keith c. brown the university of texas w. van harlow fidelity investments
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Keith C. BrownKeith C. BrownThe University of TexasThe University of Texas
W. Van HarlowW. Van HarlowFidelity InvestmentsFidelity Investments
Federal Reserve Bank of Atlanta Financial Markets Federal Reserve Bank of Atlanta Financial Markets ConferenceConference
April 15, 2004April 15, 2004
Staying the Course:Mutual Fund Investment Style Consistency
and Performance Persistence
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W4500
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Research PremiseResearch Premise
Lower Style Consistency
Does Investment Style Consistency Impact Performance?
Cap
: S
mall t
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e (
%)
Value to Growth (%)
Cap
: S
mall t
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e (
%)
Value to Growth (%)
Higher Style Consistency
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Why Style Consistency Why Style Consistency MightMight Matter Matter
Fund Outflows Due to Style DriftFund Outflows Due to Style Drift Inability of Plan Sponsors to Identify Manager’s StyleInability of Plan Sponsors to Identify Manager’s Style
Higher Consistency = Lower Turnover?Higher Consistency = Lower Turnover? Possibility of Lower Transaction Costs and Expense RatiosPossibility of Lower Transaction Costs and Expense Ratios
Style Timing Might be a “Loser’s Game”Style Timing Might be a “Loser’s Game” Analog to Difficulty of Successful Tactical Asset AllocationAnalog to Difficulty of Successful Tactical Asset Allocation
Style Consistency as a Possible “Signal” of Style Consistency as a Possible “Signal” of Superior Manager PerformanceSuperior Manager Performance
4
PeerGroup
StyleConsistency
AverageAnnual Return (1991-2000)
Lower 11.10%Large ValueHigher 13.05%
Large Blend Lower 16.69%Higher 20.04%Lower 18.55%Large GrowthHigher 19.86%Lower 17.30%Mid ValueHigher 13.58%Lower 12.95%Mid BlendHigher 12.86%Lower 13.90%Mid GrowthHigher 15.44%Lower 15.83%Small ValueHigher 16.65%Lower 14.28%Small BlendHigher 15.62%Lower 12.78%Small GrowthHigher 14.21%
Higher Returns for More
Style Consistent Funds
Simple EvidenceSimple Evidence
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Complicating FactorsComplicating Factors
PeerGroup
StyleConsistency
MedianTurnover
MedianExpense Ratio
Lower 11.10% 1.22%Large ValueHigher 13.05% 1.02%
Large Blend Lower 16.69% 1.25%Higher 20.04% 0.93%Lower 18.55% 1.36%Large GrowthHigher 19.86% 1.07%Lower 17.30% 1.40%Mid ValueHigher 13.58% 1.16%Lower 12.95% 1.41%Mid BlendHigher 12.86% 1.23%Lower 13.90% 1.40%Mid GrowthHigher 15.44% 1.29%Lower 15.83% 1.39%Small ValueHigher 16.65% 1.15%
Small Blend Lower 14.28% 1.50%Higher 15.62% 1.12%Lower 12.78% 1.46%Small GrowthHigher 14.21%
47.50%45.50%77.00%38.00%68.00%60.50%63.00%60.00%63.00%39.59%
115.00%76.00%50.00%44.82%84.50%47.00%89.00%78.00% 1.33%
Higher Returns for More
Style Consistent Funds
Median AnnualFund Return (1991-2000)
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Complicating FactorsComplicating Factors
PeerGroup
StyleConsistency
MedianTurnover
MedianExpense Ratio
