quantitative stock selection
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Global Asset Allocation and Stock Selection. Quantitative Stock Selection. Campbell R. Harvey Duke University National Bureau of Economic Research. Quantitative Stock Selection 1. Introduction. Research coauthored with Dana Achour Greg Hopkins Clive Lang. - PowerPoint PPT PresentationTRANSCRIPT
Quantitative Stock SelectionQuantitative Stock Selection
Campbell R. HarveyDuke University
National Bureau of Economic Research
Global Asset Allocation and Stock Selection
Quantitative Stock Selection 1. Introduction
Research coauthored with• Dana Achour• Greg Hopkins• Clive Lang
Quantitative Stock Selection 1. Introduction
Issue
Two decisions are important:
• Asset Allocation (country picks)
• Asset Selection (equity picks)
Quantitative Stock Selection 1. Introduction
Issue
• Considerable research on the asset allocation side
• Research has paid off in that many models avoided “overvalued” Asian markets in mid-1990s
• Many models began overweighing after the onset of the Asia Crisis
Quantitative Stock Selection 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
Quantitative Stock Selection 1. Introduction
With recent plummet in emerging markets,stock selection is important.
If market is deemed “cheap,” (as manyasset allocation models would now suggest),which stocks do we select?
Quantitative Stock Selection 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
Quantitative Stock Selection 2. Stock Selection Metrics
Methodologies:• Cross-sectional regression• Sorting• Hybrids
Quantitative Stock Selection 2. Stock Selection Metrics
Cross-sectional regression:For country j, estimate:
where i denotes firm i;A is a firm specific attribute (could be multiple) are common regression coefficients
tititi AR ,1,10,
Quantitative Stock Selection 2. Stock Selection Metrics
Cross-sectional regression:• Used in developed market stock selection• Problem with unstable coefficients• Bigger problem given noisy emerging market
returns
Quantitative Stock Selection 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
Quantitative Stock Selection 2. Stock Selection Metrics
Sorting:• Simple methodology that provides a good
starting point to investigate stock selection
Quantitative Stock Selection 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
Quantitative Stock Selection 3. Our methodology
Focus on three emerging markets:• Malaysia (representative of Asia)• Mexico (indicative of Latin America)• South Africa (unique situation)
Quantitative Stock Selection 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
Quantitative Stock Selection 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]
Quantitative Stock Selection 3. Our methodology
Steps:
1. Specify list of factors2. Univariate screens (in sample)3. Bivariate diagnostic screens4. Battery of additional diagnostics emphasizing performance through time5. Bivariate selection screens
Quantitative Stock Selection 3. Our methodology
Steps:
6. Optimize to form “scoring screen” (in sample)7. Run scoring screen on out-of-sample period8. Diagnostics on scoring screen9. Form “buy list” and “sell lists”10. Purge “buy list” of stocks that are identified
by predetermined set of “knock out criteria”
Quantitative Stock Selection 3. Our methodology
Steps:
11. Investigate turnover of portfolio – various holding periods analyzed
Quantitative Stock Selection 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,
2000)
Quantitative Stock Selection 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
Quantitative Stock Selection 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
Quantitative Stock Selection 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
Quantitative Stock Selection 4. Factors
Momentum
• One month/ 1 year price momentum
• One year historical earnings growth/momentum
• Three year historical earnings growth rate
Quantitative Stock Selection 4. Factors
Diagnostic
• Market capitalization
• Debt to common equity ratio
Quantitative Stock Selection 5. Diagnostics
• Average return
• Average excess return
• Standard deviation
• T-stat (hypothesis that excess return=0)
• Beta (against benchmark index)
• Alpha
• R2
Quantitative Stock Selection 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
Quantitative Stock Selection 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
Quantitative Stock Selection 5. Diagnostics
• Factor average for constructed portfolio
• Factor median
• Factor standard deviation
0
50
100
150
200
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300
350
400
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Malaysia IFC US$ Malaysia FX
Quantitative Stock Selection 6. Summary Statistics: Malaysia Benchmark
87% drop
Data through January 2001
0100200300400500600700800900
1000
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Mexico IFC Mexico FX
Quantitative Stock Selection 6. Summary Statistics: Mexico Benchmark
68% drop
Data through January 2001
0
50
100
150
200
250
300
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
