulting from any price movement, so, the smaller is their range of variation, and volatility needs to be scaled accordingly. Now we can put together these two pieces of the information ratio, and a little bit of algebra expresses the current price in terms of average future prices and their volatility, the information ratio, and the government return:
current = price
average price information − ratio * across scenarios
price volatility across scenarios
(1 + govt return)
The rock-bottom price is simply the price that delivers the investor’s target information ratio. If we now set the information ratio at the target level of 0.5, we have a rule for the price that will deliver that target, given expected credit returns and their volatility, and given government returns:
average pric e Rock across sce nar ios − Bot tom = pric e (1 + govt return)
target information * ratio (1 +
pric e volatility across sce nar ios
gov t return)
Notice that the current market price of the bond is absent from this definition. This is exactly as it should be if rock bottom prices are to offer an independent measure of value against which market prices can be compared. The final step is to translate the rock-bottom price into a rock-bottom spread. First, we calculate the yield to maturity on the bond that is implied by its rock-bottom price and cashflows. Then we calculate the yield of the identical set of cashflows, using the government curve. The difference between these two yields is the rock-bottom spread over government rates.
Calculating Rock-Bottom Spreads We now proceed to use the rock-bottom price equation to value generic bullet bonds. We distinguish bonds by their coupon, maturity, seniority, and senior credit rating of their issuers. To keep the volume of numbers manageable, we stick to the broad or “8-state” rating categories listed in Table 1, instead of the more detailed “18-state” classification (BBB+, Baa1, etc) now used by the rating agencies. Most of the calculations that follow can be
replicated on the 8-state version of our web calculator 3 , by entering the appropriate input values. Each calculation is a small variation on a basic set of inputs: Baseline inputs for rock-bottom spread calculations Default/Downgrade View
Historical
Recovery rate average
0.45
Recovery rate volatility
0
Information ratio
0.5
Diversity score
70
Government curve
Flat 6%
Coupon
8%
The terms “Diversity score” and “Default/Downgrade View” will be clarified below.
issuers. As a practical matter, it is easiest to calculate the impact of portfolio diversity when issuers’ fortunes are independent of each other (and horrendously difficult if they are correlated). Consequently, we use a variant of Moody’s “diversity score” measure to translate a portfolio of correlated issuers’ paper into a (smaller) number of independent issuers that would provide the same degree of diversification.[2,3] The price volatility of a diversified portfolio is simply the price volatility of a single bond, divided by the square root of the diversity score. As a result, the rock-bottom price for a portfolio is
Rock Bottom price
=
Target average price − information * across scenarios ratio
(1 + govt return )
Rock bottom: a single 1-year bond Table 2 assembles the elements of the rock-bottom calculation for the 8% one-year bond, on the assumption that it is rated BB. The average future price is $107.04, and the volatility of future prices is $7.71. Assuming a government return or annual yield of 6%, this translates into a rock-bottom price of $97.35, equivalent to a spread of 494bp. By historical standards, this is quite high for a BBrated bond. It is correct for an investor whose entire portfolio is invested in a single issuer: for this type of investor, a spread of less than 494bp will result in an information ratio of less than 0.5. However, investors typically hold more diversified portfolios, the result of which is to lower the volatility of the credit returns they face. As a consequence, a lower spread will suffice for their target information ratio.
price volatility across scenarios diversity score
Figure 3 traces the effect of diversification on the rock bottom spread of a BB-rated port folio. As diversification increases, rock-bottom spreads initially drop precipitously, but at a diversity score of 20 or so, the curve has all but flattened out. This is fortunate, since calculating diversity scores is far from a precise science. The Figure shows that it does not matter materially whether the diversity score is 50 or 100: the resulting difference in BB rock-bottom spreads is 17bps. Figure 3
Rock Bottom Spreads for BB-rated bonds held in a diversified portfolio 500 450
Table 2
400
Average Price and Price Volatility for a 1-yr BB-rated Bond
350
Scenario
Price in Scenario
Probability
Deviation Price from Average * Probability Price
Squared Deviations * Probability
300 250 200 150
No Default Default
Rock Bottom = price
108 45
98.48% 1.52%
106.36 0.68
Average
107.04
107.04 1
− +
0.5 * 7.71 0.06
0.96 -62.04
0.90 58.51
0
10
20
30
40
50
60
70
80
90
100
Diversity score Volatility
=
7.71
97.35
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs, but set the diversity score equal to 1.
Incorporating diversification Portfolio diversification results from (the lack of) correlation of the underlying asset values of the bond 3
100
The calculator is accessible on the Credit Page of MorganMarkets.com, and is described in reference [1]
The entire US High Yield corporate sector offers a diversity score of about 70. This means that, although there are approximately 1000 rated speculative-grade issuers they only provide the same diversity as would 70 issuers with independent asset values. 4 A fully diversified investor would thus face a rock-bottom spread of 141bps for a BB bon d.5 Less-diversified investors would require greater rock-bottom spreads for one-year BB bonds.
4 5
The Appendix to [3] contains a fuller discussion of diversity scores
The rock-bottom price in Table 2 becomes (107.04-0.5*7.71*√70)/1.06 = 100.55
Interpreting rock-bottom spreads The rock-bottom price has two components. The first is the breakeven price: average pric e Brea k across sce nar ios even = pric e (1 + govt return)
so called because if this is what you pay for the bond, then you will earn the same return on average as you would by investing in government bonds. Consequently, your average credit return will be zero. Only investors who are indifferent to risk would settle for breaking even. If you are risk-averse, you will refuse to pay as much as the breakeven price, because of the uncertainty credit exposure presents. Via its second component, the rock-bottom price requires a discount from the breakeven price for this risk: Rock Brea k Bot tom = even pric e pric e
Risk Dis cou nt
−
In its current form, the risk discount is driven by price volatility – associated with the uncertainty of the issuer’s rating one year from now, and diversification. Later, we shall also include the effects of uncertain recovery rates, without changing the basic form of the rock-bottom price.
anomaly, which we could have removed by “smoothing out” the default probability estimates, rather than using the raw historical numbers, as we have done for simplicity.
Table 3 shows how one-year rock-bottom spreads decompose into a breakeven spread (corresponding to the breakeven price) and a risk premium (corresponding to the risk discount component of the rock-bottom price). Each rating category entails different default probabilities, and therefore different average future prices and breakeven spreads. The risk premia rise as the probability of a default rises, because this causes price volatility to rise.
Longer-maturity bonds To this point, we have applied the principle that a bond’s value today is driven by its value in the future to derive rock-bottom prices and spreads for one-year bonds. We can now use these one-year bond values to value two-year bonds. One year from now, a t wo-year 8% BB bond can finish up in default, as before. Alternatively, it can finish the year as a one-year 8% b ond rated AAA, AA, A, BBB, BB, B, CCC. Its value with one year to go will be different according to its rating, as we have calculated in Table 3, because its chance of going into default in its last year will differ in each case. So, we need to expand the “no-default” category to these possibilities, as Figure 4 shows. Figure 4 Price scenarios for a two-year bond 2 yrs to go
While we have thus incorporated risk aversion in the rock bottom price, we have not done so by stating outright how risk-averse investors are. We have simply reasoned that they should demand from credit a risk discount that brings its performance in line with what they apparently demand from other investment strategies. This led us to a target information ratio of 0.5. Table 3 Valuing 1-yr 8% Bonds Breakeven Spread
AAA AA A BBB BB B CCC
0 2 0 11 95 483 2177
Risk Premium
Rock Bottom Spread
Rock Bottom Price
0 7 0 16 46 107 249
0 9 0 27 141 590 2426
101.89 101.80 101.89 101.63 100.55 96.52 82.91
To produce the rock-bottom spreads with the 8-state rock-bottom spread calculator, use the Baseline Inputs. Breakeven spreads result by setting the information ratio equal to zero. AA spreads are higher than A spreads because the historical AA-rated oneyear default rate is higher (see Table 1). This derives from the fact that one issuer rated A3 at the start of a calendar year defaulted within that year (DFC, in 1989). It does not mean that Aas are more risky than As, as default frequencies over longer horizons show [4]. It is a statistical
1 yr to go AAA 109.89 AA 109.80 109.89 A
BB
BBB 109.63 BB 108.55
104.52 B CCC 90.91 45.00 D
Maturity AAA 108 108 AA 108 A BBB 108 108 BB 108 B CCC D
108 45
It remains to attach probabilities to these events , namely that one-year from now, our two-year BB bond will be rated AAA, or A, etc. Again, we use historical data for illustration. Table 4 shows the frequency of changes in ratings by Moody over the last two decades. If we treat these as the probabilities of future changes in credit quality, then we have all the ingredients to calculate rock-bottom prices and spreads for two-year bonds. The relevant probabilities for BB bonds are in the fifth row. Table 5 details the calculation of the rock-bottom price of 100.67, which translates into a rock-bottom spread of 162bps. As noted above, this calculation penalises bonds for their volatility. However, it is only credit volatility that is considered, by which we mean the variation in the future value of the bond as its future credit quality varies (see Figure 4). Market price volatility does not enter into the
picture, which is in keeping with our aim of pricing the credit component of the bond.
Spread term structures
Table 4
Moody's 1-yr credit migration rates AAA AAA
BB
B
89.20%
9.69%
1.08%
0.00%
0.03%
0.00%
0.00%
0.00%
1.03%
89.31%
9.14%
0.37%
0.09%
0.02%
0.00%
0.03%
AA
AA
A
BBB
CCC
D
A
0.04%
2.48%
90.97%
5.57%
0.72%
0.21%
0.01%
0.00%
BBB
0.04%
0.29%
6.24%
86.96%
5.15%
1.09%
0.05%
0.18%
BB
0.03%
0.03%
0.60%
5.59%
82.94%
8.67%
0.62%
1.52%
B
0.01%
0.06%
0.25%
0.58%
6.43%
82.06%
3.14%
7.46%
CCC
0.00%
0.00%
0.00%
1.12%
2.87%
6.77%
60.03%
29.21%
Table 5 Average Price and Price Volatility for a 2-yr BB-rated Bond
Scenario
Price in Scenario
Probability
109.89 109.80 109.89 109.63 108.55 104.52 90.91 45.00
0.03% 0.03% 0.60% 5.59% 82.94% 8.67% 0.62% 1.52%
Price * Probabilit
Deviation from Average Price
Squared Deviations * Probabilit
2.69 2.61 2.69 2.43 1.36 -2.68 -16.28 -62.19
0.00 0.00 0.04 0.33 1.52 0.62 1.65 58.76
It may seem counterintuitive that B- and CCC-rated rock bottom spreads fall with maturity, since a longer maturity means a greater chance of losing the principal. Actually, the falling low-grade credit curve is no more surprising than the rising high-grade credit curve, and both emanate from the same source. Figure 5
Cumulative Default Probabilities 8%
BBB
7% 6% 5% 4% 3% A
2% 1%
AAA AA A BBB BB B CCC D
0.04 0.03 0.65 6.13 90.03 9.06 0.57 0.68
Average
107.19
=
1
− +
7 .93 70 0.06
0
2
3
4
5
6
7
8
9
10
CCC
80% 70% 60%
B
50% 40%
7.93 0.95
30%
BB
20%
0.5 *
10%
=
Time horizon (years)
0%
100.68
0
The recipe for 3-year bonds uses the prices calculated for 2year bonds as input, and so on. In this way, we can trace out an entire credit- and term-structure of rock-bottom spreads, as shown in Table 6. Table 6
Rock-bottom spreads by rating and maturity Based on 8% annual coupon bond
AAA AA A BBB BB B CCC
1
90%
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs
Maturity
AAA
0%
107.19 Volatility Diversified
Rock Bottom price
AA
1
2
3
5
7
10
0 9 0 27 141 590 2426
1 9 3 33 162 590 2088
1 9 6 39 179 584 1820
2 9 11 50 204 563 1452
3 10 17 60 219 539 1228
5 13 24 72 230 506 1037
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs
1
2
3
4
5
6
7
8
9
10
Figure 5 shows the “cumulative default probabilities”, derived from the figures in Table 4.which indicate the chance that a bond will have defaulted by a given number of years from now. While these probabilities must rise as the time horizon lengthens, they do so at an increasing rate in the case of bonds now rated investment grade, but at a decreasing rate for B and CCC-rated bonds. For example, the probability that a CCC-rated issuer will default within 5 years is 71%, while the 10-year probability is only 10% higher, at 81%. This dramatic difference occurs because those (currently) CCC-rated bonds that survive 5 years will probably be rated much higher, and so will enjoy a much lower default probability from then on. Now, say you require 1452bp of spread to bear 5-year CCC exposure, as in Table 6. Would you be prepared to accept this spread to extend your exposure for a further 5 years, that is, to 10 years? Over these back 5 years, you only have 10% extra chance of default, or about 2% a year, well below B-rated risk, for which you require less than 600bp, again according to Table 6. So, in fact, the 1452bp is more than you would settle for. You would accept a lower spread because the risk you are taking in an average year has been diluted. Granted, the chance of a CCC bond reaching 5
years is small, but that is reflected in the 1452bp, and should you get to that point, you will then be holding a more valuable bond. Exactly the reverse reasoning explains why higher grade credit curves slope upwards. Because cumulative default probabilities rise at an increasing rate, the back 5 years of the life of a 10-year A-rated bond will be more risky than the initial 5 years, and warrant more spread accordingly.
