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Staying the Course: Mutual Fund Investment Style Consistency and Performance Persistence. Keith C. Brown The University of Texas W. Van Harlow Fidelity Investments Federal Reserve Bank of Atlanta Financial Markets Conference April 15, 2004. Research Premise.

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Keith c brown the university of texas w van harlow fidelity investments

Staying the Course:

Mutual Fund Investment Style Consistency

and Performance Persistence

Keith C. Brown

The University of Texas

W. Van Harlow

Fidelity Investments

Federal Reserve Bank of Atlanta Financial Markets Conference

April 15, 2004


Research premise

Research Premise

Does Investment Style Consistency Impact Performance?

Higher Style Consistency

Lower Style Consistency

Cap: Small to Large (%)

Cap: Small to Large (%)

Value to Growth (%)

Value to Growth (%)


Why style consistency might matter

Why Style Consistency Might Matter

  • Fund Outflows Due to Style Drift

    • Inability of Plan Sponsors to Identify Manager’s Style

  • Higher Consistency = Lower Turnover?

    • Possibility of Lower Transaction Costs and Expense Ratios

  • Style Timing Might be a “Loser’s Game”

    • Analog to Difficulty of Successful Tactical Asset Allocation

  • Style Consistency as a Possible “Signal” of Superior Manager Performance


Simple evidence

Higher Returns

for More

Style Consistent Funds

Large Growth

Mid Value

Mid Blend

Mid Growth

Small Value

Small Blend

Small Growth

Simple Evidence

Average

Annual Return

(1991-2000)

Peer

Group

Style

Consistency

Large Value

Lower

11.10%

Higher

13.05%

Large Blend

Lower

16.69%

Higher

20.04%

Lower

18.55%

Higher

19.86%

Lower

17.30%

Higher

13.58%

Lower

12.95%

Higher

12.86%

Lower

13.90%

Higher

15.44%

Lower

15.83%

Higher

16.65%

Lower

14.28%

Higher

15.62%

Lower

12.78%

Higher

14.21%


Complicating factors

Large Value

47.50%

45.50%

77.00%

38.00%

Large Growth

68.00%

60.50%

Mid Value

63.00%

60.00%

Mid Blend

63.00%

39.59%

Mid Growth

115.00%

76.00%

Small Value

50.00%

44.82%

84.50%

47.00%

Small Growth

89.00%

78.00%

Complicating Factors

Median Annual

Fund Return

(1991-2000)

Higher Returns

for More

Style Consistent Funds

Peer

Group

Style

Consistency

Median

Turnover

Median

Expense Ratio

Lower

11.10%

1.22%

Higher

13.05%

1.02%

Large Blend

Lower

16.69%

1.25%

Higher

20.04%

0.93%

Lower

18.55%

1.36%

Higher

19.86%

1.07%

Lower

17.30%

1.40%

Higher

13.58%

1.16%

Lower

12.95%

1.41%

Higher

12.86%

1.23%

Lower

13.90%

1.40%

Higher

15.44%

1.29%

Lower

15.83%

1.39%

Higher

16.65%

1.15%

Small Blend

Lower

14.28%

1.50%

Higher

15.62%

1.12%

Lower

12.78%

1.46%

Higher

14.21%

1.33%


Complicating factors1

Large Value

47.50%

45.50%

77.00%

38.00%

Large Growth

68.00%

60.50%

Mid Value

63.00%

60.00%

Mid Blend

63.00%

39.59%

Mid Growth

115.00%

76.00%

Small Value

50.00%

44.82%

84.50%

47.00%

Small Growth

89.00%

78.00%

Complicating Factors

Median Annual

Fund Return

(1991-2000)

Higher Returns

for More

Style Consistent Funds

Peer

Group

Style

Consistency

Median

Turnover

Median

Expense Ratio

Lower

11.10%

1.22%

Higher

13.05%

1.02%

Large Blend

Lower

16.69%

1.25%

Higher

20.04%

0.93%

Lower

18.55%

1.36%

Higher

19.86%

1.07%

Lower

17.30%

1.40%

Higher

13.58%

1.16%

Lower

12.95%

1.41%

Higher

12.86%

1.23%

Lower

13.90%

1.40%

Higher

15.44%

1.29%

Lower

15.83%

1.39%

Higher

16.65%

1.15%

Small Blend

Lower

14.28%

1.50%

Higher

15.62%

1.12%

Lower

12.78%

1.46%

Higher

14.21%

1.33%


Past literature

Past Literature

  • Investment Style Appears to Matter

    • Fund Objectives: McDonald (JFQA, 1974); Malkiel (JF, 1995)