South Africa IFC US$ South Africa FX
Quantitative Stock Selection 6. Summary Statistics: South Africa Benchmark
55% drop
Data through January 2001
-30
-25
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-15
-10
-5
0
5
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15
Top Bottom
Quantitative Stock Selection 6. Malaysia: Factor returns
-5
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35
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Quantitative Stock Selection 6. Mexico: Factor returns
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Quantitative Stock Selection 6. South Africa: Factor returns
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Quantitative Stock Selection 6. Malaysia: % Periods Benchmark Outperformance
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Quantitative Stock Selection 6. Mexico: % Periods Benchmark Outperformance
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Quantitative Stock Selection 6. South Africa: % Periods Benchmark Outperformance
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Quantitative Stock Selection 6. Malaysia: Dividend Yield Screen: Index=100 each year
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Quantitative Stock Selection 6. Mexico: Historical Earnings Momentum Screen: Index=100 each year
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Quantitative Stock Selection 6. South Africa: Change in Consensus FY1-3 mo. Screen: Index=100 each year
-50-40-30-20-10
01020304050
Mala
ysia
Mex
ico
Sout
h A
frica
Quantitative Stock Selection 6. Book to Price: Low-High Spread
-50-40-30-20-10
01020304050
Mala
ysia
Mex
ico
Sout
h A
frica
Quantitative Stock Selection 6. IBES Revision Ratio: Low-High Spread
-50-40-30-20-10
01020304050
Mala
ysia
Mex
ico
Sout
h A
frica
Quantitative Stock Selection 6. IBES 12-month Prospective Earnings Yield: L-H Spread
-50-40-30-20-10
01020304050
Mala
ysia
Mex
ico
Sout
h A
frica
Quantitative Stock Selection 6. One-year Momentum: Low-High Spread
-50-40-30-20-10
01020304050
Mala
ysia
Mex
ico
Sout
h A
frica
Quantitative Stock Selection 6. Size Effect: Low-High Spread
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Quantitative Stock Selection 6. Malaysia: Scoring Screen Various Holding Periods
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35
Top Bottom
Quantitative Stock Selection 6. Mexico: Scoring Screen Various Holding Periods
-10
-5
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20
Top Bottom
Quantitative Stock Selection 6. South Africa: Scoring Screen Various Holding Periods
0102030405060708090
100
Top Bottom
Quantitative Stock Selection 6. Malaysia: Scoring Screen % Periods Benchmark Outperformance
0102030405060708090
100
Top Bottom
Quantitative Stock Selection 6. Mexico: Scoring Screen % Periods Benchmark Outperformance
0102030405060708090
100
Top Bottom
Quantitative Stock Selection 6. South Africa: Scoring Screen % Periods Benchmark Outperformance
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Quantitative Stock Selection 6. Malaysia: Scoring Screen: Index=100 each year
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Quantitative Stock Selection 6. Mexico: Scoring Screen: Index=100 each year
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Quantitative Stock Selection 6. South Africa: Scoring Screen: Index=100 each year
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12/31/88 12/31/89 12/31/90 12/31/91 12/31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/97
CU
MU
LA
TIV
E R
ET
UR
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N S
AM
PL
E
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LE
IFCG MALAYSIA
IN SAMPLE OUT OF SAMPLE
TOP
FR
IFCG MALAYSIA
BOTTOM
IN SAMPLE OUT OF SAMPLE
IBES DATA ADDED
Quantitative Stock Selection 6. Malaysia: Scoring Screen
Quantitative Stock Selection 6. Mexico: Scoring Screen
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12/31/88 12/31/89 12/31/90 12/31/91 12/31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/97
CU
MU
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TIV
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IN S
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IN SAMPLE OUT OF SAMPLE
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IFCG MEXICO
BOTTOM
IN SAMPLE OUT OF SAMPLE
Quantitative Stock Selection 6. South Africa: Scoring Screen
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12/31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/97
CU
MU
LA
TIV
E R
ETU
RN
S -
IN S
AM
PL
E
0.00
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IFCG SOUTH AFRICA
IN SAMPLE OUT OF SAMPLE
Quantitative Stock Selection 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?
Quantitative Stock Selection 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
Quantitative Stock Selection 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?
Quantitative Stock Selection 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?
Quantitative Stock Selection 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?