Persistence performance

International Research Journal of Finance and Economics ISSN 1450-2887 Issue 34 (2009) © EuroJournals Publishing, Inc. 2009 http://www.eurojournals.com/finance.htm

Do Hot Hands Warm the Mutual Fund Investor? The Myth of

Performance Persistence Phenomenon

Eero J. Pätäri School of Business, Lappeenranta University of Technology

P.O. Box 20, FIN-53851 Lappeenranta, Finland E-mail: [email protected]

Tel: +358 5621 7220; Fax: +358 5621 7299

Abstract

This paper provides an extensive literature review of performance persistence of open-end mutual funds and synthesizes the main findings of the previous studies into the aggregate wisdom that may be useful for both scholars in planning the research design for their studies and practitioners in structuring mutual fund portfolio for their clients. The comparative analysis of previous studies reveals that the systematic prediction power of past performance is strongly sample-dependent although short-term persistence in performance is documented quite often. Moreover, conventional test procedures employed in performance persistence studies are subject to many biases that may induce spurious consistency in performance. Especially in case of equity funds, results are often sensitive to methodological choices. Keywords: Mutual funds; Performance persistence; Mutual fund performance JEL Classification Codes: G20; G23

1. Introduction Performance persistence has been the most popular topic in the mutual fund literature both in the 1990s and in the third millennium. The persistence studies has focused on the issue whether it is possible to predict future performance by using past performance records. The topic is very central from the viewpoint of the entire performance measurement industry since if the past performance had no prediction power over future performance the data collecting and ex post performance evaluation would be a useless procedure from the investor’s standpoint. The only value that past performance records might in this case have would be in evaluating the success of portfolio manager. However, firing or recruiting a manager based on past performance would be groundless if past performance told nothing about future performance. Nevertheless, the performance measurement industry is growing all the time along with mutual fund markets. Companies like Morningstar and Lipper have started their business by publishing mutual fund rankings, and performance reviews are regularly published in Barron’s, Business Week, Forbes and the Wall Street Journal. Before recommending portfolio managers to the clients pension plan consultants closely examine past performance of managed portfolios. Track record of successful portfolio managers are also used in fund marketing and several scholars have documented that historical performance is the predominant criterion in fund selection (e.g., see Ippolito, 1992; Sirri and Tufano, 1993; Patel et al., 1994, Gruber, 1996; Goetzmann and Peles 1997; Edelen, 1999; Bergstresser and Poterba, 2002; Deaves, 2004; and Busse and Irvine, 2006). It

International Research Journal of Finance and Economics - Issue 34 (2009) 118

seems that everyone choosing active managers, from pension plan sponsors to individual investors, put some weight on past performance in portfolio selection.

However, the scholars do not agree on the added-value of the performance evaluation industry for the community of investors; plenty of studies have found evidence of performance persistence but there are almost as many studies that have not found it. The topic has fascinated scholars because the existence of performance persistence would question not only the weak form efficiency of capital markets, but also that of mutual fund markets. This would imply that abnormal profits over random fund selection might be earned on the basis of past performance records.

This paper provides the extensive review to the literature of mutual fund performance persistence from the very first pioneer studies till the most recent advances in tracking performance persistence. To my knowledge, this is the most comprehensive literature review ever made of the persistence studies. Besides a review this paper discusses potential explanations for inconsistent findings of the abundant literature on performance persistence. Also, the time-varying trends of the persistence literature are presented. This kind of review of the “lessons learned” from the previous persistence studies may help scholars to improve the research design and hopefully, also the validity of the forthcoming studies. Also the investment practitioners can exploit the conclusions in their decisions on mutual fund selection.

Numerous studies that examine performance persistence of institutional portfolios of other types, such as pension funds, hedge funds, publicly offered commodity funds, and REIT funds have also been published in the financial journals. For the sake of proliferation of the overall performance persistence literature, this paper focuses on relative performance persistence of common open-end mutual funds. 2. The Pioneer Studies of Performance Persistence The issue of performance persistence is discussed already in the seminal mutual fund studies. The distinctive feature of the earlier studies is the use of long selection period and typically holding period of the same length (see Table 1). Sharpe (1966) compares the performance rank orders based on the Sharpe Ratios of two successive decades and finds positive though not statistically significant correlation. He also uses the rankings of funds based on the Treynor Ratio computed from the earlier period data to predict rankings based on the Sharpe Ratio of the later period but the results remain the same.