    • Security Characteristics: Basu (JF, 1977); Banz (JFE, 1981); Fama and French (JF, 1992; JFE, 1993)

    • Style Premiums: Capaul, Rawley, Sharpe (FAJ, 1993); Lakonishok, Shleifer, Vishny (JF, 1994); Fama and French (JF, 1998); Chan and Lakonishok (FAJ, 2004); Phalippou (Working Paper, 2004)

    • Style Definitions: Roll (HES, 1995); Brown and Goetzmann (JFE, 1997)

    • Style Rotation: Barberis and Shleifer (JFE, 2003)

  • Fund Performance Persistence

    • Classic Study: Jensen (JF, 1968)

    • Hot & Icy Hands: Grinblatt and Titman (JF, 1992); Hendricks, Patel, Zeckhauser (JF, 1993); Brown and Goetzmann (JF, 1995); Elton, Gruber, Blake (JB, 1996), Ibbotson and Patel (Working Paper, 2002)

    • Accounting for Momentum: Jegadeesh and Titman (JF, 1993); Carhart (JF, 1997); Wermers (2001)

    • Conditioning Information: Ferson and Schadt (JF, 1996), Christopherson, Ferson, and Glassman (RFS, 1998)

    • Persistence & Style: Bogle (JPM, 1998); Teo and Woo (JFE, forthcoming)


Keith c brown the university of texas w van harlow fidelity investments

Research Design

Does Style Consistency Impact Performance?

  • Use alternative definitions of style consistency

  • Control for other factors affecting performance

    • Alpha persistence

    • Expense ratio

    • Turnover

    • Fund size

    • Active/passive management


Measuring investment style style consistency two approaches

Measuring Investment Style & Style Consistency: Two Approaches

  • Holdings-Based Measures: Daniel, Grinblatt, Titman, and Wermers (JF, 1997)

    • Pros: Direct Assessment of Manager’s Selection and Timing Skills; Benchmark Construction Around Security Characteristics

    • Cons: Unobservable or Observed with Considerable Lag;

      “Window Dressing” Problems

  • Returns-Based Measures: Sharpe (JPM, 1992)

    • Pros: Direct Observation of “Bottom Line” to Investor; Measured More Frequently and Over Shorter Time Intervals than Holdings

    • Cons: Indirect Measure of Managerial Decision-Making


Returns based measures of investment style consistency

K

Rjt = [ bj0+ ΣbjkFkt ]+ ejt

K=1

N

Δjt = ΣxjiRjit - Rbt = Rjt -Rbt

i=1

Returns-Based Measures of Investment Style Consistency

  • Model Based:

    • Define a style factor model:

      [1 – R2] represents portion of return not related to style

  • Benchmark Based:

    • Active Net Returns:

      TE =

      where P is the return periods per year

σΔ√P


Testable hypotheses

Testable Hypotheses

  • Hypothesis #1: Style-consistent (i.e., high R2, low TE) funds have lower portfolio turnover than style-inconsistent (i.e., low R2, high TE) funds.

  • Hypothesis #2: Style-consistent funds have higher total and relative returns than style-inconsistent funds.

  • Hypothesis #3: There is a positive correlation between the consistency of a fund’s investment style and the persistence of its future performance


Keith c brown the university of texas w van harlow fidelity investments

Data

  • Survivorship-bias free database of monthly returns for domestic diversified equity funds for the period 1988-2000

  • Morningstar style classifications (large-, mid-, small-cap; value, blend, growth)

  • Mutual Fund characteristics for the period 1991-2000 (e.g., expense ratio, turnover, total net assets)

  • Require three years of prior monthly returns to be included in the analysis on any given date

  • No sector funds; analyze with and without index funds (i.e., active vs. passive management)


Number of funds with three years of returns table 1

Number of Funds withThree Years of Returns (Table 1)

Large

Growth

Mid

Value

Mid

Blend

Mid

Growth

Small

Value

Small

Blend

Small

Growth

Large

Blend

Large

Value

Year

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


Average fund characteristics 1991 2000 table 2

Average Fund Characteristics: 1991-2000(Table 2)