A wrinkle: the government benchmark So far, we have been comparing bonds with credit risk to an unspecified government benchmark, which we have assumed to pay an annual return of 6%. Talking about the government return is somewhat vague. What we are really after is a comparison of the return of the credit bond and a government bond promising the same cashflows. Our 6% constant return assumption is tantamount to the belief, held with certainty, that the government curve will be flat until the maturity of the longest bond we have priced. Table 7 Rock bottom spreads under alternative government yield curve assumptions (bp) Rock-
Difference from
bottom spread
6% Flat Curve
6% Flat Curve 5
0% Flat Curve 0
Forward Curve 0
Random Curves 0
AA
13
+1
0
0
A BBB
25 72
+1 +5
-1 0
-1 +1
230 506
+19 +54
+1 +3
+4 +13
1036
+94
+14
+46
AAA
BB B CCC
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs, with the following amendments: substitute 0% for the government return to produce the spreads behind the second column. Select the “Research paper forward curve” option on the 8-state calculator for the third column. Here, we are assuming that each of the one year forward rates (of Feb 26, 2001) is the actual rate in the relevant year. These forward rates ranged from 4.1% at one year, to 6.7% at 30years. The "Random Curves" calculations cannot be reproduced with the 8-sate calculator. They simulate interest rate fluctuations around this forward curve using the Cox-Ingersoll-Ross model, assuming the volatility of the 1year rate to be 30%, in line with historical estimates.
While this is a wildly unrealistic view of government rates, its effects on rock-bottom spreads are not terribly serious. Table 7 shows that rock bottom spreads are much the same, irrespective of the way we account for government rates. For example, single-B 10-year rock-bottom spreads differ by only 54bp, whether the government curve is assumed flat at 6% or flat at 0%. In other words, a 100bp inaccuracy in
government rates moves B-spreads by about 9bp. Similarly, whether we use a flat 6% curve, or the current government forward curve, or assume rates vary in line with a standard term structure model, single-B spreads are affected to the tune of 13bp or less. Government rates are not significant because, to a first approximation, they will affect the prices of government and corporate promises of cashflows similarly. Just as (forward) government rates are used to discount the known cashflows of government bonds, they are used to discount the expected cashflows of bonds with credit risk, as the rock bottom price definition above shows. Simulating random government rates does not appear worth the trouble, unless we are valuing bonds where contingencies on government interest rates are important, for example, high-grade callable bonds. Accordingly, our web calculators proxy future one-year rates using the current government forward curve.
Coupon effects While changes in government rates seem to be of secondary importance for rock-bottom spreads, the level of the bond’s coupon can have a significant effect. Table 8 shows that rock-bottom spreads fall at an increasing rate as the bond’s promised coupon falls. For example, an 8% BB bond’s rock-bottom spread is 37bp lower than that of a 16% bond. However, if the coupon is lowered another eight percentage points, to zero, the rock-bottom spread falls by a further 73bp, to 157bp. The source of this effect is very different from the shape of the yield curve, which drives coupon effects on government bonds. A bond that pays a low coupon will have to command a low price, so that it can pay an expected return in excess of governments. If the bond defaults, we assume that the investor receives the same recovery rate, irrespective of coupon. 6 Table 8 10-year rock bottom spreads according to promised coupon Promised Cou on 0%
AA
8%
16%
10
13
14
BBB BB
58 157
72 230
80 267
B
266
506
635
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs but set the coupon to the specified level.
6
This corresponds to the way recovery rates are measured, i.e. as an amount per $100 face amount, irrespective of missed coupons (see [5]). It is also entirely in line with the market’s approach. Some 350 defaults over the last 20 years show no relationship betwee n the prices of defau lted debt, an d the size of the cashfl ows on which the default occurred.
Consequently, the capital loss on a low-coupon bond will be less than on a high-coupon bond. This milder loss in default mean that compensation in the no-default scenarios can be correspondingly lower, and this is reflected in the lower spreads for low-coupon bonds. This result does not necessarily mean that low-coupon bonds are a better deal than high-cou pon bonds. Market spreads may over- or undercompensate for this coupon effect. As in other cases, the appropriate route to determining which offers better value is to calculate their rock-bottom spreads, which correctly price the coupon effect, and then determine which pays the greater surplus over rock-bottom
Average recovery rates Although the uncertainty of recovery rates has little impact on recovery rates, the same cannot be said for the average level of the recovery rate. Table 10 shows the effect of average recovery rates on 10-year rock-bottom spreads, in relation to the $45 assumption we have been using. As one would expect, the effect is larger the lower the credit rating. A rough rule-of-thumb is that each $1 increase in the average recovery rate raises rock-bottom spreads for BBBs, BBs, and Bs by 1,4, and 10bps, respectively. Table 10
Rock-bottom spreads under alternative recovery rate assumptions Basis points per $
Recovery rate average (per $100 principal)
A wrinkle: uncertain recovery rates To this point, a default has been assumed to result in an immediate payout of exactly $45. In practice, there has been a wide range of variation in recovery rates. One study estimates the volatility of recovery rates to be about $23 per $100 of principal. Obviously, the greater the uncertainty about recoveries in the event of default, the higher should be the spread investors need to be induced to take credit risk. Not surprisingly, uncertain ty of recovery rates affects rock bottom spreads through the volatility of credit returns. Perhaps more surprising is the fact that uncertainty of recovery rates has a small impact on the values of credit instruments, shown in Table 9. Although large in dollar terms, the effect of recovery rate uncertainty on rock-bottom prices is small because it is scaled by the probabilit y of default and the diversity score 7 . Table 9
Increase in rock-bottom spreads from maximum possible recovery rate uncertainty Maturity
AAA AA A BBB BB B CCC
1
3
5
10
0 2 0 4 13 32 96
0 2 1 5 14 33 96
0 2 1 5 14 33 88
1 2 2 5 15 33 69
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs, but set the recovery volatility equal to 0.5.
7
To this point, each scenario has res ulted in a single outcome, as depicted in Figure 2. Now, the default scenario comprises a range of outcomes, described by the recovery volatility. The impact of this is to raise the contribution of the default scenario to credit return volatility. Specifically, the square of credit return volatility is raised by the default probability multiplied by the square of recovery volatility. In terms of the one-year BB example of Table 2, the square of credit return volatility becomes ( 7.71)^2 + ( 0.0152)* (23^2)= 59.44+8. 05=67.49. So credit r eturn volat ility rises to $8.22 from $7.71, or $0.51, as a result of accounting for recovery volatility. The effect on the rock-bottom price is considerably less, as this figure is scaled down by the diversi ty score, th e informa tion ratio, a nd the governm ent discount f actor.
AAA AA A BBB BB B CCC
$0
$20
$45
8 21 41 122 407 990 2848
6 18 34 100 325 751 1761
5 13 25 72 230 506 1036
$70
3 8 15 46 143 304 579
0.1 0.2 0.4 1 4 10 32
To produce these figures with the 8-state rock-bottom spread calculator, use the Baseline Inputs, substituting each column’s recovery rate average (expressed as a decimal).
Forward-Looking Rock-Bottom Spreads The relevant credit fundamentals for valuing a security are those expected in the future, which may or may not conform to the historical averages used in the illustrative calculations above. For example, in an economic downswing, default rates and the general direction of changes in credit quality can depart markedly from the average. Similarly, recovery rate expectations may differ from historical averages, as the industrial composition of the market changes. Meaningful rock-bottom spreads require taking a view on these elements of credit fundamentals for each year in the remaining life of the securities being valued. Of all the elements of a view on credit fundamentals, the most burdensome is the frequency of expected changes in ratings and defaults. These are summarized in a credit migration matrix such as Table 4. In this “eight-state” form, there are 49 independent numbers. In principle, a forecast of each of these numbers is needed for each year until maturity, and it would be an enormous task to make these forecasts from scratch. However, for most purposes, a simple approximation seems to suffice. The historical record suggests that movements in ratings are highly correlated across rating categories. For example, Figure 5a charts the frequency of downgrades by Moody’s among investment grade issuers. The experiences of the
Figure 5
Aggregate credit migration (a) Downgrade rates (%)
(b) Default rates (%)
20
25 Dow ngr ade rate
Ba, B Defa ult rate
18
B
90
Caa
16
20
100
Caa Defau lt rate
80
Baa All Investment Grade
Aa 15
14
70
12
60
10
50 All Speculative Grade
8
10
40
6
30
4
5
20
A Ba
2
10
0
0 1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
0 1 98 0
2000
19 8 2
1984
1 98 6
1988
1990
19 9 2
1994
1 9 96
19 9 8
2000
Figure 6
Change in annual credit migration probabilities associated with a 1% increase in… (a) Aggregate investment grade downgrades %
AAA
AAA AA A BBB BB B CCC
-0.756
1.5
0.184 0.003 -0.001 -0.002 -0.001 0.000
AA 0.687 -1.271
0.123 -0.004 -0.005 -0.003 0.000
A 0.067 1.023 -1.069
-0.089 -0.040 -0.015 -0.024
BBB 0.000 0.032 0.820
BB 0.002 0.016 0.097 0.740
-0.843
-0.382 -0.051 -0.037
-0.415
-0.481 -0.105
B 0.000 0.016 0.025 0.121 0.507
CCC 0.000 0.000 0.001 0.010 0.031 -0.375 -0.282 -0.206 -3.354
(b) Aggregate speculative grade defaults D 0.000 0.000 0.000 0.065 0.306 1.207 3.725
4.0
% AAA
1.0
AAA 0.604 0.012 -0.003 -0.003 -0.001 -0.001 0.000
% AAA AA A BBB BB B CCC
AA -0.549 -0.580 -0.158 -0.021 -0.004 -0.002 0.000
BBB 0.000 0.017 0.328 0.142 -0.275 -0.036 -0.098
BB B CCC -0.002 0.000 0.000 0.008 0.008 0.000 0.039 0.010 0.001 0.282 0.046 0.004 -0.942 0.730 0.045 -0.343 -1.266 0.125 -0.276 -0.544 -2.543
D 0.000 0.000 -0.002 0.037 0.476 1.533 3.524
%
3.0
BB
AA
B 2.0
A
0.5
A -0.053 0.535 -0.215 -0.487 -0.029 -0.010 -0.062
BBB
CCC
1.0
0.0 0.0 -0.5
-1.0
-1.0
-2.0 -3.0
-1.5 Up 3
Up 2
Up 1
No change
Down 1
Down 2
Down 3
Down 4
Down 5
AA, A, and BBB sectors have been very similar. They track the aggregate rate of downgrades closely, with correlations of 71%, 94%, and 89% respectively. Indeed, most of the systematic change in the pattern over th e cycle of investment grade credit migration seems to be a shift between the “unchanged rating” state, and downgrades. The pattern for upgrades is much more erratic. Similarly, there has been a strong correlation between the aggregate speculative grade default rate, and th e default and downgrade experience of individual speculative grade rating categories. Figure 5b exhibits the pattern for BB, B, and CCC default rates, whose correlations with the aggregate default rate are 78%, 81% and 33%, respectively. The correlation of the BB downgrade rate with the agg regate default rate has been 37%, while the corresponding figure for B’s is 22%.