Jensen (1968) uses the same lengths of both selection and holding period as Sharpe, but examines the persistence of abnormal performance determined by the Jensen Alpha. He finds positive correlation in the performance between the selection period and the holding period indicating that some funds may be consistently inferior and others consistently superior. However, Jensen emphasizes that one must be very careful in interpreting these results so that a fund manager who experienced superior performance in the earlier period would be far more likely to experience superior results in the latter period. He notes further that positive correlation between these two periods is mainly due to persistence of inferior performance.

Carlson (1970) analyzes performance persistence of 57 mutual funds on the basis of the sample data from the time-period of 1948-1967. Splitting this two-decade data like Sharpe and Jensen, he finds that the interdecade rankings based on the Sharpe Ratio show no evidence of persistence though rankings based on total return or risk (volatility) do so. As a consequence of his findings that broadly defined investment objectives might influence performance measurement, Carlson (1970) examines also smaller sample of 33 funds consisting only of common stock funds but the main results do not change. Despite the lack of overall consistency in rankings based on the Sharpe Ratio, there appears to be a slight tendency for funds to remain either in the top or bottom quartiles during both decades. Carlson further divides each decade into two five-year periods: In general, these five-year rankings based on the Sharpe Ratio improve dramatically the predictive power of past performance compared to

119 International Research Journal of Finance and Economics - Issue 34 (2009)

ten-year rankings. Also for the observation period of this length, intraquartile statistics shows a strong tendency for funds to remain within top or bottom groupings.

Sarnat (1972) examines the performance persistence of 56 mutual funds viewing the size of the efficient sets generated by the four alternative decision criteria including mean-variance criterion. Using the length of 12 years for both selection period and holding period he concludes that the composition of the efficient sets over time is not stable enough to benefit an investor economically. Kritzman (1983) analyzes the performance persistence of 32 Bell System’s fixed-income funds on the basis of total returns from two successive five-year periods and finds no relationship between past and future performance even among very best and very worst funds.

Levy and Sarnat (1984) use the same type of the efficient set approach as Sarnat (1972). Using the data on mutual fund returns for the subperiods of 11 years (1959-69 and 1970-80) the authors conclude, parallel to the results of Sarnat (1972), that the composition of the efficient sets over time is not stable enough to derive predictions materially better than simple random choice.

As a part of larger mutual fund performance study Lehmann and Modest (1987) examine the persistence of fund rankings based on various performance measures (i.e., Treynor & Black (1973) Appraisal Ratios1, alphas based on both the CAPM model and several applications of the APT models, and in addition, total returns) for the 15-year period divided further into three 5-year subperiods. The study of Lehmann and Modest (1987) can be considered one of the cornerstone studies of mutual fund performance evaluation, since this is the first time when multifactor models are used as the basis of performance measurement. Although evidence of persistence is found, the authors note that results are highly dependent on performance metrics employed; the results show considerable differences between rankings based on the CAPM model and those based on various applications of the APT model. Moreover, substantial ranking differences occur also within alternative APT implementations. Lehmann and Modest (1987) stress the need to find a set of benchmarks that represent the common factors determining fund returns.

1 The Appraisal Ratio is calculated by dividing the Jensen alpha by the nonsystematic risk of that portfolio, i.e., the

standard deviation of the residual term of the regression equation. Also known as the information ratio (e.g., see Grinold & Kahn, 1995, p. 90), it measures abnormal return per unit of risk that in principle could be diversified away by holding a market portfolio (Bodie et al., 2005, p. 868).


Table 1: Performance persistence studies of the 1966–1989 period Table 1 summarizes the main findings of the studies of mutual fund performance persistence published during the 1966-1989 time period. The common characteristic of the studies of this era is the use of relatively long selection and holding periods. Noteworthy is also that strongest evidence of persistence is found systematically in the studies employing shorter selection and/or holding periods.

