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Extract from a report
Counselling Piotroski+: Introducing our new fundamental quality score
We suggest an alternative measure of fundamental quality, building on Joseph Piotroski’s
F-Score framework. Having used the Piotroski model for many years, we believe it offers a very solid framework to assess the strength of a company’s fundamentals. Therefore, we seek to
maintain the principles of the original model whilst tweaking some of the underlying criteria aiming for a better assessment of a company’s fundamental fundamental quality.
try to extract more from our factors by averaging the factor scores instead of performing the binary tests in the original Piotroski model. As ever the main concern when re-designing a model is data mining. With that in mind we rely on factors that have been around for many years now and which have been documented by academics and practitioners.
Our ex-Financials fundamental quality score includes eight factors: 1) gross profitability on
assets; 2) five-year risk-adjusted trend in gross profitability on assets; 3) free cash flow on (852) 2166 4141 [email protected]
invested capital; 4) five-year risk-adjusted trend in free cash flow on invested capital; 5) total accruals; 6) net operating asset accruals; 7) change in asset turnover; and 8) external financing on assets.
We also suggest a set of factors that can be applied for financial stocks. Many models that
seek to quantify the quality of company fundamentals, including the Piotroski model, often fail to capture financials. Our financials fundamental quality model might not perform as well as the exfinancials model but we still find it to add some value. For financials we use just four factors: 1) return on equity, 2) five-year risk-adjusted trend in return on equity, 3) asset growth; and 4) external financing on assets.
We have backtested our quality score over the past 20 years across MSCI World stocks and
in the main investment regions. We find that our score adds value on top of the Piotroski model as well as our profitability factor portfolio both globally and in all the main regions. Long-Universe performance of our fundamental quality score (MSCI World) 180 170 160 150 140 130 120 110 100 90 80
8 9 c e D
9 9 c e D
0 0 c e D
1 0 c e D
2 0 c e D
Financ ials
3 0 c e D
4 0 c e D
5 0 c e D
6 0 c e D
7 0 c e D
8 0 c e D
9 0 c e D
Ex financials
0 1 c e D
1 1 c e D
2 1 c e D
3 1 c e D
4 1 c e D
5 1 c e D
6 1 c e D
7 1 c e D
Combined
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI.
Societe Generale (“SG”) does and seeks to do business with companies covered in its research reports. As a result, investors investors should be aware aware that SG may have a conflict of interest tha t could affect the objectivity of this report. Investors should consider this report as only a single factor in This document, on 13-Aug-2018 2:37 PMOF CET, is being provided for ANALYST(S) the exclusiveCERTIFICATION(S), use of PLEASE SEE APPENDIX ATatTHE END THIS REPORT FOR THE making their investment decision. published
Global Style Counselling
Piotroski’s F-Score Our team has used the Piotroski model extensively for many years, whether to avoid value traps, identify shorting candidates, or generally provide a more robust definition of the Quality factor. The Piotroski F-score is also one of the factors that forms the backbone of our Quality Income index. Our experience using the model has been very positive and we have found it to be one of the most consistent models in our toolkit. This experience is also shared by a number of our clients who have deployed the model in their investment strategies. The two charts below show the performance of the model since the original Piotroski note. Since then the Piotroski score has worked well out-of-sample. Absolute performance performance by Piotroski Piotroski score (MSCI (MSCI World, 2001-2018) 600 High Score (7+) 500 Mid Score (5-6)
400 Low Score (4-) 300 200 100 0
0 0 c e D
1 0 c e D
2 0 c e D
3 0 c e D
4 0 c e D
5 0 c e D
6 0 c e D
7 0 c e D
8 0 c e D
9 0 c e D
0 1 c e D
1 1 c e D
2 1 c e D
3 1 c e D
4 1 c e D
5 1 c e D
6 1 c e D
7 1 c e D
6 1 c e D
7 1 c e D
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
Relative performance by Piotroski score (MSCI World, 2001-2018) 260 High vs Low
240 220
High vs Universe
200 180 160 140 120 100 80
0 0 c e D
1 0 c e D
2 0 c e D
3 0 c e D
4 0 c e D
5 0 c e D
6 0 c e D
7 0 c e D
8 0 c e D
9 0 c e D
0 1 c e D
1 1 c e D
2 1 c e D
3 1 c e D
4 1 c e D
5 1 c e D
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
13 August 2018
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Piotroski’s methodology methodology We have covered Joseph Piotroski’s F-Score F -Score methodology in detail in two previous publications1. Essentially, the model assesses a company’s quality based on a set of financial health checks. One of the main virtues of the model is its simplicity and common sense approach as it comprises a set of just nine straightforward binary tests. What is more, the underlying factors were not selected on a backtested performance, but rather on what prior research identified as the important elements of a company’s financial quality. A more complete methodology methodology is available in the above notes and in the original Piotroski paper2, but as a quick ref resher we show below the nine criteria included in the F-Score. i)