Up 5
Up 4
Up 3
Up 2
Up 1
No change
Down 1
Down 2
Down 3
These historical relationships suggest that not much will be lost by taking a view, for each y ear you need to forecast, on at most two aggregates:
• •
investment grade downgrades speculative grade defaults
We then need to translate these aggregate forecasts into forecasts for each element of the credit migration matrix. For example, say you forecast next year’s aggregate investment grade downgrade rate to be 11.5%, which is 4% higher than the 7.5% historical average. How does this translate into a forecast for, say, downgrades from A t o BBB? The process is similar to using an individual stock’s beta to forecast its return, based on a forecast of the market. The slope of a regression of the history of A-to-BBB
downgrades on the history of aggregate investment grade downgrades is 0.82. This slope tells us how much A-toBBB downgrades will deviate from their historical average when aggregate downgrades exceed their historical average by 1%.
grade rows result from adding four times the bottom three rows of Figure 7b to Table 4. (There is nothing to stop the resulting probabilities from being negative. In this case, probability is reallocated from the nearest positive probability, to remove the negative numbe rs.)
From Table 4, the historical average for A-to-BBB downgrades is 5.57%. Since you have forecast aggregate investment grade downgrades to be 4% above their historical average, this implies you expect the A-to-BBB migration probability to be 0.82 x 4%=3.28% above its historical average, or 8.85%.
We would expect rock-bottom spreads to be higher as a result of this view, and to be more elevated, the longer the credit downswing is expected to last. These views are confirmed by Table 11, which shows the consequences of expected downswings lasting through 2001 – 03. In each case, the credit migration probabilities are assumed to revert to historical levels (i.e., those in Table 4) after the last downswing year.
We have estimated these regression slopes for each element of the credit migration matrix, using each of the two aggregate indicators. The top panels of Figure 7 display the slopes that are used by our 8-state web calculator. It seems most sensible to forecast the aggregate associated with the ratings you are most concerned with. The calculator will also accept forecasts of both, using the default forecast for speculative grade credit migration probabilities, and the downgrade forecast for the investment grade ones. Figures 7a and 7b present a bewildering array of numbers, that nevertheless have a pattern to them. This can be better appreciated from the two lower panels of Figure 7, which graph the information in the two tables, respectively. Here, however, the sensitivities of the migration probabilities have been lined up according to the number of ra ting notches moved. So, the “No change” points represent the figures on the diagonals of the tables, while, for example, the “Up 2” point for BBBs gives the sensitivity of BBB-AA upgrades. The investment grade graph shows that, when there is a 1% increase in investment grade downgrades, for each rating category this largely takes the form of a decline in issuers with unchanged ratings, and an increase in those downgraded by one notch. Moreover, the percentage that shifts in this manner is similar across rating categories. The other graph shows how a 1% increase in the aggregate speculative grade default rate translates into changes in individual migration probabilities. There is a decline in both upgraded issuers and the “no change” category, which is distributed not only into one-notch downgrades, but also, where possible, into deeper downgrades. In contrast to the investment grade case, the sensitivities differ among rating categories, the shifts in migration probabilities being more marked, the lower down the rating spectrum we go. To illustrate, say that for as long as the current “credit downswing” lasts, investment grade downgrades are expected to be 11.5% and speculative grade defaults are expected to be 8%. Both of these figures are 4% higher than their respective historical averages. Consequently, to construct the investment grade rows of the credit migration matrix for the downswing years, add four times the top four rows of Figure 7a to Table 4. Similarly, the speculative
Table 11 Rock-bottom spreads under alternative credit downswing views Historical
Downswing lasts for next…
Credit Migration
AAA
12 months
24 months
36 months
120 months
5
5
5
5
8
AA
13
14
15
16
23
A
24
27
30
34
50
BBB
72
82
92
102
143
BB
230
260
289
316
434
B
506
570
623
667
797
1036
1167
1238
1277
1291
CCC
Figure 1, presented on the first page of this paper, shows rock-bottom spreads for the actual bonds in the market, aggregated into broad rating categories, on the assumption that the credit downswing lasts only through the next 12 months. The figures differ from those in the second column of Table 11, which nominally embody the same credit view. For example, in Figure 1, the B-rated rock-bottom spread is 868bp, while the corresponding number in Table 11 is 570 bps. We can use the information presented so far, describing the sensitivity of rock-bottom spreads to changes in input assumptions, to try to reconcile this difference. A summary of the effects involved is presented in Table 12. Table 12 Reconciling BB Rock Bottom Spread Numbers Table 11 vs. Figure 1 Generic Bond 8 states (Table 11)
B-rated rock-bottom spread Inputs Maturity Coupon Recovery rate average Recovery rate volatility Baseline Default Rate
High-Yield Index 18 states (Figure 1)
Change in Rock-Bottom Spread Source
570
868
298
10yrs 8% $45/$100 $0 7%
7.3yrs 9.93% $35/$100 $23 8.96%
30 32 100 16 95 Total
273
Table 6 Table 8 Table 10 Table 9 Table 12
First, the average maturity of B-rated (senior, unsecured) bonds in the JP Morgan High Yield index is 7.3 years, compared with 10 years for the generic bond valued in Table 11. From Table 6, the spread difference between 7 and 10-year B-bonds is 33bps, and so we estimate that the effect of the 2.7 year differences is 30bps (2.7yrs/3yrs*33bps). Second, the average coupon of the index bonds is 9.93%, against the 8% assumed for the generic 10 year. Table 8 shows a 129bps difference in rock-bottom spread between 8% and 16% coupon B-bonds, so we interpolate that moving from an 8% coupon to a 9.93% coupon adds 32bps to the rock-bottom spread. Third, Figure 1 assumes a recovery rate of $35 per $100 of principal, in line with current prices of bonds in the month after they default. This is $10 lower than the baseline recovery rate and from the last column of Table 10 we estimate that it should raise the B-rated rock-bottom spread by 100 bps. Fourth, the baseline recovery volatility is zero. Table 9 shows that B-rated 10-year rock-bottom spreads are 33bps higher when recovery volatility is at its maximum of $50. Interpolating once again, , the historical average of $23 used in Figure 1 raises the rock-bottom spread by 16bps. The largest effect comes from the fact that Figure 1 is based on the default and credit migration numbers for “modified” ratings (B1/B+, etc). The composition of the B-rated sector, is different now from its past average, that resulted in the 7% average default rate in Table 4. So, when we aggregate the historical default rates of B1, B2 and B3-rated bonds, using current outstanding amounts, the resulting default rate is 8.96%, because B3 and B2 bonds are now more prevalent. Now, Figure 7 shows that a 1.53% rise in the B-rated default rate corresponds to a 1% rise in the aggregate speculative grade default rate. So, having a B-rated default rate 1.96% higher than the baseline scenario corresponds to an aggregate default rate that is 1.28% higher in each year (1.28=1.96/1.53). Now we can use Table 11 to estimate the spread effect of this elevated default rate. The Table shows a 297bps difference between rock bottom spreads under the historical credit fundamentals scenario, and under the scenario where defaults are 4% higher for 10 years. Consequently, our 1.28% higher speculative grade default rate would correspond to 95bps (1.28%/4%*297bps). Adding up all these effects gives 273bps, compared to the 298bps difference between the two B-rated rock-bottom spreads with which we started. The remaining 25bps is the result of “second-order” effects of the sources discussed above (we only used linear interpolation), and of interactions among these effects. Nevertheless, it is remarkable how closely one can account for the differences using just these basic tools.
Where to go from here Our exhaustive tour of the mechanics of rock-bottom spreads has, for the sake of clearer exposition, focussed exclusively on plain vanilla bullet bonds of a generic issuer in each rating category. The real world is somewhat more complicated in several ways, and it is well to discuss whether the rock-bottom spread framework is equal to the challenges. One complication is that actual bonds present more elaborate patterns of cashflows than plain vanilla. If anything, this is where the strength of the rock-bottom spread approach lies, as it can deal with any stream of cashflows subject to credit fundamentals risks. Callable and puttable bonds, discount bonds, subordinated paper, Brady bonds, structures with cashflows contingent on ratings changes, can all be valued in terms of their rock-bottom spread or price. Moreover, since these valuations emanate from a single framework, it is possible to make consistent relative value assessments across bonds with very different cashflow structures. Because the market does not presently have consistent yardstick for comparing value among, say, discount bonds and subordinated bonds, callable or not, this may be the place to look for unexploited pockets of value. While the rock-bottom spread framework is punctilious to a fault on cashflow structure, it uses only the limited information on issuers’ credit quality contained in ratings. The problem this creates is that bonds that appear cheap for their rating may be expensive because of the special credit conditions of the issuer, or vice versa. One way around this is to look at large portfolios or averages of bonds, rather than individual bonds. This is obviously the appropriate route for comparing value across broad asset classes. The cheapness or dearness of the bonds as a group cannot be vitiated by i ssuer idiosyncracies, because these have to average out by definition. For example, if B-rated bonds are currently expensive relative to their rock-bottom valuation, then only if today’s B-rated bonds are better quality than those in the past can one escape the conclusion that as a group they are expensive. This does not seem to be so at the moment. However, where the goal is to pick individual bonds, th e rock-bottom spread valuation has to be complemented with better issuer-specific information, either directly from cre dit analysts who follow the industry or issuer in question, or from the equity market. In this way, it is possible to qualify the cashflow valuation with a health check on the issuer. Bonds that appear cheap and healthy should be expected to perform better than those that offer a positive signal in only one, or neither of these respects .
Examples of each of these uses of the rock bottom valuation are now readily available • The effects of callability, discount structures and subordination can be examined using the new RockBottom Spread Calculators on the Credit tab on www.morganmarkets.com [1]. See also Valuing Rating-Trigg Rating -Triggered ered Ste p-up Bon ds [6] [6]
•
References
Portfolio Research
1 Introdu cing the J. P. Morgan Roc k-Bottom k-Bott om Spread 2001, Mans oor Sirinathsingh Calculator , July 12, 2001, 2 Emerging Market Collat erlaize d Bond Obliga tions: An 1996, Moody's Investors Service Overview , October 1996, 3 Valuing Credit Fundamentals: Rock Bottom Spreads, November 17, 17 , 1999, Peter Pete r Rappoport Rappopor t 4 Default and Recovery Rates of Corporate Bond Issuers: 2000, 2000, Moody's Investors Service erythi ng You Want ed to Know abo ut 5 Almost Ev erything Recoveries Recov eries on o n Defaulted Defau lted Bonds Bo nds, Edward S. Altman and V. Kishore, Financial Analysts Journal, Nov/Dec 1996, pp 57-64.
6 Valuing Rating-Triggered Step-up Bonds, Mansoor Sirinathsingh k-Bott om Roundup , July 12, 2001, 7 Introdu cing the Roc k-Bottom Peter Rappoport, Mansoor Sirinathsingh
8 The Rock-Bottom Roundup , July 12, 2001, Peter Rappoport, Mansoor Sirinathsingh 9 Pickin g High-Y ield Bonds Bo nds, July 12, 2001, Peter Rappoport, Mansoor Sirinathsingh 10 Rock-Bottom Rock-Bo ttom Spread Sp read Tu torial toria l (Excel spreadsheet) Frank Frank Zheng. Accessible on the Credit tab on www.morganmarkets.com
•
A comparison of market spreads and rock-bottom spreads across asset classes is given in the Rock-Bott Rock- Bottom om Roundup Round up [7,8], which compares US High Grade and High Yield Corporates, and Emerging Markets Sovereigns Picking High Yield Bonds [9] describes the performance performan ce of a rule that se lects bonds bond s whose rock bottom valua tion is not con tradicted b y their isu ers’ equity performance.
