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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
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 many
asset 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:
Ri ,t g 0 g 1 Ai ,t 1 i ,t
where
i denotes firm i;
A is a firm specific attribute (could be multiple)
g are common regression coefficients
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 factors
2. Univariate screens (in sample)
3. Bivariate diagnostic screens
4. Battery of additional diagnostics emphasizing
performance through time
5. 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 period
8. Diagnostics on scoring screen
9. 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
Quantitative Stock Selection
6. Summary Statistics: Malaysia Benchmark
400
350
300
250
87% drop
200
150
100
50
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Malaysia IFC US$ Malaysia FX
Data through January 2001
Quantitative Stock Selection
6. Summary Statistics: Mexico Benchmark
1000
900
800
700
600
500 68% drop
400
300
200
100
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Mexico IFC Mexico FX
Data through January 2001
Quantitative Stock Selection
6. Summary Statistics: South Africa Benchmark
300
250
200
150 55% drop
100
50
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
South Africa IFC US$ South Africa FX
Data through January 2001
-30
-25
-20
-15
-10
-5
0
5
10
15
Ca
p
D
RO
I
D
1 /E
Yr
E D
3 arn iv
Yr M
Ea om
rn
M
om
D E
FY /P
I
D 3m
FY o
FY I 6m
1
to o
F
Top
Re Y2
v
6. Malaysia: Factor returns
Ra
t io
B/
P
1 CE
m /P
o
M
1 o
Bottom
yr m
M
Pr P om
op rop
3 E
12 y r D /P
Quantitative Stock Selection
m
o Ea
24 Pr rn
m op
o E
Pr /P
op
E/
P
D
R
Re ev
in
ve
st
In RO
de
xr E
et
ur
n
-5
0
5
10
15
20
25
30
35
Ca
p
D
RO
I
D
1 /E
Yr
E D
3 arn iv
Yr M
Ea om
rn
M
om
D E
FY /P
I
D 3m
FY o
FY I 6m
1
to o
F
6. Mexico: Factor returns
Top
Re Y2
v
Ra
t io
B/
P
1 CE
m /P
o
M
1 o
Bottom
yr m
M
Pr P om
op rop
3 E
12 y r D /P
Quantitative Stock Selection
m
o Ea
24 Pr rn
m op
o E
Pr /P
op
E/
P
D
R
Re ev
in
ve
st
In RO
de
xr E
et
ur
n
0
5
10
15
20
25
30
Ca
p
D
RO
I
D
1 /E
Yr
E D
3 arn iv
Yr M
Ea om
rn
M
om
D E
FY /P
I
D 3m
FY o
FY I 6m
1
to o
F
Top
Re Y2
v
Ra
t io
6. South Africa: Factor returns
B/
P
1 CE
m /P
o
M
1 o
Bottom
yr m
M
Pr P om
op rop
3 E
12 y r D /P
Quantitative Stock Selection
m
o Ea
24 Pr rn
m op
o E
Pr /P
op
E/
P
D
R
Re ev
in
ve
st
In RO
de
xr E
et
ur
n
0
10
20
30
40
50
60
70
Ca
p
D
RO
I
D
1 /E
Yr
E D
3 arn iv
Yr M
Ea om
rn
M
om
D E
FY /P
I
D 3m
FY o
FY I 6m
1
to o
F
Top
Re Y2
v
Ra
t io
B/
P
1 CE
m /P
o
M
1 o
Bottom
yr m
M
Pr P om
op rop
3 E
12 y r D /P
Quantitative Stock Selection
m
o Ea
24 Pr rn
m op
o E
Pr /P
op
E/
P
D
R
6. Malaysia: % Periods Benchmark Outperformance
Re ev
in
ve
st
RO
E
0
10
20
30
40
50
60
70
Ca
p
D
RO
I
D
1 /E
Yr
E D
3 arn iv
Yr M
Ea om
rn
M
om
D E
FY /P
I
D 3m
FY o
FY I 6m
1
to o
F
Top
Re Y2
v
Ra
t io
B/
P
1 CE
m /P
o
M
1 o
Bottom
yr m
M
Pr P om
op rop
3 E
12 y r D /P
Quantitative Stock Selection
m
o Ea
24 Pr rn
m op
o E
Pr /P
op
E/
P
6. Mexico: % Periods Benchmark Outperformance
D
R
Re ev
in
ve
st
RO
E
0
10
20
30
40
50
60
70
Ca
p
D
RO
I
D
1 /E
Yr
E D
3 arn iv
Yr M
Ea om
rn
M
om
D E
FY /P
I
D 3m
FY o
FY I 6m
1
to o
Top
F
Re Y2
v
Ra
t io
B/
P
1 CE
m /P
o
M
Bottom
1 o
yr m
M
Pr P om
op rop
3 E
12 y r D /P
Quantitative Stock Selection
m
o Ea
24 Pr rn
m op
o E
Pr /P
op
E/
P
D
R
Re ev
in
ve
st
6. South Africa: % Periods Benchmark Outperformance
RO
E
Quantitative Stock Selection
6. Malaysia: Dividend Yield Screen: Index=100 each year
250
200
150
100
50
0
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Top Benchmark Bottom
Quantitative Stock Selection
6. Mexico: Historical Earnings Momentum Screen:
Index=100 each year
300
250
200
150
100
50
0
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Top Benchmark Bottom
Quantitative Stock Selection
6. South Africa: Change in Consensus FY1-3 mo. Screen:
Index=100 each year
200
180
160
140
120
100
80
60
40
20
0
93