ROA positive
ii)
CFO positive Profitability factors
iii) iv)
ROA positive
Accruals negative negative
v)
Leverage negative
vi)
Liquid positive
vii)
Finance negative
viii)
Margin positive
Leverage, liquidity and source of funds
Operating efficiency ix)
Turnover positive
Why change a winning model? We believe the Piotroski model offers a very solid framework to assess the strength of a company’s fundamentals. Therefore, while while we tweak some of the underlying criteria aiming for a better assessment of a company’s financial quality, we maintain the principles of the original model. Our model shifts the focus towards more cash-flow reliant factors and generally factors that have had more consistent performance historically. Similarly to the Piotroski score our model looks at the following four areas of company fundamentals: fundamentals: Profitability
In previous research we have highlighted3 that top-line based definitions of profitability have been more reliable compared to bottom-line definitions like return on assets. This is particularly true for a US universe. With that in mind, we suggest replacing return-on-assets with gross profitability on assets (GPOA).
1
“Piotroski’s F-scoreF -score-Helps Helps to pick the winners while identifying potential losers”, Global Quant Strategy (2008) and “Time for a quality check – dusting off Piotroski’s F -score”, Global Style C ounselling (2010)
2
Piotroski, J. 2000. Value investing: The use of historical financial statement information to separate winners from losers.
3
“Can profitability be profitable? We take a look at the profitability factor”, Global Style Counselling (2016 )
13 August 2018
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We also use FCFROIC (free cash flow on invested capital) instead of CFO (cash flow on assets) as we prefer to assess a company’s cash generation post CAPEX requirements. What is more, FCFROIC individually has been one of the strongest profitability factors. Long-Short performance of Profitability factors (MSCI World) 300
Return on assets Gross profitability on assets assets
250
Free cash flow on invested capital 200 150 100 50
8 9 c e D
9 9 c e D
0 0 c e D
1 0 c e D
2 0 c e D
3 0 c e D
4 0 c e D
5 0 c e D
6 0 c e D
7 0 c e D
8 0 c e D
9 0 c e D
0 1 c e D
1 1 c e D
2 1 c e D
3 1 c e D
4 1 c e D
5 1 c e D
6 1 c e D
7 1 c e D
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
Operating efficiency and trends in company fundamentals
In line with our definitions of profitability, we include two measures that capture the five year trends in a company’s gross profits on assets and free cash flow on invested capital. We calculate the trend on a risk-adjusted basis, which emphasizes more the quality rather than the magnitude of growth. As in the Piotroski model we also evaluate the change in asset turnover, so the degree to which sales are growing faster than assets. Long-Short performance of operating efficiency and growth factors (MSCI World) 220
5-year gross profitability on assets trend (t-s (t-stat) tat)
200
5-year free cash flow on invested capital trend (t-stat)
180
Change in asset turnover
160 140 120 100 80
8 9 c e D
9 9 c e D
0 0 c e D
1 0 c e D
2 0 c e D
3 0 c e D
4 0 c e D
5 0 c e D
6 0 c e D
7 0 c e D
8 0 c e D
9 0 c e D
0 1 c e D
1 1 c e D
2 1 c e D
3 1 c e D
4 1 c e D
5 1 c e D
6 1 c e D
7 1 c e D
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
Accruals/Earnings Quality
It is obviously key to avoid companies whose growth is driven by accounting practices rather than actual sales. The Piotroski model includes an accruals factor - based on the standard comparison between operating cash flow and net income - which we also use in our model. Moreover, we incorporate a second accruals factor defined as the growth in net operating assets (NOA). The latter extends the standard accruals definition to include non-current
13 August 2018
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accruals4. Interestingly, NOA accruals individually have performed much better than standard accruals in recent years as a factor. Long-Short performance of Accruals factors (MSCI World) 330 330 Total Total accruals 280 280 Net operating asset accruals 230 230 180 180 130 130 80
8 9 c e D
9 9 c e D
0 0 c e D
1 0 c e D
2 0 c e D
3 0 c e D
4 0 c e D
5 0 c e D
6 0 c e D
7 0 c e D
8 0 c e D
9 0 c e D
0 1 c e D
1 1 c e D
2 1 c e D
3 1 c e D
4 1 c e D
5 1 c e D
6 1 c e D
7 1 c e D
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
Financing
Instead of assessing a company’s debt and stock issuance separately, we opted to include one factor that combines both external financing demands. This is defined as the sum of the net debt and net equity issuance scaled by the stock’s total assets. Long-Short performance of external financing (MSCI World) 240 240 220 220 Externa Ext ernall financing on ass ets
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
4
See Richardson S., R. Sloan, M. Soliman and I. Tuna. 2001. Information in Accruals about the Quality of Earnings. Available at SSRN: https://ssrn.com/abstract=278308
13 August 2018
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Our fundamental quality score Our quality score now includes the following eight factors: 1.