Lower 11.10% 1.22%Large ValueHigher 13.05% 1.02%
Large Blend Lower 16.69% 1.25%Higher 20.04% 0.93%Lower 18.55% 1.36%Large GrowthHigher 19.86% 1.07%Lower 17.30% 1.40%Mid ValueHigher 13.58% 1.16%Lower 12.95% 1.41%Mid BlendHigher 12.86% 1.23%Lower 13.90% 1.40%Mid GrowthHigher 15.44% 1.29%Lower 15.83% 1.39%Small ValueHigher 16.65% 1.15%
Small Blend Lower 14.28% 1.50%Higher 15.62% 1.12%Lower 12.78% 1.46%Small GrowthHigher 14.21%
47.50%45.50%77.00%38.00%68.00%60.50%63.00%60.00%63.00%39.59%
115.00%76.00%50.00%44.82%84.50%47.00%89.00%78.00% 1.33%
Higher Returns for More
Style Consistent Funds
Median AnnualFund Return (1991-2000)
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Past LiteraturePast Literature Investment Style Appears to MatterInvestment Style Appears to Matter
Fund ObjectivesFund Objectives: McDonald (JFQA, 1974); Malkiel (JF, 1995): McDonald (JFQA, 1974); Malkiel (JF, 1995) Security CharacteristicsSecurity Characteristics: Basu (JF, 1977); Banz (JFE, 1981); Fama and : Basu (JF, 1977); Banz (JFE, 1981); Fama and
French (JF, 1992; JFE, 1993)French (JF, 1992; JFE, 1993) Style PremiumsStyle Premiums: Capaul, Rawley, Sharpe (FAJ, 1993); Lakonishok, Shleifer, : Capaul, Rawley, Sharpe (FAJ, 1993); Lakonishok, Shleifer,
Vishny (JF, 1994); Fama and French (JF, 1998); Chan and Lakonishok (FAJ, Vishny (JF, 1994); Fama and French (JF, 1998); Chan and Lakonishok (FAJ, 2004); Phalippou (Working Paper, 2004)2004); Phalippou (Working Paper, 2004)
Style DefinitionsStyle Definitions: Roll (HES, 1995); Brown and Goetzmann (JFE, 1997): Roll (HES, 1995); Brown and Goetzmann (JFE, 1997) Style RotationStyle Rotation: Barberis and Shleifer (JFE, 2003): Barberis and Shleifer (JFE, 2003)
Fund Performance PersistenceFund Performance Persistence Classic Study: Classic Study: Jensen (JF, 1968)Jensen (JF, 1968) Hot & Icy HandsHot & Icy Hands: Grinblatt and Titman (JF, 1992); Hendricks, Patel, : Grinblatt and Titman (JF, 1992); Hendricks, Patel,
Zeckhauser (JF, 1993); Brown and Goetzmann (JF, 1995); Elton, Gruber, Zeckhauser (JF, 1993); Brown and Goetzmann (JF, 1995); Elton, Gruber, Blake (JB, 1996), Ibbotson and Patel (Working Paper, 2002)Blake (JB, 1996), Ibbotson and Patel (Working Paper, 2002)
Accounting for MomentumAccounting for Momentum: Jegadeesh and Titman (JF, 1993); Carhart (JF, : Jegadeesh and Titman (JF, 1993); Carhart (JF, 1997); Wermers (2001)1997); Wermers (2001)
Conditioning InformationConditioning Information: Ferson and Schadt (JF, 1996), Christopherson, : Ferson and Schadt (JF, 1996), Christopherson, Ferson, and Glassman (RFS, 1998)Ferson, and Glassman (RFS, 1998)
Persistence & StylePersistence & Style: Bogle (JPM, 1998); Teo and Woo (JFE, forthcoming): Bogle (JPM, 1998); Teo and Woo (JFE, forthcoming)
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Research DesignResearch Design
Use alternative definitions of style consistencyUse alternative definitions of style consistency
Control for other factors affecting performanceControl for other factors affecting performance Alpha persistenceAlpha persistence
Expense ratioExpense ratio
TurnoverTurnover
Fund sizeFund size
Active/passive managementActive/passive management
Does Style Consistency Impact Performance?