New York Peter Rappoport Mans Mansoo oorr Sir Sirin inat aths hsin ingh gh Frank Zheng
(1-212) 648-1268 (1-2 (1-212 12)) 648648-49 4915 15 (1-212) 648-1860
Lond on Alan Cubbon Guy Coughlan St ep hen T ang
(44-20) 7325-5953 (44-20) 7777-1857 (44-20) 7777-1534
Norwa y Halvor Hoddevik
(47-22) 941-978
Tokyo Tatsushi Kishimoto
(81-3) 5573-1521
25.0
BBB
20.0 15.0 10.0
A
5.0
AA AAA
0.0
years
0
1
2
3
4
5
6
7
8
9
10 10
50
European transition
40
US transition
30 20 10
0 -10 -20 AAA
AA
A
BBB
180 160 140 120 100 80 60 40 20 0 -20
Rock-bottom Market
A seasoned
A recent
BBB seasoned
BBB recent
4.0
AAA
3.0
AA
2.0
A
1.0
BBB
0.0 -1.0 -2.0 -3.0 -4.0 up 3
up 2
up 1
unch unchan ange ged d down down 1
down down 2
down down 3
down down 4
down down 5
down down 6
200 180 160 140 120 100 80 60 40 20 0 -20
Rock-bottom Market
A seasoned
A recent
BBB seasoned
BBB recent
200 180 160 140 120 100 80 60 40 20 0 -20
Rock-bottom Market
A seasoned
A recent
BBB seasoned
BBB recent
AAA AA A BBB BB B CCC
AAA AA A BBB BB B CCC D 93.63 5.88 0.37 0.09 0.03 0.00 0.00 0.00 0.65 91.72 6.96 0.51 0.02 0.10 0.02 0.01 0.08 2.09 92.10 4.99 0.50 0.21 0.01 0.03 0.03 0.27 4.89 89.32 4.28 0.84 0.12 0.24 0.03 0.05 0.42 6.81 84.08 6.58 1.01 1.03 0.00 0.11 0.30 0.46 5.81 83.69 3.57 6.07 0.17 0.00 0.34 1.02 2.05 11.26 59.04 26.11
AAA AA A BBB BB B CCC
AAA AA A BBB BB B CCC D 92.99 6.72 0.29 0.00 0.00 0.00 0.00 0.00 0.36 91.48 7.73 0.43 0.00 0.00 0.00 0.00 0.00 2.37 93.15 4.18 0.30 0.00 0.00 0.00 0.00 0.19 6.32 92.34 0.77 0.19 0.00 0.19 0.00 0.00 1.07 4.81 87.70 6.42 0.00 0.00 0.00 0.00 1.56 1.56 4.69 82.81 4.69 4.69 0.00 0.00 0.00 0.00 0.00 0.00 75.00 25.00
Introducing the Rock-bottom Roundup •
Our new publication, the Rock-bottom Roundup compares value among
− − −
US investment grade corporate bonds US speculative grade corporate bonds Emerging markets sovereign bonds
•
It uses JP Morgan’s proprietary Rock-bottom Spread (RBS) framework to value credit risk consistently across markets
•
The more the market spread of an asset class exceeds its RBS, the better the value, all other things equal
This note is intended as a users’ guide to our Rock-bottom Roundup publication, which provides a uniform comparison of value among US Investment Grade and Speculative Grade Corporate bonds, and Emerging Markets sovereign bonds. The Roundup will be published every three months, and occasionally more frequently if changes in credit conditions warrant. Comparing the raw market spreads of the three asset classes does not make sense, because their exposures to credit and liquidity risk are so different. JP Morgan’s rock bottom spread framework effectively filters out the credit risk component. The rock-bottom spread of a bond or group of bonds is what you need to be paid to earn sufficient return for the credit risk involved. So, the difference between market spread and rock bottom, or surplus spread , indicates your reward for bearing non-credit exposures, notably illiquidity. All other things equal, the higher the surplus spread, the better. Of course, all other things are not necessarily equal; an asset class with a high surplus over rock-bottom may be bad value, because its illiquidity is too great, or its market price volatility is too high. Looking at rock-bottom spreads provides the right place to start to investigate these issues.
A bond’s rock-bottom spread combines the broad aspects of its credit exposure – those driven by its rating, coupon and maturity, seniority, call provisions -- with views on aggregate credit trends and expected recovery rates, into a measure of how much spread is needed for bearing the credit exposure. It does not factor in issuer-specific conditions, such as whether their earnings are on track, or if a patent application has been granted, except insofar as these find their way into the issuer’s rating. Consequently, it is quite plausible that there are special circumstances that make a specific issuer good value, even though its market spread is less than its rock-bottom spread. However, in the aggregate, the special circumstances cannot dominate. Thus, our emphasis is on relative value among broad asset classes, distinguished by the characteristics that go into rock-bottom spreads. We compare surplus spreads across corporates and emerging markets sovereigns, and among rating categories within each. Similarly, we compare groups of bonds according to their seniority, and by their cashflow structure. Each asset class rock-bottom spread aggregates the rock bottom spreads of its component bonds, weighted by outstanding amounts. The bond-level rock-bottom spreads depend on three distinct types of inputs
•
• •
Bond parameters : coupon, maturity, seniority, cashflow structure (bullet, discount, callable, etc), rating Market structure parameters : portfolio diversification Credit fundamentals views : Expected pattern of future aggregate defaults and downgrades Expected recovery rates, and their volatility
We focus on portfolios that achieve the maximum diversification possible in each market. Consequently, investors can differ only on the third group of inputs. The
Rock-bottom Roundup uses credit fundamentals views that appear to represent current views in the market. In particular, we reference the 12-month forecast of default rates published in Moodys’ Monthly Default Report. We use the most recent average of market prices of defaulted bonds, also to be found in Moodys’ report, to characterize expected recovery rates. Of course these views are only representative. Should your views differ from the ones in the Roundup, you can produce your very own RockBottom Roundup numbers, using the Rock-bottom Spread calculators on the JP Morgan website. Table 1 of the Roundup presents a cross-market comparison for speculative grade and investment grade corporates, and emerging markets sovereigns. For emerging markets the spreads presented are stripped spreads. As is consistent with market practice, we define bonds trading at prices below 50 as distressed. Treating these bonds as though they are certain to default, and reducing the default probabilities on the remaining bonds proportionately, we calculate the rock-bottom and market
spreads of the non-distressed bonds. For emerging markets sovereigns we consider two possible scenarios with respect to portfolio composition. The first is for the dedicated emerging markets investor, whose portfolio comprises only emerging markets sovereign bonds (Dedicated). The second is for the investor who buys emerging markets sovereigns into a maximally diversified corporates portfolio (Crossover). Tables 2 through 5 present for senior unsecured, subordinated, senior secured and discount bonds, the rock bottom and market spreads, aggregated by rating category. Given their different levels in the capital structure, each of these types of bonds have different recovery rates, and their rock-bottom spreads are calculated accordingly. Tables 6 and 7 summarize the results for emerging markets sovereigns, showing both stripped and blended spreads.
Rock-bottom Roundup • • • •
B-rated U.S. corporates have not adequately priced in the recession… … while BB-rated corporates offer better value Emerging markets are particularly attractive to crossover investors For the crossover investor, high-grade emerging markets are priced similarly to A- and BBB-rated U.S. corporates
Table 1
Cross-market summary Rock bottom spread
Market Spread
Difference
274 989 844
412 744 702
138 -245 -142
509
839
330
228 407 642
255 487 881
27 80 239
401
839
438
145 274 457
255 487 881
110 213 424
67 44 98
191 180 233
124 136 135
High Yield Corporates BB B B Non-distressed
EMBIG (Dedicated) Inv Grade BB B
EMBIG (Crossover) Inv Grade BB B
High Grade Corporates AA A BBB
U.S. Corporates Table 2 Senior unsecured bonds
Aaa Aa1 Aa2 Aa3 A1 A2 A3 Baa1 Baa2 Baa3 Ba1 Ba2 Ba3 B1 B2 B3
RBS
Market
Surplus
Coupon
Maturity
# Bonds
10 8 24 26 37 30 48 67 81 135 187 270 461 663 965 1429
93 106 127 120 143 161 197 206 213 273 339 479 480 638 645 1021
83 98 103 94 106 131 149 139 132 138 152 209 19 -25 -320 -408
6.72 6.51 6.91 6.82 7.2 7.2 7.51 7.48 7.54 7.98 8.25 8.66 8.96 9.72 9.84 10.36
13.57 11.34 16.05 12.65 18.05 14.8 16.94 17.89 14.94 15.57 8.23 7.15 7.43 6.71 7.62 7.45
144 35 130 232 222 485 303 391 329 334 90 77 77 65 89 94
RBS
Market
Surplus
Coupon
Maturity
# Bonds
8 4 8 18 28 28 28 35 67 61 166 213 283 382 611 858
122 135 139 144 147 153 166 187 210 224 344 413 413 449 525 771
114 131 131 126 119 125 138 152 143 163 178 200 130 67 -86 -87
7.3 6.86 7.55 7.39 7.09 7.16 7.44 8.03 8.28 7.79 9.23 9.43 9.3 9.59 9.65 10.42
15.72 10.55 9 13.02 10.54 14.03 10.91 7.68 11.59 4.63 9.04 8.99 7.45 7.5 7.74 7.32
11 4 1 72 133 93 28 3 8 6 19 18 47 36 126 170
Table 3 Subordinated bonds
Aaa Aa1 Aa2 Aa3 A1 A2 A3 Baa1 Baa2 Baa3 Ba1 Ba2 Ba3 B1 B2 B3
Table 4 Senior secured bonds
Ba1 Ba2 Ba3 B1 B2 B3
RBS
Mark et
Surplus
Coupon
Matur ity
# Bonds
143 238 368 463 882 1152
313 524 492 529 739 1135
170 286 124 66 -143 -17
8.41 11.09 9.77 8.75 9.88 11.24
8.89 8.08 6.89 11.01 3.73 6.79
5 2 15 10 11 12
RBS
Mark et
Surplus
Coupon
Matur ity
# Bonds
438 --726 995 1493
443 --958 841 1337
5 --232 -154 -156
10.27 --10.55 10.77 11.75
5.26 --6.32 8.16 7.19
2 --5 11 27
Table 5 Discount bonds
Ba1 Ba2 Ba3 B1 B2 B3
U.S. Corporates forecasts used in Tables 1 - 5 IG downgrade rates: 12% for the next year, 7% thereafter
14%
12%
HY grade default rates: 9% for the next year, 4% thereafter
10%
8%
6%
4%
HY Default Rate
2%
IG downgrade rate 0%
Recovery rates: Senior secured: Senior unsecured: Subordinated: Discounts
53% 36% 16% 36%
Recovery volatility: Diversity score:
23% 70
Source: Moody’s Investors Service Default Report 2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Emerging markets forecasts used in Tables 6 - 7
Emerging Markets
Recovery rate: Recovery volatility: Diversity score:
Table 6
Emerging markets summary Blended RBS
Blended Market
Stripped RBS
Stripped Market
207 407 608
228 482 825
228 407 642
255 487 881
IG BB B
Table 7
Country summaries S&P Moodys Blended Blended Stripped RBS Market RBS rating rating CCC Caa2 1266 707 1266
Country Alge ria
BBB-
Chile
B+ A-
China
BBB
Colombia
BB
Cote d'Ivoire Croatia
CCC BBB-
Ecuado r
CCC BBB-
690
994 575
1574 859
1044 609
1652 924
B2 Baa1
415 129
524 188
529 129
658 183
A3
165
132
165
126
Ba2
444
440
444
458
Caa2 Baa3
857 285
2131 212
857 285
2313 199
Caa2
963
1447
963
1481
Ba1
352
365
352
369
Korea
ABBB
A3 Baa2
93 146
46 149
93 146
41 143
Leba non
B+
B2
813
529
813
529
Baa2
184
211
184
209
Baa3 Ba1 Caa2
229 363 692
276 472 904
270 363 1113
331 451 1474
1251
1353
1251
1338
328
397
328
400
Argentina Brazi l Bulgaria
Egypt
Hungary
Malaysia Moro cco Nigeria
BBB BB+ BB CCC
Mexico
Caa1 B1
Stripped Market
B-
Caa1
Panama
BB+
Ba1
Peru
BB-
Ba3
529
616
529
618
Philippines
BB+
Ba1
423
570
423
575
Poland
BBB+
Baa1
134
200
144
210
Russia
B
B3
661
827
661
831
South Africa
BBBBBB-
Baa3 Baa3
244 238
276 166
244 238
273 164
B1 Caa1
819 1363
984 1550
819 1363
994 1534
252 525
282 776
252 623
286 933
Pakistan
Thailand
BCCC
Turkey Ukraine
BBBB
Uruguay Venezuela
Baa3 B2
Positive/Negative outlooks
17.5% 7.5% 9
Bondpicking Rule
20%
Index
10% 0% -10% -20% 1999.II
2000.I
2000.II
2001.I
Average
credit ratio =
rock – bottom price market price
All Inde x Bonds
1598
1079
No equity pr ic es
Equity Filter
A
519
B
648
431
CCC, No t Ra te d, Dis tre ssed,.. .