Authors Method for

performance evaluation

Type of funds and size of

sample

Time period

Length of selection period

Length of holding period

Results

Sharpe 1966 Sharpe RatioTreynor Ratio for SPa/Sharpe Ratio for HPb

34 mutual funds 1944–1963 10 years 10 years weak evidence of persistence

Jensen 1968 Jensen Alpha 115 mutual funds 1945–1964 10 years 10 years weak evidence of persistence

57 mutual funds 10 years 10 years no persistence based on risk-adj. performance metrics Carlson 1970

Treynor Ratio for SP/Sharpe Ratio for HP Sharpe Ratio 33 equity funds

1948–19675 years 5 years significant persistence

Sarnat 1972 efficient set approach 56 mutual funds 1946–1969 12 years 12 years

no economically exploitable persistence (no improvement compared to the random choice selection)

Levy & Sarnat 1984 efficient set approach 100 mutual funds 1959–1980 11 years 11 years

the composition of efficient sets not better than that based on random choice

Lehmann & Modest 1987

Appraisal Ratios, Jensen Alpha & several APT alphas

130 mutual funds 1968–1982 5 years 5 years evidence of persistence but results are sensitive to performance metrics

Levy & Lerman 1988 efficient set approach 100 mutual funds 1959–1980 11 years 1–11 years

persistence when using MVRc, SSDRd, or TSDRe criteria (riskless asset included)

a SP refers to selection period b HP refers to holding period c MVR refers to mean-variance efficiency criterion with riskless asset d SSDR refers to the second degree stochastic dominance efficiency criterion with riskless asset e TSDR refers to the third degree stochastic dominance efficiency criterion with riskless asset

Using the same data as Levy and Sarnat (1984) Levy and Lerman (1988) extend the work of the formers to test the predictive power of investment decision criteria that use also information about the riskless asset. While keeping the selection period always at the 11 years, Levy and Lerman vary the length of the holding period from a maximum of eleven years for entry in 12th year to one year for the ultimate year entry. Generally, the results indicate that there is a definite value to using ex post information for ex ante portfolio selection, when the selection of efficient sets is based on mean-variance criterion with riskless asset (MVR criterion), or the second or the third degree stochastic dominance criterion with riskless asset (SSDR or TSDR criterion, respectively). 3. The Studies of the 1990s Table 2 provides an overview of persistence studies of the 1990s and reveals one general trend in the research design of the performance persistence studies; i.e., the shift to the use of shorter selection period and holding period compared to those used in the earlier studies carried out in the time period from 1960s to 1980s.

Christopherson and Turner (1991) classify managers according to the style and use a single index reflecting that style instead of a broad market index in determining the manager alpha (named as style index alpha). They conclude that the relationship between alpha over a previous three-year period and an alpha in the subsequent one-, two- or three-year period does not exist.

Bogle (1992) ranks the annual raw returns of over 330 equity funds for 10 successive years for the 1981-1990 time period. By comparing the average ranking of the TOP 20 funds for the former


period to their average ranking for the subsequent period he finds no persistence in rankings from one year to the next. In the interdecade return comparisons (1971-1980 vs. 1981-1990), the rankings are even less meaningful

Grinblatt and Titman (1992) examine the performance persistence of 279 mutual funds over the 1975-1984 period using the methodology based on the eight-portfolio benchmark (P8)2 . A cross-sectional regression of abnormal returns computed from the last five years of data on abnormal returns computed from the first five years of data reveals positive persistence which cannot be explained by inefficiencies in the benchmark that are related to firm size, dividend yield, past returns, skewness of return distribution, interest rate sensitivity, or CAPM beta.

In another study Grinblatt and Titman (1993) develop a new innovative performance metrics named as Portfolio Change Measure which evaluates performance on the basis of changes in quarterly portfolio holdings of 155 funds for the time period 1975-84. The results show strong evidence of persistence for the entire sample of funds and weaker evidence of persistence for subsamples of aggressive growth, growth, and growth-income funds. Therefore, authors conclude that the observed persistence in performance of the entire sample of funds is not due to consistent outperformance of aggressive growth funds.