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Measuring Investment Style & Measuring Investment Style & Style Consistency: Two Style Consistency: Two
ApproachesApproaches Holdings-Based Measures: Holdings-Based Measures: Daniel, Daniel,
Grinblatt, Titman, and Wermers (JF, 1997)Grinblatt, Titman, and Wermers (JF, 1997) Pros: Pros: Direct Assessment of Manager’s Selection and Timing Direct Assessment of Manager’s Selection and Timing
Skills; Benchmark Construction Around Security CharacteristicsSkills; Benchmark Construction Around Security Characteristics Cons: Cons: Unobservable or Observed with Considerable Lag; Unobservable or Observed with Considerable Lag;
“ “Window Dressing” ProblemsWindow Dressing” Problems
Returns-Based Measures: Returns-Based Measures: Sharpe (JPM, Sharpe (JPM, 1992)1992) Pros: Pros: Direct Observation of “Bottom Line” to Investor; Direct Observation of “Bottom Line” to Investor;
Measured More Frequently and Over Shorter Time Intervals Measured More Frequently and Over Shorter Time Intervals than Holdingsthan Holdings
Cons: Cons: Indirect Measure of Managerial Decision-MakingIndirect Measure of Managerial Decision-Making
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Model BasedModel Based::
Define a style factor model:Define a style factor model:
[1 – [1 – RR22] represents portion of return not related to style] represents portion of return not related to style
Benchmark BasedBenchmark Based::
Active Net Returns: Active Net Returns:
TE =TE = where P is the return periods per yearwhere P is the return periods per year
Returns-Based Measures of Returns-Based Measures of Investment Style ConsistencyInvestment Style Consistency
Rjt = [ bj0 + ΣbjkFkt ]+ ejt
K
K=1
Δjt = Σ xji Rjit - Rbt = Rjt - Rbt
N
i=1
σΔ√P
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Testable HypothesesTestable Hypotheses
Hypothesis #1Hypothesis #1: Style-consistent (i.e., high R: Style-consistent (i.e., high R22, low TE) funds , low TE) funds have lower portfolio turnover than style-inconsistent (i.e., have lower portfolio turnover than style-inconsistent (i.e., low Rlow R22, high TE) funds., high TE) funds.
Hypothesis #2Hypothesis #2: Style-consistent funds have higher total : Style-consistent funds have higher total and relative returns than style-inconsistent funds.and relative returns than style-inconsistent funds.
Hypothesis #3Hypothesis #3: There is a positive correlation between the : There is a positive correlation between the consistency of a fund’s investment style and the consistency of a fund’s investment style and the persistence of its future performancepersistence of its future performance
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DataData
Survivorship-bias free database of monthly returns for Survivorship-bias free database of monthly returns for domestic diversified equity funds for the period 1988-2000domestic diversified equity funds for the period 1988-2000
Morningstar style classifications (large-, mid-, small-cap; Morningstar style classifications (large-, mid-, small-cap; value, blend, growth)value, blend, growth)
Mutual Fund characteristics for the period 1991-2000 Mutual Fund characteristics for the period 1991-2000 (e.g., expense ratio, turnover, total net assets)(e.g., expense ratio, turnover, total net assets)
Require three years of prior monthly returns to be included Require three years of prior monthly returns to be included in the analysis on any given datein the analysis on any given date
No sector funds; analyze with and without index funds (i.e., No sector funds; analyze with and without index funds (i.e., active vs. passive management)active vs. passive management)
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Number of Funds withNumber of Funds withThree Years of Returns (Table Three Years of Returns (Table
1)1)
YearLargeValue
LargeBlend
LargeGrowth
MidValue
MidBlend
MidGrowth
SmallValue
SmallBlend
SmallGrowth
1991 135 163 118 60 47 79 25 29 42
1992 140 172 120 60 49 78 28 30 44
1993 156 184 126 65 54 78 31 30 49
1994 169 203 139 67 54 82 38 37 59
1995 215 245 178 69 62 106 47 52 78
1996 273 314 233 87 71 150 62 71 113