Vanilla Filter
Equity and Rock Bottom Signals
Conflicting signals
C 243
No View
Eq ui ty : Ne gat iv e RB : Exp en siv e
D 143
Sells
45
Buys
Eq ui ty :Po sitiv e RB : C h ea p
E
Compare market and rock-bottom prices 6 months of equity returns
6 month holding period
Holding period
Trade on recommendations on...
1999.II 2000.I 2000.II 2001.I
July 1, 1999 Jan 2, 2000 July 1, 2000 Jan 2, 2001
Unwind trades on...
Dec 31, 1999 June 30, 2000 Dec 31, 2000 June 30, 2001
UTILITY TRANSPORTATION SERVICE RE TAI L ME TA LS MIN ER ALS
ME DIA EN TER TAI NM ENT MA NUF AC TURIN G INF OR MA TIO N TECHNOLOGY HO US ING
HE ALT HC ARE GAMING/LEISURE FOREST PROD CONTAINERS FOOD/TOBACCO
FOOD A ND DRUG FINANCIAL EN ER GY CONSUMER NO N-D UR ABLE S CONSUMER DU RAB LES CHEMICALS AE ROS PA CE % return -10%
0%
10%
1999.II
2000.I
20 % 2000.II
3 0%
40%
2001.I
Bond price UST price
D B
C A
Put option price
Rock bottom price
Equity cushion
2.5%
1.5%
0.5%
-0.5% 1997II
1998I
1998II
1999I
1999II
2000I
2000II
2001I
Average
credit ratio =
rock – bottom price market price
Compare market and rock- bottom prices 6 months of equity returns Holding period
1997.II
Trade on recommendations on...
July 1, 1997
.
.
.
.
.
2000.I 2000.II 2001.I
6 month holding period
.
Jan 2, 2000 July 1, 2000 Jan 2, 2001
Unwind trades on...
Dec 31, 1997 . . .
June 30, 2000 Dec 31, 2000 June 30, 2001
m u m i x a M
g e n g i a k r c r o e v a r r r A T E
1.3
7.3
6.7
-0.1
2.1
1.12
1.0
1.16
Equity Equity & RB
-0.3 -0.2
0.9 4.3
0.49 2.17
0.5 1.9
1.02 1.12
RB Only
-0.9
2.8
0.89
1.6
0.55
Equity Equity & RB RB Only
-0.2 -0.4 -0.9
0.8 1.3 1.9
0.44 0.99 0.86
0.4 0.8 1.2
1.07 1.28 0.72
Index return Outperformance Baseline Strategy Buys
Sells
n o i t a m o r i o t f a n R I
m u m i n i M
6 s t h s r t o n o W m Outperformers % of Index Bonds
s 6 h t t n s e o B m
e g a r e v A
38
77
58
-7 -10 -16
8 44 36
3 15 9
23
62
42
-7 -8 -12
8 24 22
3 11 8
…relative to index
% of Buys
Equity Equity & RB RB Only Underperformers % of Index Bonds …relative to index
% of Sells
Equity Equity & RB RB Only
Aerospace Building
Consumer
Average Issuers
Average Capitalization ($billions
Aerospace
8.1
12.9
Building
7.8
2.6
Land dev./Real Estate
1.8
0.6
Mobile/Modular Homes
0.4
0.1
Beverages
9.1
9.6
Cosmetics/Toiletries
2.8
3.5
Food
19.0
20.3
0.6
0.3
Home Furnishings
Energy Finance
Household Products
1.6
0.3
Leather/shoes
1.0
0.2
Retail Stores
23.9
25.2
Oil and Gas
41.9
31.3
Banking
98.1
88.2
Finance
101.8
126.8
Investment
Health
HiTech Insurance Leisure Manufacturing
8.8
5.3
Securities
14.5
39.3
Drugs-Generic and OTC
10.6
8.0
Health Care Centers
2.0
1.1
Medical equipment/supply
6.3
2.9
Data Processing
6.8
9.5
Electronics/Electric
17.8
13.4
Insurance
26.8
13.4
Filmed Entertainment
1.1
1.3
Leisure/Amusement
12.1
9.0
Auto parts/equipment
4.8
2.4
Auto/Truck mfrs.
4.8
13.6
Chemicals
17.6
9.1
Coatings, paint, varnishes
1.6
0.4
Containers
2.9
1.2
Glass/products
2.1
1.2
14.0
7.5
Machinery Manufacturing/Distr
4.5
3.6
Office Equipment
1.5
1.0
Paper/Products
14.9
10.2
Plastic/Products
7.0
6.5
Rubber
3.0
1.1
Specialty instruments
0.8
1.0
Textiles
1.9
0.4
Tobacco
1.9
1.2
Media/Telecom Advertising/Communications
0.1
0.1
7.4
8.3
Broadcasting
Metals/Mining
Other
Graphic Arts
1.8
0.5
Publishing
13.5
16.0
Telecommunications
44.0
51.4
Aluminum
3.3
1.2
Metal
0.5
0.2
Mining/Diversified
9.4
3.0
Steel-Iron
2.4
1.0
Conglomerate/diversified
2.8
2.4
Foreign
1.0
0.6
Pollution Control Real Estate Investment Trust
Service
Transport
Utility
1.4
1.2
21.9
7.1
Food serving
2.0
0.6
Hotels/Motels/Inns
1.4
0.8
Services
3.6
1.5
Air Transport
6.0
5.5
Auto rental/service
1.8
2.2
Railroads
9.1
13.9
Transportation
4.4
2.2
Trucking
0.5
0.1
Util.-Diversified
11.6
7.7
Utilities-Electric
36.4
25.5
Utilities-Gas
24.5
15.4
8% Bond Selection 6%
Industry Selection
4%
2%
0%
-2%
I I 7 9 9 1
I 8 9 9 1
I I 8 9 9 1
I 9 9 9 1
I I 9 9 9 1
I 0 0 0 2
I I 0 0 0 2
I 1 0 0 2
e g a r e v A
5%
4%
1-yr holding period
6-month holding period
3-month holding period
3%
2%
1%
0% 1997II
1998I
1998II
1999I
1999II
2000I
2000II
2001I
Average to 2000II
-1%
credit ratio =
rock – bottom price market price
Market
Neutral Industries Overweight Industries
Industry Selection
Underweight Industries
Buy best bonds in industry
Bond Selection
Sell worst bonds in industry
Industry View
Performance vs Index BestIndustry looking bonds
Overweight Consensus
Worstlooking bonds
0
Underweight Consensus Varied (50/50)
0
3.5%
2.5%
1.5%
Market variation Bond variation
0.5%
Industry variation
0 1997II
1998I
1998II
1999I
1999II
2000I
2000II
2001I
Market
1.5%
Rock-Bottom rule
Industry type
Out Rates of Occurrence performer
0.7%
x e d Out n i performs s v d Under n o performs B
Underperformer
70%
41%
30%
59%
Industry type Success rates n o Buys i t i s o p d n Sells o B
Outperformer
Underperformer
79%
54%
40%
64%
0.5%
-0.5%
I I 7 9 9 1
I 8 9 9 1
I I 8 9 9 1
I 9 9 9 1
I I 9 9 9 1
I 0 0 0 2
I I 0 0 0 2
I 1 0 0 2
e g a r e v A
2
Market = Variation
2
2
Industry Bond + Variation Variation
Valuing rating-triggered step-up bonds •
Rating-dependent coupons add to the value of bonds such as the most recent DT and BT issues, but to a degree that critically depends on:
•
-
the exact form of rating dependence
-
bond maturity
-
current rating
These results flow from the JPMorgan Rock Bottom Spread framework
During the past year, telecom operators such as BT, DT, and KPN issued bonds that included step-up language to protect investors in the event of a downgrade. The bonds pay coupons which depend upon the issuer’s current rating, as shown in Chart 1. Coupon step-ups are in effect credit options, but valuing these options using traditional derivative methods is difficult. The main questions addressed in this piece are: (1) how should bonds with ratings-triggered coupon step-ups be valued and (2) how is the spread on these bonds likely to change in the event of downgrades.
presence or absence of a step-up clause, we can value the step-up by comparing the credit spreads on two identical bonds, one with a step-up clause, and one without. Our previous work on pricing the fair compensation for bearing credit risk (Valuing Credit Fundamentals: Rock Bottom Spreads, November 1999) provides a natural framework for measuring the credit component of a bond’s market spread, or what we term it’s Rock Bottom Spread (RBS). Rock-bottom spreads are essentially reservation spreads for credit risky bonds. This valuation draws only on credit fundamentals data that are essentially external to the market, such as default rates and recovery rates, and on the investor’s risk tolerance. Basically, the RBS framework values a bond by tracing its future possible credit ratings and combining the probability of these ratings occurring with what the bond will pay given each of these future ratings. A traditional bond’s cashflows do not vary from one rating to another, except when the bond defaults. Capturing the effect of cashflows that change in a prescribed way as the rating changes is a simple amendment to this framework.
Chart 1
Applying the RBS methodology to the BT and DT bonds gives the rock-bottom spreads for these bonds. Removing the step-up provision and applying the RBS analysis gives the rock-bottom spreads for plain bonds. The difference between these two numbers is the value of the step up. These values are presented in Table 1.
