1. 0 Keith C. Brown The University of Texas W. Van Harlow Fidelity Investments Federal Reserve Bank of Atlanta Financial Markets Conference April 15, 2004 Staying the Course: Mutual Fund Investment Style Consistency and Performance Persistence

2. 1 Research Premise Lower Style Consistency Does Investment Style Consistency Impact Performance? Cap: Small to Large (%) Value to Growth (%) Cap: Small to Large (%) Value to Growth (%) Higher Style Consistency

3. 2 Why Style Consistency Might Matter Fund Outflows Due to Style Drift Fund Outflows Due to Style Drift  Inability of Plan Sponsors to Identify Manager’s Style Higher Consistency = Lower Turnover? Higher Consistency = Lower Turnover?  Possibility 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 Allocation Style Consistency as a Possible “Signal” of Superior Manager Performance Style Consistency as a Possible “Signal” of Superior Manager Performance

4. 3 Peer Group Style Consistency Average Annual Return (1991-2000) Lower11.10%Large Value Higher13.05% Large BlendLower16.69% Higher20.04% Lower18.55%Large Growth Higher19.86% Lower17.30%Mid Value Higher13.58% Lower12.95%Mid Blend Higher12.86% Lower13.90%Mid Growth Higher15.44% Lower15.83%Small Value Higher16.65% Lower14.28%Small Blend Higher15.62% Lower12.78%Small Growth Higher14.21% Higher Returns for More Style Consistent Funds Simple Evidence

5. 4 Complicating Factors Peer Group Style Consistency Median Turnover Median Expense Ratio Lower11.10%1.22%Large Value Higher13.05%1.02% Large BlendLower16.69%1.25% Higher20.04%0.93% Lower18.55%1.36%Large Growth Higher19.86%1.07% Lower17.30%1.40%Mid Value Higher13.58%1.16% Lower12.95%1.41%Mid Blend Higher12.86%1.23% Lower13.90%1.40%Mid Growth Higher15.44%1.29% Lower15.83%1.39%Small Value Higher16.65%1.15% Small BlendLower14.28%1.50% Higher15.62%1.12% Lower12.78%1.46%Small Growth Higher14.21% 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 Annual Fund Return (1991-2000)

6. 5 Complicating Factors Peer Group Style Consistency Median Turnover Median Expense Ratio Lower11.10%1.22%Large Value Higher13.05%1.02% Large BlendLower16.69%1.25% Higher20.04%0.93% Lower18.55%1.36%Large Growth Higher19.86%1.07% Lower17.30%1.40%Mid Value Higher13.58%1.16% Lower12.95%1.41%Mid Blend Higher12.86%1.23% Lower13.90%1.40%Mid Growth Higher15.44%1.29% Lower15.83%1.39%Small Value Higher16.65%1.15% Small BlendLower14.28%1.50% Higher15.62%1.12% Lower12.78%1.46%Small Growth Higher14.21% 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 Annual Fund Return (1991-2000)

7. 6 Past Literature Investment Style Appears to Matter 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 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)

8. 7 Research Design Use alternative definitions of style consistency Use alternative definitions of style consistency Control for other factors affecting performance Control for other factors affecting performance  Alpha persistence  Expense ratio  Turnover  Fund size  Active/passive management Does Style Consistency Impact Performance?

9. 8 Measuring Investment Style & Style Consistency: Two Approaches Holdings-Based Measures: Daniel, Grinblatt, Titman, and Wermers (JF, 1997) 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 “Window Dressing” Problems Returns-Based Measures: Sharpe (JPM, 1992) 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

10. 9 Model Based : Model Based :  Define a style factor model: [1 – R 2 ] represents portion of return not related to style Benchmark Based : Benchmark Based :  Active Net Returns: TE = where P is the return periods per year where P is the return periods per year Returns-Based Measures of Investment Style Consistency R jt = [ b j0 + Σ b jk F kt ] + e jt K K=1 Δ jt = Σ x ji R jit - R bt = R jt - R bt N i=1 σΔ√PσΔ√P

11. 10 Testable Hypotheses Hypothesis #1 : Style-consistent (i.e., high R 2, low TE) funds have lower portfolio turnover than style-inconsistent (i.e., low R 2, high TE) funds. Hypothesis #1 : Style-consistent (i.e., high R 2, low TE) funds have lower portfolio turnover than style-inconsistent (i.e., low R 2, high TE) funds. Hypothesis #2 : Style-consistent funds have higher total and relative returns than style-inconsistent 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 Hypothesis #3 : There is a positive correlation between the consistency of a fund’s investment style and the persistence of its future performance

12. 11 Data Survivorship-bias free database of monthly returns for domestic diversified equity funds for the period 1988-2000 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) 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) 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 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) No sector funds; analyze with and without index funds (i.e., active vs. passive management)

13. 12 Number of Funds with Three Years of Returns (Table 1) Year Large Value Large Blend Large Growth Mid Value Mid Blend Mid Growth Small Value Small Blend Small Growth 1991135163118604779252942 1992140172120604978283044 1993156184126655478313049 1994169203139675482383759 19952152451786962106475278 199627331423387711506271113 1997350382297102991837997152 199841044635512710422197123206 1999504584425167125289121147262 2000564729549199138333162194309