1997 350 382 297 102 99 183 79 97 152
1998 410 446 355 127 104 221 97 123 206
1999 504 584 425 167 125 289 121 147 262
2000 564 729 549 199 138 333 162 194 309
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Average Fund Characteristics: Average Fund Characteristics: 1991-20001991-2000(Table 2)(Table 2)
PeerGroup
AverageTurnover
AverageExpense
Ratio
Average Fund Firm Size ($mm)
Large Value 67.57% 1.38% 25,298
Large Blend 69.14% 1.22% 44,611
Large Growth 92.93% 1.45% 45,381
Mid Value 84.73% 1.43% 5,731
Mid Blend 79.39% 1.45% 6,782
Mid Growth 132.96% 1.55% 4,917
Small Value 61.43% 1.48% 643
Small Blend 82.17% 1.50% 1,283
Small Growth 119.89% 1.64% 1,057
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MethodologyMethodology
Use two alternative returns-based definitions of style Use two alternative returns-based definitions of style consistencyconsistency Goodness-of-fit from a multivariate factor model (i.e., RGoodness-of-fit from a multivariate factor model (i.e., R22))
Tracking error relative to peer-group specific benchmarksTracking error relative to peer-group specific benchmarks
Evaluate the impact of style consistency on performance by Evaluate the impact of style consistency on performance by using a tournament-based methodology (Brown, Harlow, using a tournament-based methodology (Brown, Harlow, Starks (JF, 1996))Starks (JF, 1996)) Relative performance within a peer group is the focusRelative performance within a peer group is the focus
Avoids the usual model specification issuesAvoids the usual model specification issues
Controls for cross-sectional differences in consistency measuresControls for cross-sectional differences in consistency measures
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MethodologyMethodology Multivariate Performance Attribution ModelMultivariate Performance Attribution Model
Factor ModelsFactor Models EGB Four Factor - Elton, Gruber and Blake (JB, 1996)EGB Four Factor - Elton, Gruber and Blake (JB, 1996) Modified EGB with Five Factors (adding EAFE factor)Modified EGB with Five Factors (adding EAFE factor) FF Three Factors - Fama and French (1993)FF Three Factors - Fama and French (1993) FFC Four Factors - Carhart (1997)FFC Four Factors - Carhart (1997)
Use RUse R22 and alpha from the model and alpha from the model
t
kt
k
t
where
R
R
=
=
=
=
=
a
b
e
. . .
. . .
the risk-adjusted excess return (alpha);
the excess return of a fund in month t;
the excess return of factor k in month t (k = 1 … N);
the beta of factor k (k = 1 … N);
the tracking error in month t;
t t t Nt tR R R R= + + + + + a b b b e1 2 . . . , N1 2
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W4500
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W4500
R2
R2 = 0.92 R2 = 0.78
Methodology (Figure 1)Methodology (Figure 1)
Examples from Multivariate Factor Model
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Methodology (Table 3)Methodology (Table 3)
Style Group Style Consistency Median R2 Median Tracking Error (%)
Large Value Low 0.86 5.23 (LV) High 0.93 3.75
Large Blend Low 0.88 4.93
(LB) High 0.96 2.85
Large Growth Low 0.83 7.44 (LG) High 0.92 4.94
Mid Value Low 0.77 7.46 (MV) High 0.87 5.07
Mid Blend Low 0.75 8.24 (MB) High 0.87 4.89
Mid Growth Low 0.80 8.72 (MG) High 0.88 5.92
Small Value Low 0.75 7.85 (SV) High 0.87 5.02
Small Blend Low 0.77 8.40 (SB) High 0.89 5.85
Small Growth Low 0.81 8.74 (SG) High 0.90 6.60
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MethodologyMethodology
Use past 36 months of data to estimate model parametersUse past 36 months of data to estimate model parameters
Evaluate performance in tournamentEvaluate performance in tournament Standardized returns within each peer group on a give date to Standardized returns within each peer group on a give date to
allow for time-series and cross-sectional poolingallow for time-series and cross-sectional pooling
Peer rankingsPeer rankings
Above median performanceAbove median performance
Roll the process forward one quarter (one year) and estimate Roll the process forward one quarter (one year) and estimate all parameters again, etc.all parameters again, etc.