GPOA: Gross profitability on assets (+)
2.
GPTSTAT: 5-year risk-adjusted trend in gross profitability on assets (+)
3.
FCFROIC: Free cash flow on invested capital (+)
4.
FCFTSTAT: FCFTSTAT: 5-year risk-adjusted trend in f ree cash flow on invested capital (+)
5.
TOTAL ACCRUALS: Net income minus operating cash flow on assets (-)
6.
NOA ACCRUALS: Change in net operating assets on assets (-)
7.
TUROVER: Change in asset turnover (+)
8.
EXTFIN: External financing on assets (-)
Whilst we like the simplicity of the 9-binary tests of the Piotroski model, we think that adding more granularity to our model can be beneficial. This may also make it easier to incorporate our quality score into multi-factor models. Hence, i nstead of using binary factors we choose to average the scores of the underlying factors. To do so, we first standardize all eight metrics on a z-score basis and then average all z-scores. As we are dealing with financial accounting data, we perform the standardization within the relevant industry peer group.
Backtesting the model We backtested our quality score across MSCI World ex-financial stocks and in the main investment regions (US, Europe, Asia Pacific ex Japan and Japan). In each case we formed long and short portfolios that included the top and bottom quintiles of stocks on our scoring. All portfolios were rebalanced at the end of each month throughout our backtesting period (1998-2018). The chart below shows the overall risk-adjusted returns for our quality score as well as the eight underlying factors. As we saw in the previous section, all eight factors have added value historically. The combined model adds more value than any of the factors individually. Return/Risk(IRs) Return/Risk(IRs) of individual factors vs combined score (MSCI World ex financials, Long-Short) 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
13 August 2018
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We further evaluate the performance of our fundamental score comparing it against the Piotroski model. As our model incorporates profitability elements, we also include in the comparison our ‘Profitability factor’ factor’ portfolio, which we define based on sector relative ROA, ROE, ROIC and GPOA. The two charts below compare the performance on a long vs universe and long vs short basis. In both cases, our quality combo comfortably outperforms outperforms the original Piotroski model as well as our Profitability portfolio. Long-Universe performance (MSCI World ex financials)
Long-Short performance (MSCI World ex financials)
180
330
170 160
280
150 140
230
130 120
180
110 130
100 90
80
80
SG Fund undamen amenttalQuali ualitty
Piio ottrosk oski
SG Funda undame ment nta al Qualit ality y
Profit ofita abili bilitty
Piio ottroski ski
Profit ofitab abil ilit ity y
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
The table below summarizes the performance of the above strategies over the past 20 years. Compared to the universe, our fundamental quality score produced more than twice the outperformance of either the Piotroski model or our profitability factor. What is more, it has achieved those returns whilst maintaining a much lower tracking error versus the universe. Therefore, risk-adjusted returns are considerably higher. Drawdown risk wa also significantly less both on a long-short and long-universe basis.