Coupons step up when ratings decrease (%) 13 12
BT 7.625%
11 Table 1
10
Value of step-up clauses for BT and DT bonds
9 8
DT 7.75% $05
7 6 Aaa
Aa3
A3
Baa3
Ba3
B3
Market spreads can generally be regarded as compensation for two different risks – credit risk and liquidity risk. Thus, we can think of partitioning the market spread into two discrete components, a credit spread, which compensates for the probability of loss due to defaults, and a liquidity spread. Assuming that the liquidity risk of a bond is not affected by the
Bond
BT BT BT DT DT DT
7.625% 8.125% 8.625% 7.750% 8.000% 8.250%
$05 $10 $30 $05 $10 $30
Rating
Value of step-up
A2/A A2/A A2/A A2/AA2/AA2/A-
16 bps 27 bps 44 bps 7 bps 10 bps 14 bps
These results assume a general credit fundamentals view of a 34% recovery rate on defaulted debt, and an investment grade downgrade rate of 12% for the next
year, followed by the historical rate of 7% for the remaining years. The BT bonds step up 25bps per rating notch per agency below A3/A-, and the DT bonds step up 50 bps if ratings go below A3 and A-, as shown in Chart 1. Coupons step down in the exact opposite manner if the bonds are upgraded. This explicit valuation of the step-up clause makes it easier to determine what the market spreads for these bonds should be. For example, if a plain 10yr bond, with an 8.125% coupon and credit quality similar to that of BT is trading in the market at T+280 bps, we would expect the 10yr, 8.125% BT bond to be trading somewhere near T+253 bps, as a result of the step-up clause. S&P’s and Moodys’ negative outlook on DT prompts the question of what the step-up clause would be worth if the company were downgraded. To evaluate this, we calculate the RBS of the bonds as if they had a lower rating, and subtract that from the RBS of a bond without the step-up. In each case we compare the credit spread on the step-up bond, with a plain bond having the same coupon as the step-up bond would if it had been downgraded. For example, to value the step-up clause for the DT 8% $10, if it were downgraded to Baa1, we compare it to a plain bond having a coupon of 8.5%, as this is the coupon the DT bond would pay if it were rated Baa1. Table 2 gives the results of this analysis. Table 2
Value of step-up clauses for downgraded bonds (bps) Bond
BT BT BT DT DT DT
7.625% 8.125% 8.625% 7.750% 8.000% 8.250%
$05 $10 $30 $05 $10 $30
A2
A3
Baa1
Baa2
16 27 44 7 10 14
33 47 60 15 18 20
22 32 41 -10 -10 -12
13 18 23 -5 -7 -9
As is evident from Table 2, the step-up clause has the greatest value in the A3-rating state. This is not surprising as it is in this state that there is the greatest expected benefit from the step-up clause. Somewhat surprising at first glance is the negative value for the DT bonds in the Baa1 and Baa2 states. This is easily understood when one considers that relative to a plain
Baa1-rated bond, the DT bonds have a step- down clause, i.e. if the bonds are upgraded the coupon decreases, while further rating downgrades have no effect (see Chart 1). Using the RBS framework and the above results we may also evaluate how the spreads on the step-up bonds are likely to change if the bonds are downgraded. Consider a plain A2-rated, 10yr, 8.0% bond, trading at a spread of 280 bps. Assuming liquidity spreads remain constant and given the general credit fundamentals view mentioned above, the RBS framework suggests that this bond should trade at 294 bps, if downgraded to A3, for a spread widening of 14 bps. Using Table 2, the value of the step-up clause for the DT 8.0% $10 is 10 bps, if DT is rated A2, and 18 bps if DT is rated A3. Hence this bond should trade at a spread of 270 bps (280 bps – 10 bps), if rated A2 and T+276 bps (294 bps – 18 bps), if rated A3. This corresponds to a spread widening of 6 bps. Thus on the plain bond, the spread widens by 14 bps on downgrade, while the DT bond widens by 6 bps. This analysis for the other bonds is shown in Table 3. Table 3
Spread widening due to downgrades (bps) Downgrade from: A2 to A3 A3 to Baa1 Baa1to Baa2 Plain 7.750% $05 8 16 19 BT 7.625% $05 0 28 28 DT 7.750% $05 0 41 14 Plain 8.000% $10 14 19 25 BT 8.125% $10 0 34 38 DT 8.000% $10 6 48 20 Plain 8.250% $30 18 22 26 BT 8.625% $30 2 40 44 DT 8.250% $30 13 53 21
Thus, while the step-up clause affords some protection against spread widening given an A2 rating, it actually causes the spread widening in successive downgrades to be more severe than that of a plain bond. To summarize, our analysis indicates that the step-up clause adds value given an A2 or A3 rating for both BT and DT bonds, while it actually makes the DT bonds cheaper given a Baa1 or Baa2 rating . Furthermore, the step-up clause affects the way the market spread on these bonds changes in downgrades thereby making them more or less attractive than plain bonds depending upon their current rating.
EMBI px+
EMBI px+ EMBI px+ + EMBI px
ar et +
px EMBI EMBIpx
Rock ottom
erence
587
604
-17
MLHY
451
533
-82
Difference
136
71
+
EMBI px
1600 1400 1200
1103
+ EMBI px
1000 80 0 60 0
58 7
40 0
45 3
20 0 0 Jan 98
Jul 98
Feb 99
Aug 99
Mar Jan 28 ’0000
1200 1000 80 0
78 6
60 0
EMBI px+ EMBI px+ + EMBI px
EMBI px+ 45 1
40 0
30 7
20 0
EMBI+px
60 MLHY
50 0 Nov 86
Jan 89
Mar 91 May 93 Aug 95
Oct 97
Dec 99 Mar 02
EMBI px+
40 30 20 10 0 BBB
BB
B
CCC
EMBI px+ EMBI px+ EMBI px+
Corporates Long-term
Next two years
Upgrades
Downgrades
Defaults
Upgrades
Downgrades
-
11.3
0.00
-
12.0
0.00
AA
1.1
10.2
0.01
0.7
11.5
0.01
A
3.0
6.8
0.01
3.0
8.6
0.01
BBB
7.5
7.2
0.16
4.9
8.8
0.16
BB
6.4
8.6
1.50
3.0
11.3
2.10
B
7.5
2.8
7.09
3.8
4.8
9.49
11.0
-
26.15
6.0
-
33.15
Upgrades
Downgrades
Defaults
Upgrades
Downgrades
-
2.8
0.00
-
2.4
0.00
AA
0.7
3.0
0.00
1.0
2.2
0.00
A
4.8
4.4
0.23
4.8
3.3
0.21
BBB
5.2
8.3
0.30
6.8
7.4
0.23
BB
6.5
7.3
1.82
8.6
5.7
1.44
17.2
2.5
5.43
19.5
1.3
4.03
9.8
-
13.00
12.8
-
9.06
AAA
CCC
Defaults
Sovereigns Long-term
AAA
B CCC
Defaults
AAA
EMBI px+
Next two years
AAA
AA
A
BBB
BB
B
CCC
Default
97.2
2.8
0.0
0.0
0.0
0.0
0.0
0.0
AA
0.7
96.2
1.6
0.2
0.6
0.7
0.0
0.0
A
0.0
4.8
90.6
4.4
0.0
0.0
0.0
0.2
BBB
0.0
0.0
5.2
86.1
6.8
1.6
0.0
0.3
BB
0.0
0.0
0.0
6.5
84.4
5.9
1.4
1.8
B
0.0
0.0
0.0
0.2
17.0
75.0
2.5
5.4
CCC
0.0
0.0
0.0
0.0
0.0
9.8
77.3
13.0
30 25
Activity
20 15
10
Drift
5 0 -5 -10 Dec 90
Oct 92
May 96
Mar 98
Dec 99
Customized + EMBI+EMBI px
MLHY Credit quality and composition (%) BBB
0.0
6.8
BB
40.7
38.5
B
51.0
54.0
8.3
0.6
9.32
8.46
7.9
10.1
70
5
CCC Coupon (%) Maturity (yrs)
Aug 94
Diversity score Recovery value ave rage (per $100 face)
$45
$17.50
Long-term default rates 6.4
3.7
2.0
-0.9
Rock-bottom spread (bps)
533
604
Market spread (bps)
451
587
(Index average %) default rate adjustment (%) (credit cycle for next 2 yrs)
MLHY
533bp Better EM Composition -114bp Lower EM Diversity +214bp Lower EM Recovery +332bp Safer EM Credit Migration -205bp Better EM Credit Outlook -156bp + EMBI px
604bp EMBI px+ EMBI px+ EMBI px+ EMBI px+ EMBI px+
EMBI px+ EMBI px+
Corporates Optimistic
Long-term
Pessimistic
0
0
0
AA
0.01
0.01
0.01
A
0.01
0.01
0.01
BBB
0.20
0.16
0.20
BB
0.3
1.5
3.6
B
2.3
7.1
15.5
CCC
8.0
26.2
50.6
1.95
6.4
13.6
AAA
MLHY
Sovereigns Optimistic
Long-term
Pessimistic
0
0
0
AA
0.00
0
0.00
A
0.21
0.2
0.90
BBB
0.23
0.3
1.20
BB
1.4
1.8
2.8
B
4.0
5.4
6.7
CCC
9.1
13.0
26.0
EMBI+px
2.8
3.7
4.9
AAA
+ EMBI px
EMBI px+
EMBI px+ EMBI px+
20 16 12
Market
Credit Fundamentals
8 4 0 HY
+ EMBI+px px EMBI
e u l a v o l i o f t r o P
3.0
3.0
2.5
2.5
2.0
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0.0
0.0 0
1
2
3
4
5 6 Horizon (yrs)
7
8
9
10
3.5
3.5
High yield Emerging Markets
3.0
3.0
2.5
2.5
2.0
2.0
1.5 1.0
1.5 1.0
0.5
0.5
0.0
0.0 0
1
2
3
4
5
6
7
8
9
10
•
•
•
Exhibit 1
Converging EM and HY spreads… (bps) 1,400 1,200 EMBI Global sovereign spread
1,000 800 600
Merrill Lynch high yield spread (over 10y UST)
400 200 Jan 99
Jun 99
Nov 99
Apr 00
Sep 00
Exhibit 2
…conceal big differences in credit fundamentals Market spread minu s rock-bottom spread (bps) 250
EM 200
EM BB EM B HY BB
150 100
HY
50 0 -50
HY B
Probability o f upgrade, downgrade, no change
Probability of default
Portfolio diversity
Recovery rate
Credit fundamentals exposure
Exhibit 4
Sovereign ratings continue drifting upwards Ratio of number of upgrades to number of downgrades
a y 9 0
S e p 9 1
Source: S&P
J a n 9 3
J u n 9 4
O c t 9 5
M a r 9 7
J u l 9 8
D e c 9 9
Ratings outlook of major emerging markets sovereigns are predominantly positive S&P
Moody’s
Postive
Negative
Postive
Negative
Brazil
Colombia
Brazil
Croatia
Cost a Rica
C roati a
Cost a Ric a
Paki stan
Greece
Egypt
Hungary
Ukraine
Hungary
Paraguay
India
Vietnam
Iceland
Peru
Indonesia
Lebanon
India
Kazakhstan
Korea
Kuwait
Malaysia
Malaysia
Mexico
Russia
Turkey
Slovenia South Africa Tunisia Turkey
Source: S&P and Moody’s, as of October, 2000
Exhibit 3
9 8 7 6 5 4 3 2 1 0M
A p r 0 1
Exhibit 5
Outlook influences the probability of upgrade Probability of one notch upgrade by rating and out look 40% 35%
Negative
Stable
Positive
30% 25% 20% 15% 10% 5% 0% A
BBB
BB
B
Exhibit 6
A negative outlook entails highest default probability Probability of default by rating and outlook 12% P osi ti ve