Estimate Model
EvaluateTournamentPerformance
36 Months 3 Months(12 Months)
Time
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Univariate Analysis (Table 4)Univariate Analysis (Table 4)
Correlation with R²FFC Four-Factor Model
(1991-2000)
Period
Fund Turnover
Fund
Expense Ratio
Actual
Fund Return
Tournament Fund Return
Tournament
Return Ranking 1991-2000 -0.216 (0.000) -0.318 (0.000) 0.029 (0.000) 0.110 (0.000) 0.092 (0.000)
1991 -0.185 (0.000) -0.254 (0.000) 0.034 (0.411) 0.031 (0.449) 0.057 (0.170) 1992 -0.246 (0.000) -0.305 (0.000) 0.108 (0.006) 0.110 (0.006) 0.094 (0.018) 1993 -0.195 (0.000) -0.330 (0.000) -0.058 (0.128) -0.054 (0.160) -0.031 (0.417) 1994 -0.260 (0.000) -0.410 (0.000) 0.159 (0.000) 0.170 (0.000) 0.077 (0.037) 1995 -0.277 (0.000) -0.369 (0.000) 0.240 (0.000) 0.278 (0.000) 0.236 (0.000) 1996 -0.240 (0.000) -0.394 (0.000) 0.291 (0.000) 0.301 (0.000) 0.241 (0.000) 1997 -0.180 (0.000) -0.345 (0.000) 0.265 (0.000) 0.329 (0.000) 0.240 (0.000) 1998 -0.166 (0.000) -0.329 (0.000) 0.089 (0.000) 0.147 (0.000) 0.141 (0.000) 1999 -0.246 (0.000) -0.313 (0.000) -0.088 (0.000) -0.082 (0.000) -0.043 (0.058) 2000 -0.233 (0.000) -0.250 (0.000) 0.044 (0.030) 0.035 (0.083) 0.025 (0.217)
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Multivariate Analysis (Table Multivariate Analysis (Table 5A)5A)
Parameter Variable
Parameter Estimate Prob Estimate Prob
Consistency (R²)
Expense Ratio
Turnover
Assets
Intercept
Alpha
FF Three-Factor Model
FFC Four-Factor Model
0.034
0.032
(0.068)
(0.011)
0.000
0.058
0.000
0.000
0.000
0.012
1.000
0.000
0.000
0.000
0.000
0.093
1.000
0.011
0.030
0.033
(0.082)
(0.008)
0.000
0.011
3-Month Future Returns(1991-2000)
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Multivariate Analysis (Table Multivariate Analysis (Table 5B)5B)
12-Month Future Returns(1991-2000)
Parameter Variable
Parameter Estimate Prob Estimate Prob
Consistency (R²)
Expense Ratio
Turnover
Assets
Intercept
Alpha
FF Three-Factor Model
FFC Four-Factor Model
0.081
0.060
(0.134)
(0.021)
0.000
0.060
0.000
0.000
0.000
0.022
1.000
0.000
0.000
0.000
0.000
0.038
1.000
0.000
0.077
0.062
(0.145)
(0.019)
0.000
0.038
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Fama-MacBeth Fama-MacBeth Cross-Sectional AnalysisCross-Sectional Analysis
Use past 36 months of data to estimate model parametersUse past 36 months of data to estimate model parameters
Run a sequence of cross-sectional regressions of future Run a sequence of cross-sectional regressions of future performance against fund characteristics and model parameters performance against fund characteristics and model parameters (alpha and R(alpha and R2 2 ))
Average the coefficient estimates from regressions across the Average the coefficient estimates from regressions across the entire sample periodentire sample period
T-statistics based on the time-series means of the coefficientsT-statistics based on the time-series means of the coefficients
24
Fama-MacBeth Cross-Sectional Fama-MacBeth Cross-Sectional AnalysisAnalysis
(Table 6) (Table 6) 3-Month Future Returns
(1991-2000)
Parameter Variable
Parameter Estimate Prob Estimate Prob
Turnover
Assets
Expense Ratio
Alpha
Consistency (R²)
FF Three-Factor Model
FFC Four-Factor Model
0.001
(0.099)
0.018
0.087
0.067
0.970
0.000
0.030
0.000
0.000
0.970
0.000
0.030
0.029
0.000
0.001
(0.099)
0.018
0.040
0.068
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Multivariate Analysis (Table 7)Multivariate Analysis (Table 7)
Summary of Style Consistency Parameters forIndividual Style Groups