Annualized return and risk statistics statistics (MSCI World ex financials, financials, 1998-2018)
Return
11.80
10.37
9.70
8.60
2.87
1.39
0.89
5.87
4.28
1.85
Volatility
13.97
13.06
13.99
14.46
2.27
3.37
3.50
4.79
9.81
8.02
Return/Vol
0.84
0.79
0.69
0.59
1.26
0.41
0.25
1.23
0.44
0.23
Max drawdown
48.30
48.77
48.24
50.91
4.21
9.36
11.94
7.06
22.97
27.39
Beta
0.95
0.88
0.94
1.00
-0.05
-0.12
-0.06
-0.16
-0.38
-0.24
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
13 August 2018
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Performance in individual regions The outperformance of our score is evident in the main investment regions as well. Below we plot the long versus universe returns for MSCI Europe, MSCI US, MSCI Asia Pac ex Japan and Japan indices. The model has managed a solid and consistent outperformance in all regions. Moreover, as was the case for MSCI World stocks it has outperformed the original Piotroski model and our profitability factor. Japan stands out as Piotroski and profitability have not added any value historically, but our quality combo managed a good performance. MSCI Europe ex financials (Long-Universe)
MSCI United States ex financials (Long-Universe)
260
160
240
150
220
140
200
130
180
120
160
110
140 120
100
100
90
80
80
SG Fund undamen amenttalQuali ualitty
Piio ottrosk oski
SG Funda undame ment nta al Qualit ality y
Profit ofita abili bilitty
MSCI Asia Pacific ex Japan ex financials (Long-Universe)
Piio ottroski ski
Profit ofitab abil ilit ity y
MSCI Japan ex financials (Long-Universe)
220
160 150
200
140
180
130
160
120 110
140
100
120
90 80
100
70
80
60
SG Fund undamen amenttalQuali ualitty
Piio ottrosk oski
Profit ofita abili bilitty
SG Funda undame ment nta al Qualit ality y
Piio ottroski ski
Profit ofitab abil ilit ity y
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
What about financials? As in the original Piotroski model, so far in our analysis we have excluded financial stocks from our universe. Many models that seek to quantify the quality of company fundamentals often do not include financials. No doubt, the more complicated capital structure of many financials makes it difficult to assess quality with a quant approach. Moreover, factors based on cash-flow and accruals cannot be clearly defined for financial firms, whilst even factors that are more straightforward to define seem to add less value for financials. In order to apply our model for financial stocks, we had to exclude some of the factors and adapt others to make them applicable. We still wanted to maintain the same principles though. So, after some head scratching we decided to include four factors: ROE for
13 August 2018
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profitability; the trend in company fundamentals based on ROE trend over the last five years; change in assets (as an alternative factor to change in asset turnover); and external financing. 1.
ROE: Return on equity (+)
2.
ROETSTAT: 5-year risk-adjusted risk-adjusted trend in return on equity (+)
3. ASSET GROWTH: GROWTH: Change in assets assets (-) 4.
EXTFIN: External financing on assets (-)
As before, we average the z-scores across all factors to calculate a combined score. The performance of our quality combo for financials is shown below. It is clear these results are less impressive than we saw for the ex-financial stocks. Still our quality model managed to add some value in financials as well. Compared to a simple profitability based model, the outperformance outperformance has been more consistent as well. Long-Universe performance (MSCI World Financials) 150 140 130
Long-Short performance (MSCI World Financials) 260
SG Fundamental Quality
240
Profitability
200
120
Profitability
180
110
160
100
140
90
120
80
100
70
80
60
SG Fundam Fundam ental Quality
220
8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 9 - 9 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 c c c c c c c c c c c c c c c c c c c c e e e e e e e e e e e e e e e e e e e e D D D D D D D D D D D D D D D D D D D D
60
8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 9 - 9 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 c c c c c c c c c c c c c c c c c c c c e e e e e e e e e e e e e e e e e e e e D D D D D D D D D D D D D D D D D D D D
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
As the charts below show, the lower performance performance of our quality score within Financials results results in only a small performance drag for the combined Financials and e x-Financials model. Long-Universe performance of our fundamental quality score (MSCI World) 180 170 160 150 140 130 120 110 100 90 80
Long-Short performance of our fundamental quality score (MSCI World) 330 280 230 180 130
8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 9 - 9 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 c c c c c c c c c c c c c c c c c c c c e e e e e e e e e e e e e e e e e e e e D D D D D D D D D D D D D D D D D D D D
Financials
Ex financials
80
Com bined
8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 9 - 9 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 c c c c c c c c c c c c c c c c c c c c e e e e e e e e e e e e e e e e e e e e D D D D D D D D D D D D D D D D D D D D
Financials
Ex financials
Com bined
This is a backtest. Past performance is no guide to future returns. Returns do not include execution costs. Source: SG Cross Asset Research/Equity Quant, FactSet, MSCI
13 August 2018
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Conclusion Piotroski’s F-Score F -Score continues to stand the test of time, having performed well since the original paper was published now almost 20 years ago. In this note, we discussed some potential changes to the model which we feel can help us gain better insights into a company’s fundamental quality. Our changes are twofold: 1) we shift the focus of the model towards more cash-flow reliant factors, and generally factors that have had more consistent performance historically; and 2) we try to extract more from our f actors by averaging the factor scores instead of performing the binary tests in the original Piotroski model. We also suggest a set of factors that can be applied for financial stocks. Clearly, whenever you change a model the concern is over fitting and data mining . It’s true that quants rarely produce bad backtests! But our main goal was to bring out those factors that we believe can add value in quality investing. Reassuringly, these factors that are similar to those in the Piotroski model have also been around for many years now, and they too are documented by academics and practitioners.
