1

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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Research PremiseResearch Premise

Lower Style Consistency

Does Investment Style Consistency Impact Performance?

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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

5

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)

6

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)

7

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

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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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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

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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

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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

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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

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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?