(12-Month Future Returns)
+ *** + *** + ***
+ ***
+
+ ***
+
+
+ ***
+ *** + ***+ **
+ *
+ ** _
Note: Significant at the * 10% level; ** 5% level; *** 1% level
26
Logit Analysis for Above-Median Logit Analysis for Above-Median Performance (Table 8)Performance (Table 8)
12-Month Future ReturnsFFC Four-Factor Model
(1991-2000)
Intercept
Parameter Estimate
0.005
Prob
0.788
Variable Prob
0.821
Parameter Estimate
Alpha 0.048 0.029 0.0390.0430.004
Consistency 0.115 0.000 0.0000.115
FF Three-Factor Model FFC Four-Factor Model
Assets (0.022) 0.257
Consistency*Alpha 0.008 0.548 0.0640.024
Expense Ratio (0.194) 0.000 0.000(0.200)
Turnover 0.093 0.000 0.0000.098
(0.020) 0.304
27
Probability Implications for the FFC Four-Factor Model Assuming average characteristics for expense ratio, turnover and assets
(1991-2000)
Logit Analysis for Above-Logit Analysis for Above-Median Performance (Table Median Performance (Table
9A)9A)
Consistency (RSQ):
Standard
Deviation Group -2
(Low) -1 0 +1 +2
(High) (High – Low)
-2 (Low)
0.4467
0.4631
0.4796
0.4962
0.5127
0.0660
-1
0.4453
0.4678
0.490 3
0.5129
0.5355
0.0902
0
0.4440
0.4725
0.5010
0.5296
0.5580
0.1140
+1
0.4427
0.4771
0.5118
0.5463
0.5804
0.1377
+2 (High)
0.4414
0.4818
0.5225
0.5628
0.6024
0.1610
ALPHA:
(High – Low)
-0.0053
0.0187
0.0429
0.0666
0.0897
28
Probability Implications for the FFC Four-Factor Model Assuming average characteristics turnover and assets but –2 std for expense ratio
(1991-2000)
Logit Analysis for Above-Logit Analysis for Above-Median Performance (Table Median Performance (Table
9B)9B)
Consistency (RSQ):
Standard
Deviation Group -2
(Low) -1 0 +1 +2
(High) (High – Low)
-2 (Low)
0.5464
0.5628
0.5790
0.5951
0.6110
0.0646
-1
0.5451
0.5674
0.5895
0.6111
0.6324
0.0873
0
0.5438
0.5720
0.5998
0.6269
0.6533
0.1095
+1
0.5425
0.5766
0.6100
0.6425
0.6736
0.1312
+2 (High)
0.5412
0.5812
0.6202
0.6577
0.6933
0.1522
ALPHA:
(High – Low)
-0.0053
0.0184
0.0412
0.0626
0.0824
29
Active versus PassiveActive versus Passive
Multivariate AnalysisThree-Month Future Returns
(1991-2000)
Parameter Variable
Parameter Estimate Prob Estimate Prob
All Funds
Excluding Index Funds
Intercept 0.000 1.000 1.0000.000
Consistency (R²)
Expense Ratio
Turnover
Assets
Alpha
0.030
0.033
(0.082)
(0.008)
0.011
0.000
0.000
0.000
0.093
0.011
0.000
0.000
0.000
0.124
0.010
0.030
0.034
(0.080)
(0.007)
0.012
30
Analysis using tracking error produces virtually identical resultsAnalysis using tracking error produces virtually identical results
Alternative Consistency Alternative Consistency MeasureMeasure
Tracking Error as a Measure of Style Consistency
R1000V R1000 R1000G
RMidV RMid RMidG
R2000V R2000 R2000G
31
Returns of Low and High Expense Ratio Quintiles(1991-2000)
Trading StrategiesTrading Strategies
Lo EXPR
Hi EXPR
Lo EXPR = 15.58%
Hi EXPR = 13.44%Annual Return Difference =
2.14%
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
1990
12
1991
06
1991
12
1992
06
1992
12
1993
06
1993
12
1994
06
1994
12
1995
06
1995
12
1996
06
1996
12
1997
06
1997
12
1998
06
1998
12
1999
06
1999
12
2000
06
Date
Gro
wth
of
a $1
32
Trading Strategies (Figure 2A)Trading Strategies (Figure 2A)
Annual Return Difference = 2.69%
Hi RSQ: Lo EXPR
Lo RSQ: Hi EXPR
Hi RSQ: Lo EXPR = 15.79%
Lo RSQ: Hi EXPR = 13.10%
Lo EXPR
Hi EXPR
“Consistency Premium” = 0.55%
Style Consistency Implications forReturns of Low and High Expense Ratio Quintiles
(1991-2000)
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
1990
12
1991
06
1991
12
1992
06
1992
12
1993
06
1993
12
1994
06
1994
12
1995