10%
S table
Ne gati ve
8% 6% 4% 2% 0% A
BBB
BB
B
Exhibit 7
Rating outlooks affect sovereign rock-bottom spreads Rock-bottom spreads for EMBI Global sovereigns by rating and outlook 800 700
Positive
Stable
A
BBB
Negative
600 500 400 300 200 100 0 BB
B
Exhibit 8
Most EMBI Global emerging markets countries look attractive relative to their rock-bottom spread S&P Rating and
Rock-bottom
outlook†
spread
Moody’s
Rati ng and
Rock-bottom
outlook†
spread
494
EMBI Global
Average Rock-bottom
Market
spread‡
spread
482
488
<
690
Argentina
BB
438
B1
604
521
<
722
Bulgaria
B+
561
B2
632
596
<
804
B+
500
B2
555
527
<
735
Ivory coast
CCC
875
CCC
875
875
<
2023
Chile
A-
123
Baa1
158
141
<
213
China
BBB
169
A3
112
140
Colombia
BB
590
Ba2
435
512
Algeria
CCC
1633
CCC
1633
1633
Ecuador
B-
783
Caa2
1132
958
<
1303
Croatia
BBB-
349
Baa3
349
349
<
415
Hungary
BBB+
105
Baa1
105
105
Korea
BBB
140
Baa2
161
150
Lebanon
B+
667
B1
921
794
Morocco
BB
401
Ba1
317
359
<
519
Mexico
BB+
326
Baa3
293
309
<
360
<
230
Brazil *
*
138 <
746 749
119 <
264 267
BBB
165
Baa3
232
199
Nigeria
CCC
1218
CCC
1218
1218
<
1887
Panama
BB+
350
Baa1
177
263
<
471
Peru
BB
522
Ba3
474
498
<
674
Philippines
BB+
370
Ba1
370
370
<
657
Poland
BBB+
182
Baa1
182
182
<
269
CCC
1224
B3
770
997
<
1056
Thailand
BBB-
259
Baa3
259
259
Turkey
B+
517
B1
517
517
Malaysia *
Russia
**
161 <
624
Ukraine
CCC
1690
Caa1
1455
1572
Venezuela
B
650
B2
650
650
<
822
South Africa
BBB-
283
Baa3
251
267
<
364
† As of October, 2000 ‡ As of market close of Oct 12, 2000 * These sovereigns are neither rated by S&P nor by Moody's. We assign CCC ratings to them with stable outlook ** Russia is rated SD (selective default ) by S&P and B3 (with positive outlook) by Moody's. Since Russia has just "cured" its default on external debt, for the purpose of calculating rock-bottom spread, we adjust its S&P rating to CCC with stable outlook Source: S&P, Moody's, and J.P. Morgan analytics
1622
Exhibit 9
Most EMBI Global emerging market countries look attractive relative to their rock-bottom spread †
EMBI Global country market spread (bps) vs rock bottom spread (bps) 1400 Ecuador 1200
Cheap Russia 1000
Bulgaria 800
Colombia Brazil Peru
Philippines
Venezuela
Argentina Turkey
600
Expensive
Morocco
Panama
Croatia
400
South Africa Korea Chile
200
Mexico
Poland Malaysia
Lebanon
Thailand China Hungary 0 0
† As of close of Oct 12, 2000
200
400
600
800
1000
1200
1400
Exhibit 10
Default rates are correlated 20% B 15%
BB
10% 5% 0% 1980
1985
1990
1995
2000
Exhibit 11
Effect of 1% increase in speculative default rate Changes of transition matrix (%) AAA
AA
A
BBB
BB
B
CCC
D
AAA
-0.3
0.3
0.0
0.0
0.0
0.0
0.0
0.0
AA
-0.2
-0.5
0.6
0.0
0.0
0.0
0.0
0.0
A
0.0
0.0
-0.9
0.8
0.1
0.0
0.0
0.0
BBB
0.0
-0.1
-1.3
0.5
0.7
0.1
0.0
0.1
BB
0.0
0.0
-0.2
-1.5
0.0
1.2
0.1
0.3
B
0.0
0.0
0.0
-0.2
-1.7
-0.3
1.0
1.2
CCC
0.0
0.0
-0.2
-0.2
-0.7
-1.4
-1.0
3.5
Exhibit 12
Change in credit migration probabilities accompanying a one percent increase in speculative grade default (%) 4 CCC
3
2 B
1 BB
0
-1
-2
5 +
4 +
3 +
2 +
Upgrades (number of notches)
1 +
e g n a h c o N
1 -
2 -
3 -
4 -
5 -
Downgrades (number of notches)
Exhibit 13
Historical market and rock-bottom spread levels Market May
Rock-Bottom Spreads
Oct Historical
1999 2000
†
290
B
475 733.4
CCC MLHY
1236 1894 465
Default Default Credit Fundamentals Scenario Scenario
467
BB
708
† As of close of Oct 12, 2000
2000-01 2000-02
231
296
336
572
752
852
1389 491
1909 648
2099 730
Exhibit 14
The BB sector has responded most sharply to rising defaults Market spreads (bps) versus rock-bottom spreads (bps) 800 700
B
600 500
BB
400 300 200
Oct 2000
100
May 1999
0 0
200
400
600
800
Exhibit 15
Anatomy of rock-bottom spread differences EMBI Global with current rating outlooks 488bp …with stable rating outlooks 514bp
+26bp
…and with HY credit composition 671bp
+157bp
…and with historical HY recovery rate 473bp
-198bp
…and with historical HY credit migration 691bp
+218bp
…and with HY diversity 491bp
-200bp
…and with current HY recovery rate view 551bp
+60bp
…and with current HY credit migration view 648bp
+97bp
HY with current default view 648bp
Exhibit A1
Sovereign transition matrix under Positive, Stable, and Negative outlook Positive AAA
AA
A
BBB
BB
B
CCC
Default
AAA
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
AA
0.00
0.99
0.01
0.00
0.00
0.00
0.00
0.00
A
0.00
0.07
0.91
0.02
0.00
0.00
0.00
0.00
BBB
0.00
0.00
0.11
0.87
0.01
0.00
0.00
0.00
BB
0.00
0.00
0.00
0.12
0.87
0.00
0.00
0.01
B
0.00
0.00
0.00
0.00
0.34
0.62
0.02
0.01
CCC
0.00
0.00
0.00
0.00
0.00
0.10
0.77
0.13
AAA
AA
A
BBB
BB
B
CCC
Default
AAA
0.97
0.03
0.00
0.00
0.00
0.00
0.00
0.00
AA
0.01
0.96
0.02
0.00
0.01
0.01
0.00
0.00
A
0.00
0.05
0.91
0.04
0.00
0.00
0.00
0.00
BBB
0.00
0.00
0.05
0.86
0.07
0.02
0.00
0.00
BB
0.00
0.00
0.00
0.06
0.84
0.06
0.01
0.02
B
0.00
0.00
0.00
0.00
0.17
0.75
0.02
0.05
CCC
0.00
0.00
0.00
0.00
0.00
0.10
0.77
0.13
AAA
AA
A
BBB
BB
B
CCC
Default
AAA
0.71
0.29
0.00
0.00
0.00
0.00
0.00
0.00
AA
0.00
0.99
0.01
0.00
0.00
0.00
0.00
0.00
A
0.00
0.01
0.84
0.15
0.00
0.00
0.00
0.00
BBB
0.00
0.00
0.01
0.85
0.01
0.13
0.00
0.00
BB
0.00
0.00
0.00
0.04
0.67
0.17
0.06
0.06
B
0.00
0.00
0.00
0.00
0.17
0.70
0.02
0.10
CCC
0.00
0.00
0.00
0.00
0.00
0.10
0.77
0.13
Stable (or Historical)
Negative
Explanation of these sovereign transition matrices: In order to take rating outlook into account, we examined the history of S&P one-year ratings migration for countries with positive outlooks, negative outlooks, and irrespective of outlook (unconditional), respectively.
In our earlier research, we estimated a historical sovereign transition matrix using both loan defaults and extended sovereign rating history based on J.P.Morgan internal ratings. This historical estimate thus has a different basis than the raw numbers conditioned on outlo ok, which only draw on S&P ratings. In order to account for these differences, we obtain the positive (negative) outlook transition matrix in this exhibit by adding to t his historical transition matrix the difference between the positive (negative) outlook matrix and the unconditional transition matrix. The stable transition matrix in this exhibit is simply the historical transition matrix.
Exhibit A2
Hisorical US corporate transition matrix AAA
AA
A
BBB
BB
B
CCC
Default
AAA
0.89
0.10
0.01
0.00
0.00
0.00
0.00
0.00
AA
0.01
0.89
0.10
0.00
0.00
0.00
0.00
0.00
A
0.00
0.03
0.90
0.06
0.01
0.00
0.00
0.00
BBB
0.00
0.00
0.07
0.85
0.06
0.01
0.00
0.00
BB
0.00
0.00
0.01
0.06
0.84
0.08
0.00
0.01
B
0.00
0.00
0.00
0.01
0.07
0.83
0.03
0.07
CCC
0.00
0.00
0.01
0.01
0.03
0.06
0.63
0.26
Exhibit A3
US Corporate Transition Matrix correpsonding to a 7.5% speculative default rate AAA
AA
A
BBB
BB
B
CCC
Default
AAA
0.89
0.10
0.01
0.00
0.00
0.00
0.00
0.00
AA
0.00
0.87
0.12
0.00
0.00
0.00
0.00
0.00
A
0.00
0.03
0.88
0.08
0.01
0.00
0.00
0.00
BBB
0.00
0.00
0.03
0.87
0.08
0.01
0.00
0.00
BB
0.00
0.00
0.00
0.01
0.84
0.12
0.01
0.03
B
0.00
0.00
0.00
0.00
0.01
0.81
0.06
0.11
CCC
0.00
0.00
-0.01
0.00
0.01
0.01
0.58
0.40
140 120 100
Baa
80 60
A
40 20
Aa
0 8 8 8 8 9 9 9 9 l t n r a p u c J A J O
9 9 9 9 0 0 0 9 9 9 9 0 0 0 l t n r n r l a p u c a p u J A J O J A J
0 0 t c O
1 1 0 0 n r a p J A
100
US
50 0 -50 -100 Japan
-150 -200 -250 Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Issuer
Ratings
Years
Treasury Similar issuer in Japan spread
Ratings
Years
JGB spread
Bank of America Corp
Aa2/A+
3.9
83
Shizuoka Bank
Aa2/AA-
3.9
16
CITIGROUP Inc
Aa2/AA-
4.5
90
Shizuoka Bank
Aa2/AA-
4.3
17
Wal-Mart Stores
Aa2/AA
3.2
57
Ito-Yokado
Aa3/AA+
3.0
11
Bank One Corp
Aa3/A
4.1
100
Shoko Chukin
Aa3/A
4.1
12
Chase Manhattan Corp
Aa3/AA-
3.5
93
Shoko Chukin
Aa3/A
3.5
11
Sony Corporation
Aa3/A+
1.7
70
Sony Corp.
Aa3/A+
2.0
8
Dow Chemical
A1/A
4.8
100
Asahi Kasei
A2/A-
5.0
15
Goldman Sachs Group
A1/A+
4.2
102
Nomura Securities
Baa1/BBB+
4.0
26
Statoil
A1/AA-
4.9
115
Nippon Mitsubishi Oil
A3/BB+
5.0
21
American Airlines Inc
A2/A
3.3
165
Japan Airlines
Baa3/BB
3.0
47
GMAC
A2/A
4.6
135
Fuji Heavy Ind.
A- (R&I)
5.0
33
DaimlerChrysler NA Hldg
A3/A-
4.6
153
Fuji Heavy Ind.
A- (R&I)
5.0
33
Worldcom Inc.
A3/BBB+
1.9
160
Nippon Telecom
AA (JCR)
2.0
8
Sun Microsystems Inc*
Baa1/BBB+
3.2
165
NEC Corporation
Baa1/ -
3.0
15
FedEx Corp
Baa2/BBB
2.7
132
Yamato Transport
A3/A-
3.0
15
FedEx Corp
Baa2/BBB
4.7
152
Yamato Transport
A3/A-
5.0
10
Kellogg Co
Baa2/BBB
1.8
107
Suntory
Baa3/ -
2.0
18
Kellogg Co
Baa2/BBB
4.8
127
Suntory
Baa3/ -
5.0
24
Delta Air Lines
Baa3/BBB-
4.5
295
ANA
Baa3/BB-
5.0
66
Lockheed Martin Corp
Baa3/BBB-
4.9
135
IHI
Baa2/BBB-
5.0
24
Raytheon Co
Baa3/BBB-
3.8
185
Kawasaki Heavy Ind.
Baa2/BB+
4.0
31
Issuer
Ratings
Maturity
Years
¥LIBOR Similar issuer in Japan spread (a)
Ratings
Years
¥LIBOR spread (b)
¥LIBOR spread diff. (a)-(b)
Bank of America Corp
Aa2/A+
5/16/05
3.9
22
Shizuoka Bank
Aa2/AA-
3.9
12
10
CITIGROUP Inc
Aa2/AA-
12/1/05
4.5
15
Shizuoka Bank
Aa2/AA-
4.3
13
2
Wal-Mart Stores
Aa2/AA
8/10/04
3.1
18
Ito-Yokado
Aa3/AA+
3.0
4
14
Bank One Corp
Aa3/A
8/1/05
4.1
32
Shoko Chukin
Aa3/A
4.1
10
22
Chase Manhattan Corp
Aa3/AA-
Sony Corporation
Aa3/A+
12/1/04
3.5
42
Shoko Chukin
Aa3/A
3.5
7
35
3/4/03
1.7
18
Sony Corp.
