Quantitative Stock Selection 1. Introduction

Transcription

1 Global Asset Allocation and Stock Selection Campbell R. Harvey 1. Introduction Research coauthored with Dana Achour Greg Hopkins Clive Lang 1

2 1. Introduction Issue Two decisions are important: Asset Allocation (country picks) Asset Selection (equity picks) 1. Introduction Issue Considerable research on the asset allocation side Research has paid off in that many models avoided overvalued Asian markets in mid-199s Many models began overweighing after the onset of the Asia Crisis 2

3 1. Introduction Issue Little research on the stock selection side. Why? Sparse data on individual stocks Information asymmetries among local and global investors Extremely high transactions costs 1. Introduction With recent plummet in emerging markets, stock selection is important. If market is deemed cheap, (as many asset allocation models would now suggest), which stocks do we select? 3

4 2. Stock Selection Metrics Ingredients for success: Identify stable relationships Attempt to model unstable relationships Use predictor variables that reflect the future, not necessarily the past Do not overfit Validate in up-markets as well as down Tailor to country characteristics in emerging markets 2. Stock Selection Metrics Methodologies: Cross-sectional regression Sorting Hybrids 4

5 2. Stock Selection Metrics Cross-sectional regression: For country j, estimate: R i, t = γ + γ 1Ai, t 1 + ε i, t where i denotes firm i; A is a firm specific attribute (could be multiple) γ are common regression coefficients 2. Stock Selection Metrics Cross-sectional regression: Used in developed market stock selection Problem with unstable coefficients Bigger problem given noisy emerging market returns 5

6 2. Stock Selection Metrics Sorting: Used in developed market stock selection Potentially similar in stability problems Can be cast in regression framework (a regression on ranks, or a multinomial probit regression) Rank regression may have advantages given the high variance (high noise) in emerging equity returns 2. Stock Selection Metrics Sorting: Simple methodology that provides a good starting point to investigate stock selection 6

7 2. Stock Selection Metrics Hybrid: Create portfolios based on stocks sorted by attributes Use regression or optimization to weight portfolios Produces a flexible, highly nonlinear way to select stocks 3. Our methodology Focus on three emerging markets: Malaysia (representative of Asia) Mexico (indicative of Latin America) South Africa (unique situation) 7

8 3. Our methodology Specify exhaustive list of firm specific factors Includes many traditional factors Extra emphasis on expectations factors Specific a number of diagnostic variables Includes factors that reflect the type of firm we are selecting 3. Our methodology Identify the best stocks and the worst stocks Do not impose the constraints of a tracking error methodology [Tracking error can be dealt with at a later stage of the analysis] 8

9 3. Our methodology Steps: 1. Specify list of factors 2. Univariate screens (in sample) 3. Bivariate diagnostic screens 4. Battery of additional diagnostics emphasizing performance through time 5. Bivariate selection screens 3. Our methodology Steps: 6. Optimize to form scoring screen (in sample) 7. Run scoring screen on out-of-sample period 8. Diagnostics on scoring screen 9. Form buy list and sell lists 1. Purge buy list of stocks that are identified by predetermined set of knock out criteria 9

10 3. Our methodology Steps: 11. Investigate turnover of portfolio various holding periods analyzed 4. Past research Very few papers: Rouwenhorst (JF) looks at IFC data Claessens, Dasgupta and Glen (EMQ) look at IFC data Fama and French (JF) look at IFC data Achour, Harvey, Hopkins, Lang (1998, 1999, 2) 1

11 4. Past research What we offer: No one has merged IFC, MSCI, Worldscope, and IBES data First paper to look at comprehensive list of firm attributes First paper to look at expectational attributes 4. Factors Fundamental factors Dividend yield Earnings yield Book to price ratio Cash earnings to price yield Change in return on equity Revenue growth Rate of re-investment Return on equity 11

12 4. Factors Expectational Change in consensus FY1 estimate - last 3 or 6 months Consensus FY2 to FY1 estimate change Consensus forecast earnings estimate revision ratio 12 months prospective earnings growth rate 3 year prospective earnings growth rate 12 month prospective earnings yield 4. Factors Momentum One month/ 1 year price momentum One year historical earnings growth/momentum Three year historical earnings growth rate 12

13 4. Factors Diagnostic Market capitalization Debt to common equity ratio 5. Diagnostics Average return Average excess return Standard deviation T-stat (hypothesis that excess return=) Beta (against benchmark index) Alpha R 2 13

14 5. Diagnostics Average capitalization % periods > market index (hit rate) % periods > market index in up markets % periods > market index in down markets Max number of consecutive benchmark outperformances 5. Diagnostics Max observed excess return Min observed excess return Max number of consecutive negative returns Max number of consecutive positive returns Year by year returns 14

15 5. Diagnostics Factor average for constructed portfolio Factor median Factor standard deviation 6. Summary Statistics: Malaysia Benchmark % drop Malaysia IFC US$ Malaysia FX Data through January 21 15

16 6. Summary Statistics: Mexico Benchmark % drop Mexico IFC Mexico FX Data through January Summary Statistics: South Africa Benchmark % drop South Africa IFC US$ South Africa FX Data through January 21 16

17 6. Malaysia: Factor returns Cap D ROI D/E Div 1 Yr Earn Mom 3 Yr Earn Mom E/P D FYI 3mo D FYI 6mo FY1 to FY2 Rev Ratio Top B/P CE/P 1 mo Mom 1 yr Mom Prop E/P Prop 3yr D Earn 12 mo Prop E/P 24 mo Prop E/P Bottom D Rev Reinvest ROE Index return 6. Mexico: Factor returns Cap D ROI D/E Div 1 Yr Earn Mom 3 Yr Earn Mom -5 E/P D FYI 3mo D FYI 6mo FY1 to FY2 Rev Ratio Top B/P CE/P 1 mo Mom 1 yr Mom Prop E/P Prop 3yr D Earn Bottom 12 mo Prop E/P 24 mo Prop E/P D Rev Reinvest ROE Index return 17