06
1995
12
1996
06
1996
12
1997
06
1997
12
1998
06
1998
12
1999
06
1999
12
2000
06
Date
Gro
wth
of
a $1
33
Trading StrategiesTrading StrategiesReturns of Low and High Expense Ratio and Alpha Quintiles
(1991-2000)
1990
12
1991
06
1991
12
1992
06
1992
12
1993
06
1993
12
1994
06
1994
12
1995
06
1995
12
1996
06
1996
12
1997
06
1997
12
1998
06
1998
12
1999
06
1999
12
2000
06
Date
Annual Return Difference = 3.94%
Lo EXPR: Hi ALPHA
Hi EXPR: Lo ALPHA
Lo EXPR: Hi ALPHA = 15.58%
Hi EXPR: Lo ALPHA = 11.64%
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
Gro
wth
of
a $1
34
Trading Strategies (Figure 2B)Trading Strategies (Figure 2B)
Annual Return Difference = 5.94%
Lo EXPR: Hi ALPHA
Hi EXPR: Lo ALPHA
Hi RSQ: Lo EXPR: Hi ALPHA = 16.08%
Lo RSQ: Hi EXPR: Lo ALPHA = 10.14%
Hi RSQ: Lo EXPR: Hi ALPHA
Lo RSQ: Hi EXPR: Lo ALPHA
“Consistency Premium” = 2.00%
Style Consistency Implications forReturns of Low and High Expense Ratio and Alpha Quintiles
(1991-2000)
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
1990
12
1991
06
1991
12
1992
06
1992
12
1993
06
1993
12
1994
06
1994
12
1995
06
1995
12
1996
06
1996
12
1997
06
1997
12
1998
06
1998
12
1999
06
1999
12
2000
06
Date
Gro
wth
of
a $1
35
3.07 % 0.85 % 1.89 %
2.40 % 0.54 % 0.19 %
(1.80 %) 7.16 % 4.60 %
Consistency PremiumsConsistency Premiums
Consistency Premiums by Style Groups
36
ConclusionConclusion Funds with more style consistency within a peer group tend to Funds with more style consistency within a peer group tend to
have better performance, ceteris paribus, during the sample periodhave better performance, ceteris paribus, during the sample period
Findings robust with respect to two alternative definitions of Findings robust with respect to two alternative definitions of consistency (and four factor models for one definition of consistency)consistency (and four factor models for one definition of consistency)
Results are not related to active/passive management issuesResults are not related to active/passive management issues
Style consistency effect appears to be separate from past alpha Style consistency effect appears to be separate from past alpha and expense ratios in explaining future performanceand expense ratios in explaining future performance
Results are robust within sample period and across fund typesResults are robust within sample period and across fund types
Although not reported, analysis of performance back to 1981 (not Although not reported, analysis of performance back to 1981 (not entirely survivorship-bias free) produces identical results to the entirely survivorship-bias free) produces identical results to the 1991-2000 analysis1991-2000 analysis
37
Extensions and ImplicationsExtensions and Implications
Need to Extend Analysis through 2003Need to Extend Analysis through 2003: : Same Behavior in “Down” Markets?Same Behavior in “Down” Markets?
Consistency as a “Signal” of PersistenceConsistency as a “Signal” of Persistence: : Easier to Identify Good Managers?Easier to Identify Good Managers?
Consistency and GovernanceConsistency and Governance: Manager : Manager Evaluation Relative to Peer Group; Evaluation Relative to Peer Group; Manager Compensation; Single vs. Team-Manager Compensation; Single vs. Team-Managed FundsManaged Funds
Consistency and RegulationConsistency and Regulation: Easier to : Easier to Assess Whether Fund Prospectus Assess Whether Fund Prospectus Objectives and Constraints are Satisfied?Objectives and Constraints are Satisfied?
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