Aa3/A+
2.0
0
18
Dow Chemical
A1/A
4/1/06
4.8
Goldman Sachs Group
A1/A+
8/17/05
4.2
20
Asahi Kasei
A2/A-
5.0
12
8
33
Nomura Securities
Baa1/BBB+
4.0
23
10
STATOIL
A1/AA-
5/1/06
4.9
29
Nippon Mitsubishi Oil
A3/BB+
5.0
18
11
American Airlines Inc
A2/A
10/15/04
3.3
110
Japan Airlines
Baa3/BB
3.0
40
70
GMAC
A2/A
1/15/06
4.6
53
Fuji Heavy Ind.
A- (R&I)
5.0
30
23
DaimlerChrysler NA Hldg
A3/A-
1/18/06
4.6
68
Fuji Heavy Ind.
A- (R&I)
5.0
30
38
Worldcom Inc.
A3/BBB+
5/15/03
1.9
95
Nippon Telecom
AA (JCR)
2.0
0
95
Sun Microsystems Inc*
Baa1/BBB+
8/15/04
3.2
117
NEC Corporation
Baa1/ -
3.0
8
109
FedEx Corp
Baa2/BBB
2/12/04
2.7
35
Yamato Transport
A3/A-
3.0
8
27
FedEx Corp
Baa2/BBB
2/15/06
4.7
65
Yamato Transport
A3/A-
5.0
7
58
Kellogg Co
Baa2/BBB
4/1/03
1.8
50
Suntory
Baa3/ -
2.0
10
40
Kellogg Co
Baa2/BBB
4/1/06
4.8
39
Suntory
Baa3/ -
5.0
21
18
Delta Air Lines
Baa3/BBB-
12/15/05
4.5
192
ANA
Baa3/BB-
5.0
63
129
Lockheed Martin Corp
Baa3/BBB-
5/15/06
4.9
47
IHI
Baa2/BBB-
5.0
21
26
Raytheon Co
Baa3/BBB-
3/15/05
3.7
114
Kawasaki Heavy Ind.
Baa2/BB+
4.0
28
86
250 Market spreads
200
Rock-bottom spread (34% recovery) Rock-bottom spread (45% recovery)
150 100 50 0 Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
300 Market spread
250
Rock-bottom spread (15% recovery) 200
Rock-bottom spread (45% recovery)
150 100 50 0 Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
100
US
50 0 -50 -100 Japan
-150 -200 -250 Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Issuer
Ratings
Years
¥LIBOR
Rock-
¥LIBOR
Rock-
spread
bottom
Surplus above Similar issuer in Japan RBS
Ratings
Years
spread
bottom
RBS
(a)
spread
(a)-(b)
(a)
spread
(a)-(b)
(b) Bank of America Corp CITIGROUP Inc Wal-Mart Stores Bank One Corp Chase Manhattan Corp Sony Corporation Dow Chemical Goldman Sachs Group STATOIL American Airlines Inc GMAC DaimlerChrysler NA Hldg Worldcom Inc. Sun Microsystems Inc* FedEx Corp FedEx Corp Kellogg Co Kellogg Co Delta Air Lines Lockheed Martin Corp Raytheon Co
Aa2/A+ Aa2/AAAa2/AA Aa3/A Aa3/AAAa3/A+ A1/A A1/A+ A1/AAA2/A A2/A A3/AA3/BBB+ Baa1/BBB+ Baa2/BBB Baa2/BBB Baa2/BBB Baa2/BBB Baa3/BBBBaa3/BBBBaa3/BBB-
3.9 4.5 3.2 4.1 3.5 1.7 4.8 4.2 4.9 3.3 4.6 4.6 1.9 3.2 2.7 4.7 1.8 4.8 4.5 4.9 3.8
22 15 18 32 42 18 20 33 29 110 53 68 95 117 35 65 50 39 192 47 114
1 3 1 4 4 2 6 4 7 5 9 19 14 109 46 57 45 57 120 120 116
Surplus above
(b) 21 12 17 28 38 16 14 29 22 105 44 49 81 8 -11 8 5 -18 72 -73 -2
Shizuoka Bank Shizuoka Bank Ito-Yokado Shoko Chukin Shoko Chukin Sony Corp. Asahi Kasei Nomura Securities Nippon Mitsubishi Oil Japan Airlines Fuji Heavy Ind. Fuji Heavy Ind. Nippon Telecom NEC Corporation Yamato Transport Yamato Transport Suntory Suntory ANA IHI Kawasaki Heavy Ind.
Aa2/AAAa2/AAAa3/AA+ Aa3/A Aa3/A Aa3/A+ A2/ABaa1/BBB+ A3/BB+ Baa3/BB A- (R&I) A- (R&I) AA (JCR) Baa1/ A3/AA3/ABaa3/ Baa3/ Baa3/BBBaa2/BBBBaa2/BB+
3.9 4.3 3.0 4.1 3.5 2.0 5.0 4.0 5.0 3.0 5.0 5.0 2.0 3.0 3.0 5.0 2.0 5.0 5.0 5.0 4.0
12 13 4 10 7 0 12 23 18 40 30 30 0 8 8 7 10 21 63 21 28
6 6 6 7 7 5 16 43 27 145 149 149 8 39 19 27 140 149 149 75 67
6 7 -2 3 0 -5 -4 -20 -9 -105 -119 -119 -8 -31 -11 -20 -130 -128 -86 -54 -39
Diversity score
Rock-bottom spread
60
59
50
61
40
63
30
66
20
72
10
84
5
102
1
176
Ratings
Issuer
Industry sector
Coupon
Maturity
Years
Features
Trsry spread
$LIBOR spread
¥LIBOR
Rock-
spread
bottom spread
Aa2/A+ Aa2/A+ Aa2/AA Aa2/AAAa2/AAAa2/AA Aa2/AA Aa2/AA Aa3/A Aa3/A Aa3/A Aa3/AAAa3/AAAa3/A+ A1/A A1/A+ A1/A+ A1/AAA1/A+ A1/A+ A2/A A2/A A2/AAA2/A A2/A A2/A A2/A A2/A A2/A A3/A A3/AA3/AA3/AA3/AA3/AA3/AA3/BBB+ Baa1/BBB+ Baa1/BBB+ Baa2/BBB Baa2/BBB Baa2/BBB Baa2/BBB Baa2/BBB Baa3/BBBBaa3/BBBBaa3/BBBBaa3/BBBBaa3/BBBBaa3/BBB-
Bank of America Corp Bank of America Corp Chevron Corp CITIGROUP Inc CITIGROUP Inc Procter & Gamble Co Wal-Mart Stores Wal-Mart Stores Bank One Corp Bank One Corp Bank One Corp Chase Manhattan Corp JPMorgan Chase & Co Sony Corporation Dow Chemical Goldman Sachs Group IBM Corp Statoil Unilever Capital Corp Unilever Capital Corp American Airlines Inc AT&T Corp Boeing Capital Corp GMAC GMAC GMAC Walt Disney Company Walt Disney Company Walt Disney Company American Home Products BHP Finance USA Ltd DaimlerChrysler NA Hldg DaimlerChrysler NA Hldg DaimlerChrysler NA Hldg DaimlerChrysler NA Hldg Hertz Corp Worldcom Inc. Sun Microsystems Inc Time Warner Inc CSX Corp FedEx Corp FedEx Corp Kellogg Co Kellogg Co Bausch & Lomb Inc Delta Air Lines Delta Air Lines Lockheed Martin Corp Raytheon Co Raytheon Co
Banks Banks Oil&Gas Financial Financial Household Retail Retail Banks Banks Banks Banks Financial Home Furnishings Chemicals Financial Computers Oil&Gas Household Household Airlines Telecom Financial Financial Financial Financial Media Media Media Pharmaceuticals Mining Auto Manufacturers Auto Manufacturers Auto Manufacturers Auto Manufacturers Commercial Services Telecommunications Computers Media Transportation Transportation Transportation Food Food Healthcare-Products Airlines Airlines Aerospace/Defense Aerospace/Defense Aerospace/Defense
6.625 7.875 6.625 5.7 6.75 6.6 6.55 5.875 5.625 7.625 6.5 6.75 5.75 6.125 8.625 7.625 5.625 6.875 6.75 6.875 7.155 5.625 7.1 5.875 7.5 6.75 5.125 7.3 6.75 5.875 6.69 7.75 6.9 7.75 7.25 8.25 7.875 7.35 7.75 7.25 6.625 6.875 5.5 6 6.75 6.65 7.7 7.25 7.9 6.3
6/15/04 5/16/05 10/1/04 2/6/04 12/1/05 12/15/04 8/10/04 10/15/05 2/17/04 8/1/05 2/1/06 12/1/04 2/25/04 3/4/03 4/1/06 8/17/05 4/12/04 5/1/06 11/1/03 11/1/05 10/15/04 3/15/04 9/27/05 1/22/03 7/15/05 1/15/06 12/15/03 2/8/05 3/30/06 3/15/04 3/1/06 5/27/03 9/1/04 6/15/05 1/18/06 6/1/05 5/15/03 8/15/04 6/15/05 5/1/04 2/12/04 2/15/06 4/1/03 4/1/06 12/15/04 3/15/04 12/15/05 5/15/06 3/1/03 3/15/05
3.0 3.9 3.3 2.6 4.5 3.5 3.1 4.3 2.7 4.1 4.6 3.5 2.7 1.7 4.8 4.2 2.8 4.9 2.4 4.4 3.3 2.7 4.3 1.6 4.1 4.6 2.5 3.6 4.8 2.7 4.7 1.9 3.2 4.0 4.6 4.0 1.9 3.2 4.0 2.9 2.7 4.7 1.8 4.8 3.5 2.7 4.5 4.9 1.7 3.7
NC NC MW NC NC NC NC NC NC NC NC NC NC NC NC NC NC NC 1 NC NC NC MW NC NC NC NC NC NC NC NC 1 NC NC NC NC NC NC NC MW NC NC NC 1 NC 1 NC 1 NC 1 MW NC NC NC NC 1 NC
83 83 60 78 90 50 57 67 92 100 108 93 78 70 100 102 68 115 63 85 165 117 83 93 118 135 67 77 95 107 150 117 110 133 153 138 160 165 113 125 132 152 107 127 335 285 295 135 190 185
-23 32 24 -14 26 9 25 4 -1 44 39 53 -16 22 32 45 -31 42 -17 22 127 20 22 50 62 67 -17 32 -56 11 79 58 76 79 85 86 102 132 59 24 39 82 54 54 278 184 223 62 143 132
-27 22 16 -18 15 0 18 -4 -6 32 27 42 -20 18 20 33 -34 29 -20 12 110 17 14 49 49 53 -18 21 -57 8 61 56 64 67 68 72 95 117 47 17 35 65 50 39 249 167 192 47 135 114
1 1 56 1 3 2 1 2 2 4 5 4 2 2 6 4 3 7 3 5 5 5 7 5 7 9 6 7 9 13 19 14 13 15 19 15 14 109 32 46 46 57 45 57 137 115 120 120 124 116
JPMorgan
1.2 billion
Investor $10 million
$10 million 1.2 billion
$10 million
5-year Baa3 corporate bond Coupon 7.25% $10 million
$10 million Cash flow at value date Cash flow at maturity
T+120bp Investor
JPMorgan $L+45bp*
$L+45bp*
T+120bp
5-year Baa3 corporate bond Coupon 7.25% $10 million
L+30bp
¥1.2 billion
Repackaged bond issued by an SPC
Investor
5-year Baa3 corporate bond Coupon 7.25% $10 million
¥1.2 billion
Cash flow at value date $10 million
Cash flow at maturity
¥1.2 billion
$10 million ¥1.2 billion
JPMorgan Repackaged bond issued by an SPC Investor
5-year Baa3 corporate bond Coupon 7.25% $10 million
¥L+30bp - SPC cost
$L+45bp ¥ L+30bp
T+120bp
$L+45bp
JPMorgan