14. 13 Average Fund Characteristics: 1991-2000 (Table 2) Peer Group Average Turnover Average Expense Ratio Average Fund Firm Size ($mm) Large Value67.57%1.38%25,298 Large Blend69.14%1.22%44,611 Large Growth92.93%1.45%45,381 Mid Value84.73%1.43%5,731 Mid Blend79.39%1.45%6,782 Mid Growth132.96%1.55%4,917 Small Value61.43%1.48%643 Small Blend82.17%1.50%1,283 Small Growth119.89%1.64%1,057

15. 14 Methodology Use two alternative returns-based definitions of style consistency Use two alternative returns-based definitions of style consistency  Goodness-of-fit from a multivariate factor model (i.e., R 2 )  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)) 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

16. 15 Methodology Multivariate Performance Attribution Model Multivariate Performance Attribution Model Factor Models 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 R 2 and alpha from the model Use R 2 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; tttNt t RRRR =+++++ a bbb e 12..., N 12

17. 16 R 2 = 0.92 R 2 = 0.78 Methodology (Figure 1) Examples from Multivariate Factor Model Cap: Small to Large (%) Value to Growth (%) Cap: Small to Large (%) Value to Growth (%)

18. 17 Methodology (Table 3)

19. 18Methodology Use past 36 months of data to estimate model parameters Use past 36 months of data to estimate model parameters Evaluate performance in tournament 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. Roll the process forward one quarter (one year) and estimate all parameters again, etc. Estimate Model Evaluate Tournament Performance 36 Months 3 Months (12 Months) Time

20. 19 Univariate Analysis (Table 4) Correlation with R² FFC 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)

21. 20 Multivariate Analysis (Table 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 0.012 1.000 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)

22. 21 Multivariate Analysis (Table 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 0.022 1.000 0.000 0.038 1.000 0.000 0.077 0.062 (0.145) (0.019) 0.000 0.038

23. 22 Fama-MacBeth Cross-Sectional Analysis Use past 36 months of data to estimate model parameters 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 R 2 ) Run a sequence of cross-sectional regressions of future performance against fund characteristics and model parameters (alpha and R 2 ) Average the coefficient estimates from regressions across the entire sample period Average the coefficient estimates from regressions across the entire sample period T-statistics based on the time-series means of the coefficients T-statistics based on the time-series means of the coefficients

24. 23 Fama-MacBeth Cross-Sectional Analysis (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 0.970 0.000 0.030 0.029 0.000 0.001 (0.099) 0.018 0.040 0.068

25. 24 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

26. 25 Logit Analysis for Above-Median Performance (Table 8) 12-Month Future Returns FFC Four-Factor Model (1991-2000) Intercept Parameter Estimate 0.005 Prob 0.788 Variable Prob 0.821 Parameter Estimate Alpha0.0480.0290.0390.043 0.004 Consistency0.1150.000 0.115 FF Three-Factor ModelFFC Four-Factor Model Assets(0.022)0.257 Consistency*Alpha0.0080.5480.0640.024 Expense Ratio(0.194)0.000 (0.200) Turnover0.0930.000 0.098 (0.020)0.304

27. 26 Probability Implications for the FFC Four-Factor Model Assuming average characteristics for expense ratio, turnover and assets (1991-2000) Logit Analysis for Above-Median Performance (Table 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 0.4903 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. 27 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-Median Performance (Table 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. 28 Active versus Passive Active versus Passive Multivariate Analysis Three-Month Future Returns (1991-2000) Parameter Variable Parameter Estimate Prob Estimate Prob All Funds Excluding Index Funds Intercept0.0001.000 0.000 Consistency (R²) Expense Ratio Turnover Assets Alpha 0.030 0.033 (0.082) (0.008) 0.011 0.000 0.093 0.011 0.000 0.124 0.010 0.030 0.034 (0.080) (0.007) 0.012

30. 29 Analysis using tracking error produces virtually identical results Analysis using tracking error produces virtually identical results Alternative Consistency Measure Tracking Error as a Measure of Style Consistency R1000V R1000 R1000G RMidV RMid RMidG R2000V R2000 R2000G

31. 30 Returns of Low and High Expense Ratio Quintiles (1991-2000) Trading 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 199012199106199112199206199212199306199312199406199412199506199512199606199612199706199712199806199812199906199912200006 Date Growth of a $1

32. 31 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 for Returns 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 199012199106199112199206199212199306199312199406199412199506199512199606199612199706199712199806199812199906199912200006 Date Growth of a $1

33. 32 Trading Strategies Returns of Low and High Expense Ratio and Alpha Quintiles (1991-2000) 199012199106199112199206199212199306199312199406199412199506199512199606199612199706199712199806199812199906199912200006 Date

34. 33 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 for Returns 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 199012199106199112199206199212199306199312199406199412199506199512199606199612199706199712199806199812199906199912200006 Date Growth of a $1

35. 34 3.07 % 0.85 % 1.89 % 2.40 % 0.54 % 0.19 % (1.80 %) 7.16 % 4.60 % Consistency Premiums Consistency Premiums by Style Groups

36. 35 Conclusion Funds with more style consistency within a peer group tend to have better performance, ceteris paribus, during the sample period 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 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 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 Although not reported, analysis of performance back to 1981 (not entirely survivorship-bias free) produces identical results to the 1991-2000 analysis

37. 36 Extensions and Implications Need to Extend Analysis through 2003: Same Behavior in “Down” Markets? Need to Extend Analysis through 2003: Same Behavior in “Down” Markets? Consistency as a “Signal” of Persistence: Easier to Identify Good Managers? 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 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? Consistency and Regulation: Easier to Assess Whether Fund Prospectus Objectives and Constraints are Satisfied?