18 South Africa: Factor returns 5 Cap D ROI D/E Div 1 Yr Earn Mom 3 Yr Earn Mom E/P D FYI 3mo D FYI 6mo FY1 to FY2 Rev Ratio Top B/P CE/P 1 mo Mom 1 yr Mom Prop E/P Prop 3yr D Earn 12 mo Prop E/P 24 mo Prop E/P Bottom D Rev Reinvest ROE Index return Malaysia: % Periods Benchmark Outperformance Cap D ROI D/E Div 1 Yr Earn Mom 3 Yr Earn Mom E/P D FYI 3mo D FYI 6mo FY1 to FY2 Rev Ratio Top B/P CE/P 1 mo Mom 1 yr Mom Prop E/P Prop 3yr D Earn 12 mo Prop E/P 24 mo Prop E/P Bottom D Rev Reinvest ROE 1 18

19 Mexico: % Periods Benchmark Outperformance Cap D ROI D/E Div 1 Yr Earn Mom 3 Yr Earn Mom E/P D FYI 3mo D FYI 6mo FY1 to FY2 Rev Ratio Top B/P CE/P 1 mo Mom 1 yr Mom Prop E/P Prop 3yr D Earn 12 mo Prop E/P 24 mo Prop E/P Bottom D Rev Reinvest ROE South Africa: % Periods Benchmark Outperformance Cap D ROI D/E Div 1 Yr Earn Mom 3 Yr Earn Mom E/P D FYI 3mo D FYI 6mo FY1 to FY2 Rev Ratio Top B/P CE/P 1 mo Mom 1 yr Mom Prop E/P Prop 3yr D Earn 12 mo Prop E/P 24 mo Prop E/P Bottom D Rev Reinvest ROE 1 19

20 25 6. Malaysia: Dividend Yield Screen: Index=1 each year Top Benchmark Bottom Mexico: Historical Earnings Momentum Screen: Index=1 each year Top Benchmark Bottom

21 South Africa: Change in Consensus FY1-3 mo. Screen: Index=1 each year Top Benchmark Bottom Book to Price: Low-High Spread Malaysia Mexico South Africa 21

22 6. IBES Revision Ratio: Low-High Spread Malaysia Mexico South Africa 6. IBES 12-month Prospective Earnings Yield: L-H Spread Malaysia Mexico South Africa 22

23 6. One-year Momentum: Low-High Spread Malaysia Mexico South Africa 6. Size Effect: Low-High Spread Malaysia Mexico South Africa 23

24 6. Malaysia: Scoring Screen Various Holding Periods Monthly Quarterly Top Semiannual Bottom Semiannual w/ko Market 6. Mexico: Scoring Screen Various Holding Periods Monthly Quarterly Top Bottom Semiannual Market 24

25 6. South Africa: Scoring Screen Various Holding Periods Monthly Quarterly Top Bottom Semiannual Market 6. Malaysia: Scoring Screen % Periods Benchmark Outperformance Monthly Quarterly Top Bottom Semiannual Semiannual w/ko 25

26 6. Mexico: Scoring Screen % Periods Benchmark Outperformance Monthly Top Quarterly Bottom Semiannual 6. South Africa: Scoring Screen % Periods Benchmark Outperformance Monthly Top Quarterly Bottom Semiannual 26

27 25 6. Malaysia: Scoring Screen: Index=1 each year Top Bottom Mexico: Scoring Screen: Index=1 each year Top Bottom

28 6. South Africa: Scoring Screen: Index=1 each year Top 1996 Bottom Malaysia: Scoring Screen IN SAMPLE OUT OF SAMPLE TOP FR CUMULATIVE RETURNS - IN SAMPLE IBES DATA ADDED IFCG MALAYSIA CUMULATIVE RETURNS - OUT OF SAMPLE 2. BOTTOM /31/88 12/31/89 12/31/9 12/31/91 12/31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/97. 28

29 CUMULATIVE RETURNS - IN SAMPLE 6. Mexico: Scoring Screen IN SAMPLE OUT OF SAMPLE 21. TOP IFCG MEXICO BOTTOM /31/88 12/31/89 12/31/9 12/31/91 12/31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/ CUMULATIVE RETURNS - OUT OF SAMPLE 6. South Africa: Scoring Screen 35. IN SAMPLE OUT OF SAMPLE TOP CUMULATIVE RETURNS - IN SAMPLE IFCG SOUTH AFRICA BOTTOM CUMULATIVE RETURNS - OUT OF SAMPLE /31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/97. 29

30 7. Research Directions 1) Comparison of regression method and multivariate screening process Panel multinomial probit models How do we reduce the noise in emerging market equity returns? 7. Research Directions 2) What are the characteristics of countries that make some factors work and other not work? Stage of market integration process Industrial mix Openness of economy Microstructure factors 3

31 7. Research Directions 3) What causes the shifting importance of factors through time, e.g. value versus growth? Can the cross-section of many stock returns help us identify when a factor is likely to work? 7. Research Directions 4) Can the country selection process be merged with the stock selection exercise? Should buy portfolios be used in top-down optimizations? Does country-specific tracking error really matter in global asset allocation? 31

32 7. Research Directions 5) Should we expand our view of risk in both the stock selection and country selection exercises? Mean, variance, skewness? What are the driving forces of changing variance? What are the determinants of skewness? 32