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Investment Style Performance Value stocks showed some signs of recovery in July, outperforming in most regions. Their performance was highest in Japan where our long-short Value portfolio was up 4.4% last month. US Value was also up strongly ending the month up 2.8%. Still Value is down c. -6% ytd in most developed regions. On the flipside, growth and momentum factors underperformed last month. Our Momentum portfolio was down -1.7% globally and as much as -3.2% in Japan, whilst growth was down 0.9% globally and -2.9% in Japan. Long-short style performance per region (Q1-Q5)
Greenblatt
2.7
-0.2
2.8
-0.5
3.1
-1.1
-2.9
-5.1
-6.4
-0.6
-2.0
FY1 PE
5.3
2.3
0.8
4.0
-0.3
2.8
-2.2
-6.0
-6.8
-5.7
-5.0
-4.6
2.7
Value
2.3
0.8
4.4
-0.8
2.8
-1.5
-5.9
-4.2
-8.5
-0.8
-3.9
0.0
R1m
1.9
2.3
1.6
1.0
3.3
1.5
3.1
2.2
0.1
-3.1
-2.9
7.6
PE
1.8
0.5
3.5
1.4
2.0
-2.1
-0.7
-6.6
7.8
-3.4
-0.2
6.4
ROE
1.5
0.1
-0.2
0.8
1.2
-1.5
5.2
2.0
0.2
5.1
8.9
7.7
IREV1m
1.3
0.9
0.0
1.1
3.9
0.6
1.1
-2.3
-1.9
-1.4
-0.7
5.9
Volatility
1.3
-1.0
-0.8
-0.2
2.7
-0.4
-4.9
-2.1
-3.3
-0.6
-8.0
-1.8
ROIC
1.2
0.3
-0.8
-1.5
1.1
-1.6
5.5
3.9
0.4
4.0
10.2
9.6
DY+BB
1.2
0.2
1.9
1.1
0.5
-1.0
-3.5
-2.4
-3.9
-6.7
-3.1
4.2
PB
1.1
1.7
3.7
-1.1
1.1
-1.0
-4.4
-1.4
-5.5
-2.3
-7.4
0.4
1.1
1.1
4.5
1.9
0.5
1.3
-6.5
-8.0
-4.5
-9.2
-5.2
9.0
EVEBITDA
1.0
-0.5
2.8
-0.4
1.7
1.4
-6.0
-7.0
-14.2
-0.5
-4.1
1.3
Yield
ROA
1.0
-0.2
-0.9
-1.1
1.6
-1.3
4.9
3.5
4.5
11.3
6.4
DY+BB+DEBT
0.8
0.2
0.4
0.6
1.1
2.2
3.4
9.3
-1.6
-1.1
-1.2
10.9
PFCF
0.7
-0.9
0.1
-0.5
0.9
0.9
0.7
-0.8
-4.0
-1.5
1.7
10.4
Profitability
0.6
0.0
-1.3
-1.0
1.4
-1.1
6.4
5.9
2.0
5.5
11.5
10.4
BB
0.6
-2.0
-0.8
0.2
1.7
-1.1
2.4
2.7
-3.9
6.5
-0.3
10.4
Graham & Rea
0.3
-0.2
1.3
2.6
-0.1
-1.4
-6.0
-3.6
-10.0
4.4
-6.8
1.4
Merton
0.2
-0.7
-4.0
-0.5
2.2
-1.3
3.3
2.8
2.5
8.4
0.1
1.5
Value+Momentum
0.1
0.0
1.1
-0.4
0.5
-2.9
-3.8
-6.9
-7.9
0.9
-4.8
7.8
Earnings Quality
0.1
0.1
0.5
0.7
-0.6
0.7
-0.5
0.0
-4.4
-4.3
1.7
4.8
FY1 Growth
0.0
0.6
-1.0
1.0
-1.1
1.1
5.7
8.2
-3.6
8.5
10.7
9.0
Piotroski
-0.1
-1.1
1.3
-1.5
0.4
-2.3
3.6
5.1
-7.2
19.3
5.6
16.1
GPOA
-0.1
1.4
-2.4
0.8
1.2
-0.3
7.8
-1.2
5.3
0.8
15.0
7.3
EPS3Yr Growth
-0.4
-1.6
-1.0
-1.7
0.3
-1.6
-0.2
3.5
5.3
2.9
-5.6
7.2
Quality
-0.4
-0.1
-3.8
2.0
0.1
-1.8
1.0
4.7
3.2