Average

Fund Firm

Size ($mm)

Average

Expense

Ratio

Peer

Group

Average

Turnover

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


Keith c brown the university of texas w van harlow fidelity investments

Methodology

  • Use two alternative returns-based definitions of style consistency

    • Goodness-of-fit from a multivariate factor model (i.e., R2)

    • Tracking error relative to peer-group specific benchmarks

  • Evaluate the impact of style consistency on performance by using a tournament-based methodology (Brown, Harlow, Starks (JF, 1996))

    • Relative performance within a peer group is the focus

    • Avoids the usual model specification issues

    • Controls for cross-sectional differences in consistency measures


Methodology

=

+

b

+

b

+

+

b

+

,

. . .

a

e

R

R

R

R

t

1

t

2

t

Nt

t

1

2

N

where

a

=

the risk-adjusted excess return (alpha);

=

the excess return of a fund in month t;

R

t

=

the excess return of factor k in month t (k = 1 … N);

. . .

R

kt

=

the beta of factor k (k = 1 … N);

b

. . .

k

=

the tracking error in month t;

e

t

Methodology

  • Multivariate Performance Attribution Model

  • Factor Models

    • EGB Four Factor - Elton, Gruber and Blake (JB, 1996)

    • Modified EGB with Five Factors (adding EAFE factor)

    • FF Three Factors - Fama and French (1993)

    • FFC Four Factors - Carhart (1997)

  • Use R2 and alpha from the model


Keith c brown the university of texas w van harlow fidelity investments

Methodology (Figure 1)

Examples from Multivariate Factor Model

R2 = 0.92

R2 = 0.78

Cap: Small to Large (%)

Cap: Small to Large (%)

Value to Growth (%)

Value to Growth (%)


Methodology table 3

Methodology (Table 3)


Methodology1

Methodology

Evaluate

Tournament

Performance

Estimate Model

Time

3 Months

(12 Months)

36 Months

  • Use past 36 months of data to estimate model parameters

  • Evaluate performance in tournament

    • Standardized returns within each peer group on a give date to allow for time-series and cross-sectional pooling

    • Peer rankings

    • Above median performance

  • Roll the process forward one quarter (one year) and estimate all parameters again, etc.


Keith c brown the university of texas w van harlow fidelity investments

Univariate Analysis (Table 4)

Fund

Actual

Tournament

Tournament

Period

Fund Turnover

Expense Ratio

Fund Return

Fund Return

Return Ranking

1991

-

2000

-

0.216

-

0.318

0.029

0.110

0.092

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

1991

-

0.185

-

0.254

0.034

0.031

0.057

(0.000)

(0.000)

(0.411)

(0.449)

(0.170)

1992

-

0.246

-

0.305

0.108

0.110

0.094

(0.000)

(0.000)

(0.006)

(0.006)

(0.018)

1993

-

0.195

-

0.330

-

0.058

-

0.054

-

0.031

(0.000)

(0.000)

(0.128)

(0.160)

(0.417)

1994

-

0.260

-

0.410

0.159

0.170

0.077

(0.000)

(0.000)

(0.

000)

(0.000)

(0.037)

1995

-

0.277

-

0.369

0.240

0.278

0.236

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

1996

-

0.240

-

0.394

0.291

0.301

0.241

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

1997

-

0.180

-

0.345

0.265

0.

329

0.240

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

1998

-

0.166

-

0.329

0.089

0.147

0.141

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

1999

-

0.246

-

0.313

-

0.088

-

0.082

-

0.043

(0.000)

(0.000)

(0.000)

(0.000)

(0.058)

2000

-

0.233

-

0.250

0.044

0.035

0.025

(0.000)

(0.000)

(0.030)

(0.083)

(0.217)

Correlation with R²

FFC Four-Factor Model

(1991-2000)


Keith c brown the university of texas w van harlow fidelity investments

Multivariate Analysis (Table 5A)

3-Month Future Returns

(1991-2000)

FFC Four-Factor Model

FF Three-Factor Model

Parameter

Parameter

Prob

Prob

Estimate

Estimate

Variable

Intercept

0.000

1.000

0.000

1.000

Alpha

0.058

0.000

0.011

0.011

Consistency (R²)

0.034

0.000

0.030

0.000

Turnover

0.032

0.000

0.033

0.000

Expense Ratio

(0.068)

0.000

(0.082)