94
95
96
97
98
19
19
19
19
19
19
Top Benchmark Bottom
Quantitative Stock Selection
6. Book to Price: Low-High Spread
50
40
30
20
10
0
-10
-20
-30
South Africa
-40
Mexico
-50
Malaysia
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Quantitative Stock Selection
6. IBES Revision Ratio: Low-High Spread
50
40
30
20
10
0
-10
-20
-30
South Africa
-40
Mexico
-50
Malaysia
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Quantitative Stock Selection
6. IBES 12-month Prospective Earnings Yield: L-H Spread
50
40
30
20
10
0
-10
-20
-30
South Africa
-40
Mexico
-50
Malaysia
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Quantitative Stock Selection
6. One-year Momentum: Low-High Spread
50
40
30
20
10
0
-10
-20
-30
South Africa
-40
Mexico
-50
Malaysia
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Quantitative Stock Selection
6. Size Effect: Low-High Spread
50
40
30
20
10
0
-10
-20
-30
South Africa
-40
Mexico
-50
Malaysia
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Quantitative Stock Selection
6. Malaysia: Scoring Screen Various Holding Periods
15
10
5
0
-5
-10
-15
-20 al
ly
rly
t
KO
ke
nu
th
rte
ar
on
w/
ian
M
ua
M
al
m
Q
nu
Se
ian
m
Se
Top Bottom
Quantitative Stock Selection
6. Mexico: Scoring Screen Various Holding Periods
35
30
25
20
15
10
5
0
l
ly
ly
t
ua
ke
th
ter
n
ar
on
ian
ar
M
M
Qu
m
Se
Top Bottom
Quantitative Stock Selection
6. South Africa: Scoring Screen Various Holding Periods
20
15
10
5
0
-5
-10
l
ly
ly
t
ua
ke
th
ter
n
ar
on
ian
ar
M
M
Qu
m
Se
Top Bottom
Quantitative Stock Selection
6. Malaysia: Scoring Screen
% Periods Benchmark Outperformance
100
90
80
70
60
50
40
30
20
10
0
al
ly
rly
KO
nu
th
rte
on
w/
ian
ua
M
al
m
Q
nu
Se
ian
m
Se
Top Bottom
Quantitative Stock Selection
6. Mexico: Scoring Screen
% Periods Benchmark Outperformance
100
90
80
70
60
50
40
30
20
10
0
al
ly
rly
nu
th
rte
on
ian
ua
M
m
Q
Se
Top Bottom
Quantitative Stock Selection
6. South Africa: Scoring Screen
% Periods Benchmark Outperformance
100
90
80
70
60
50
40
30
20
10
0
al
ly
rly
nu
th
rte
on
ian
ua
M
m
Q
Se
Top Bottom
Quantitative Stock Selection
6. Malaysia: Scoring Screen: Index=100 each year
250
200
150
100
50
0
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Top Bottom
Quantitative Stock Selection
6. Mexico: Scoring Screen: Index=100 each year
300
250
200
150
100
50
0
89
90
91
92
93
94
95
96
97
98
19
19
19
19
19
19
19
19
19
19
Top Bottom
Quantitative Stock Selection
6. South Africa: Scoring Screen: Index=100 each year
200
180
160
140
120
100
80
60
40
20
0
93
94
95
96
97
98
19
19
19
19
19
19
Top Bottom
Quantitative Stock Selection
6. Malaysia: Scoring Screen IN SAMPLE OUT OF SAMPLE
900.00 160.00
T OP
FR
800.00
140.00
CUMULATIVE RETURNS - OUT OF SAMPLE
700.00
120.00
CUMULATIVE RETURNS - IN SAMPLE
600.00
100.00
500.00 IFCG MALAYSIA
80.00
400.00 IBES DATA
ADDED
60.00
300.00
40.00
200.00 BOT T OM
20.00
100.00
0.00 0.00
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
Quantitative Stock Selection
6. Mexico: Scoring Screen IN SAMPLE OUT OF SAMPLE
2100.00 250.00
T OP
2000.00
1900.00
1800.00
1700.00 200.00
CUMULATIVE RETURNS - OUT OF SAMPLE
1600.00
CUMULATIVE RETURNS - IN SAMPLE
1500.00
1400.00
1300.00
150.00
1200.00
IFCG MEXICO
1100.00
1000.00
900.00
100.00
800.00
700.00
600.00
500.00
BOT T OM
400.00 50.00
300.00
200.00
100.00
0.00 0.00
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
Quantitative Stock Selection
6. South Africa: Scoring Screen
IN SAMPLE OUT OF SAMPLE
350.00 120.00
T OP
300.00
100.00
CUMULATIVE RETURNS - OUT OF SAMPLE
CUMULATIVE RETURNS - IN SAMPLE
250.00
80.00
IFCG SOUT H
200.00 AFRICA
60.00
150.00
BOT T OM
40.00
100.00
20.00
50.00
0.00 0.00
12/31/92 12/31/93 12/31/94 12/31/95 12/31/96 12/31/97
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) Stability and migration tracking
– Should we consider the behavior of the stock
moving from fractile to fractile?
Quantitative Stock Selection
7. Research Directions
6) 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?