3.4
-4.0
2.4
FY2 Growth
-0.5
1.2
-2.5
-0.3
0.0
-1.1
5.1
-2.2
9.6
-5.5
3.7
-7.9
5.9
8.2
2.9
6.8
0.2
3.6
-5.8
-6.1
-6.4
5.0
Growth
-0.9
-0.9
-2.9
-0.4
-0.3
-1.3
SAL3Yr Growth
-1.3
-2.8
-1.5
-1.9
-1.1
-1.9
-1.1
Beta
-1.7
0.6
-3.9
3.0
-1.1
-2.5
-1.5
1.3
4.5
-4.0
-3.5
1.9
EPS MOM
-1.7
-1.1
-1.5
-0.5
-1.6
1.5
4.9
6.7
0.0
4.4
8.2
7.0
IMOM12m-1m
-1.7
-0.7
-3.2
0.3
-1.6
-2.3
1.9
-2.9
-3.0
2.7
2.6
9.9
Momentum
-1.7
-0.7
-3.2
0.3
-1.6
-2.3
1.9
-2.9
-3.0
2.7
2.6
9.9
Quality Income
-1.8
-2.3
0.0
-0.6
-0.6
-1.2
-4.8
-5.7
-5.4
6.0
3.0
3.6
R12m-1m
-2.1
-1.2
-4.3
0.8
-1.1
-2.3
2.9
-0.9
-0.3
2.9
4.8
8.7
IMOM3m-1m
-2.1
-1.5
-2.7
0.6
-2.3
-1.1
4.1
-1.1
9.9
3.4
3.8
2.5
R3m-1m
-2.8
-2.8
-3.0
0.0
-1.7
-2.5
3.0
-0.5
14.3
3.9
6.5
3.1
6.3
-0.7
Source: SG Cross Asset Research/Equity Quant, FactSet, FactSet, FTSE, I/B/E/S *For our Quality Income and Graham & Rea screen, the Q5 portfolio contains all stocks that do not pass the screen
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List of factors included in our Style Counselling report Below is the list of factors included in the document along with links to previous research documents covering the factors. For more details on the factor construction and analysis section of the report, see our September-2014 edition of Global Style Counselling ( link link ). ). Factor list
PE
Price to 12-month trailing earnings
Yes
Included
Descending
link
FY1 PE
Price to FY1 earnings
Yes
Included
Descending
link
PB
Price to last reported book value
Yes
Included
Descending
link
PFCF
Price to 12-month trailing free cash flow
Yes
Excluded
Descending
link
EVEBITDA
EV to 12-month trailing EBITDA
Yes
Excluded
Descending
link
No
Included
Ascending
link
No
Included
Ascending
No
Included
Ascending
No
Included
Ascending
No
Included
Ascending
link
Yield BB DY+BB DY+BB+DEBT R12m-1m
Next 12-month dividend yield (or 12-month trailing when not available) Annual net share share repurchases to market cap Annual net share share repurchases + annual dividend to market cap Annual net share share repurchases + annual dividend + annual debt reduction to market cap 12-month total return lagged by 1-month
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Report completed on 13 Aug. 2018 13:39 CET
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