0.000

Assets

(0.011)

0.012

(0.008)

0.093


Keith c brown the university of texas w van harlow fidelity investments

Multivariate Analysis (Table 5B)

12-Month Future Returns

(1991-2000)

FFC Four-Factor Model

FF Three-Factor Model

Parameter

Parameter

Prob

Prob

Estimate

Estimate

Variable

Intercept

0.000

1.000

0.000

1.000

Alpha

0.060

0.000

0.038

0.000

Consistency (R²)

0.081

0.000

0.077

0.000

Turnover

0.060

0.000

0.062

0.000

Expense Ratio

(0.134)

0.000

(0.145)

0.000

Assets

(0.021)

0.022

(0.019)

0.038


Fama macbeth cross sectional analysis

Fama-MacBeth Cross-Sectional Analysis

  • Use past 36 months of data to estimate model parameters

  • Run a sequence of cross-sectional regressions of future performance against fund characteristics and model parameters (alpha and R2 )

  • Average the coefficient estimates from regressions across the entire sample period

  • T-statistics based on the time-series means of the coefficients


Keith c brown the university of texas w van harlow fidelity investments

Fama-MacBeth Cross-Sectional Analysis(Table 6)

3-Month Future Returns

(1991-2000)

FFC Four-Factor Model

FF Three-Factor Model

Parameter

Parameter

Prob

Prob

Estimate

Estimate

Variable

Alpha

0.087

0.000

0.040

0.029

Consistency (R²)

0.067

0.000

0.068

0.000

Turnover

0.001

0.970

0.001

0.970

Expense Ratio

(0.099)

0.000

(0.099)

0.000

Assets

0.018

0.030

0.018

0.030


Keith c brown the university of texas w van harlow fidelity investments

Multivariate Analysis (Table 7)

Summary of Style Consistency Parameters for

Individual Style Groups

(12-Month Future Returns)

+ ***

+

+ ***

+ *

_

+ ***

+ ***

+ ***

+

+ **

+

+ ***

+ ***

+ **

+ ***

Note: Significant at the * 10% level; ** 5% level; *** 1% level


Keith c brown the university of texas w van harlow fidelity investments

Logit Analysis for Above-Median Performance (Table 8)

12-Month Future Returns

FFC Four-Factor Model

(1991-2000)

FF Three-Factor Model

FFC Four-Factor Model

Parameter

Parameter

Prob

Variable

Estimate

Prob

Estimate

Intercept

0.005

0.788

0.004

0.821

Alpha

0.048

0.029

0.043

0.039

Consistency

0.115

0.000

0.115

0.000

Turnover

0.093

0.000

0.098

0.000

Expense Ratio

(0.194)

0.000

(0.200)

0.000

(0.020)

0.304

Assets

(0.022)

0.257

Consistency*Alpha

0.008

0.548

0.024

0.064


Keith c brown the university of texas w van harlow fidelity investments

Logit Analysis for Above-Median Performance (Table 9A)

Probability Implications for the FFC Four-Factor Model

Assuming average characteristics for expense ratio, turnover and assets

(1991-2000)

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

ALPHA:

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

(High

-

0.0053

0.0187

0.0429

0.0666

0.0897

Low)


Keith c brown the university of texas w van harlow fidelity investments

Logit Analysis for Above-Median Performance (Table 9B)

Probability Implications for the FFC Four-Factor Model

Assuming average characteristics turnover and assets but –2 std for expense ratio

(1991-2000)

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

ALPHA:

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

(High

-

0.0053

0.0184

0.0412

0.0626

0.0824

Low)


Keith c brown the university of texas w van harlow fidelity investments

Active versus Passive

Alpha

0.011

0.011

0.012

0.010

Consistency (R²)

0.030

0.000

0.030

0.000

Turnover

0.033

0.000

0.034

0.000

Expense Ratio

(0.082)

0.000

(0.080)

0.000

Assets

(0.008)

0.093

(0.007)

0.124

Multivariate Analysis

Three-Month Future Returns

(1991-2000)

Excluding Index Funds

All Funds

Parameter

Parameter

Prob

Prob

Estimate

Estimate

Variable

Intercept

0.000

1.000

0.000

1.000


Keith c brown the university of texas w van harlow fidelity investments

Alternative Consistency Measure

R1000G

R1000

R1000V

RMidG

RMid

RMidV

R2000G

R2000

R2000V

Tracking Error as a Measure of Style Consistency

  • Analysis using tracking error produces virtually identical results


Keith c brown the university of texas w van harlow fidelity investments

Trading Strategies

Returns of Low and High Expense Ratio Quintiles

(1991-2000)

5.00

4.50

Lo EXPR

4.00

Lo EXPR = 15.58%

Hi EXPR = 13.44%

Hi EXPR

3.50

Annual Return Difference = 2.14%

Growth of a $1

3.00

2.50

2.00

1.50

1.00

199012

199106

199112

199206

199212

199306

199312

199406

199412

199506

199512

199606

199612

199706

199712

199806

199812

199906

199912

200006

Date


Keith c brown the university of texas w van harlow fidelity investments

Trading Strategies (Figure 2A)

Style Consistency Implications for

Returns of Low and High Expense Ratio Quintiles

(1991-2000)

5.00

Hi RSQ: Lo EXPR

4.50

Lo EXPR

4.00

Hi RSQ: Lo EXPR = 15.79%

Lo RSQ: Hi EXPR = 13.10%

Hi EXPR

3.50

Lo RSQ: Hi EXPR

Annual Return Difference = 2.69%

Growth of a $1

3.00

2.50

2.00

“Consistency Premium” = 0.55%

1.50

1.00

199012

199106

199112

199206

199212

199306

199312

199406

199412

199506

199512

199606

199612

199706

199712

199806

199812

199906

199912

200006

Date


Keith c brown the university of texas w van harlow fidelity investments

Trading Strategies

5.00

4.50

Lo EXPR: Hi ALPHA

4.00

Lo EXPR: Hi ALPHA = 15.58%

Hi EXPR: Lo ALPHA = 11.64%

3.50

Annual Return Difference = 3.94%

Hi EXPR: Lo ALPHA

Growth of a $1

3.00

2.50

2.00

1.50

1.00

Returns of Low and High Expense Ratio and Alpha Quintiles

(1991-2000)

199012

199106

199112

199206

199212

199306

199312

199406

199412

199506

199512

199606

199612

199706

199712

199806

199812

199906

199912

200006

Date


Keith c brown the university of texas w van harlow fidelity investments

Trading Strategies (Figure 2B)

Style Consistency Implications for

Returns of Low and High Expense Ratio and Alpha Quintiles

(1991-2000)

5.00

Hi RSQ: Lo EXPR: Hi ALPHA

4.50

Lo EXPR: Hi ALPHA

Hi RSQ: Lo EXPR: Hi ALPHA = 16.08%

Lo RSQ: Hi EXPR: Lo ALPHA = 10.14%

4.00

3.50

Annual Return Difference = 5.94%

Hi EXPR: Lo ALPHA

Growth of a $1

3.00

2.50

Lo RSQ: Hi EXPR: Lo ALPHA

2.00

1.50

“Consistency Premium” = 2.00%

1.00

199012

199106

199112

199206

199212

199306

199312

199406

199412

199506

199512

199606

199612

199706

199712

199806

199812

199906

199912

200006

Date


Keith c brown the university of texas w van harlow fidelity investments

Consistency Premiums

Consistency Premiums by Style Groups

1.89 %

0.85 %

3.07 %

0.19 %

0.54 %

2.40 %

4.60 %

7.16 %

(1.80 %)


Keith c brown the university of texas w van harlow fidelity investments

Conclusion

  • Funds with more style consistency within a peer group tend to have better performance, ceteris paribus, during the sample period

    • Findings robust with respect to two alternative definitions of consistency (and four factor models for one definition of consistency)

    • Results are not related to active/passive management issues

  • Style consistency effect appears to be separate from past alpha and expense ratios in explaining future performance

  • Results are robust within sample period and across fund types

  • Although not reported, analysis of performance back to 1981 (not entirely survivorship-bias free) produces identical results to the 1991-2000 analysis


Extensions and implications

Extensions and Implications

  • Need to Extend Analysis through 2003: Same Behavior in “Down” Markets?

  • Consistency as a “Signal” of Persistence: Easier to Identify Good Managers?

  • Consistency and Governance: Manager Evaluation Relative to Peer Group; Manager Compensation; Single vs. Team-Managed Funds

  • Consistency and Regulation: Easier to Assess Whether Fund Prospectus Objectives and Constraints are Satisfied?


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