Using the survivorship bias-free sample of 41 nonmunicipal bond funds Blake et al. (1993) examine whether past alphas are predictive of future alphas. They divide the 10-year period into two 5-year subperiods and three 3-year subperiods (excluding the first year of data in this case). While all of the models used by Blake et al. produce broadly similar ranking of funds, none of them is useful in selecting funds that have higher alphas in subsequent periods. The authors analyze also the larger samples in which the potential survivorship bias were not taken into account and find some evidence of predictability. Table 2: Performance persistence studies of the 1990s

Table 2 provides an overview of persistence studies of the 1990s and reveals one general trend in the research design of the performance persistence studies; i.e., the prominent shift to the use of shorter selection period and holding period compared to those employed in the earlier studies carried out in the prior three decades (from 1960s to 1980s). The majority of studies find at least some evidence of persistence which in most cases is explained by portfolio characteristics or/and expense ratios.

Authors Method for



sample

Time period



Results

Christophersson & Turner 1991 style index alphas 177 equity funds –1989 3 years 1–3 years no persistence

equity funds from 330 (1981) to 829 (1990)

1981–1990 1 year 1 year no persistence Bogle 1992 total returns

177 equity funds 1971–1990 10 years 10 years no persistence Grinblatt & Titman 1992 8-factor (P8) alpha 279 equity funds 1975–1984 5 years 5 years evidence of persistence

1979–1988 5 years 5 years Blake et al. 1993 several one-, 3-, 6-index alphas

41 non-municipal bond funds 1980–1988 3 years 3 years no persistence

Elton et al. 1993 3-index alpha 143 equity funds 1965–1984 10 years 10 years persistence concentrated on inferior performance

Grinblatt & Titman 1993

Portfolio Change Measure (no benchmarks required)

155 mutual funds 1975–1984 56 months 55 months evidence of persistence – weaker evidence when style differences are taken into account

3 months 6 months

1 year Hendricks et al. 1993

total returns, Sharpe Ratio, alphas based on various bechmarks

165 U.S. equity growth funds 1974–1988 1 year

2 years

short-term persistence (particularly among worst-performing funds)

2 P8 was suggested by Grinblatt & Titman (1989). The basic idea behind the formation of this benchmark is that various

firm characteristics are correlated with their stocks’ factor loadings. As a result of this, portfolios constructed from stocks classified by securities characteristics can be used as proxies for the factors. The P8 benchmark, formed from groupings of the passive portfolios’ returns just described, consists of four size-based portfolios, three dividend-yield-based portfolios, and the lowest past returns portfolio.


Authors Method for



sample

Time period



Results

1 month 1 month total returns 1–3 years 1–3 years 1 month 1 months

Goetzmann & Ibbotson 1994 Jensen Alphas

728 equity funds 1976–1988

2 years 2 years

evidence of persistence at its strongest on the very short term

Brown & Goetzmann 1995

total returns, Jensen Alpha, Appraisal Ratio, 3-index alpha, 3-index Appraisal Ratio, and characteristic return

equity funds from 372 (1976) to 829 (1988)

1976–1988 1 year 1 year evidence of persistence within top- and worst-performers but also occasional reversals

300 U.S. equity funds 1988–1993 3 years 3 years ambiguous results

Kahn & Rudd 1995 total returns, Appraisal Ratio, and selection returns 195 bond funds 10/90–9/93 1 yr 5 mos 1 yr 5 mos

persistence in risk-adjusted performance, no persistence in total returns

Malkiel 1995 total returns

equity funds from 220 (1971-1972) to 684 (1990-1991)

1971–1991 1 year 1 year mixed results; strong persistence during 1970s, no persistence during 1980s

Elton et al. 1996 4-index alpha of Elton et al. (1996)

188 U.S. equity funds 1977–1993 1–3 years 1–3 years evidence of persistence at its strongest

using equal lengths of SP and HP total returns

Gruber 1996 4-index alpha of Elton et al. (1996)

270 common equity funds 1985–1994 1–3 years 1–3 years

strong evidence of persistence particularly when 4-index alpha is used as performance metric on SP a

Volkman & Vohar 1996

abnormal returns based on various models

332 funds 10/80–12/89 1–5 years 1–4 years persistence over 1- to 3-year HPb

based on 3- and 4-year SP

Carhart 1997

total returns, Jensen Alpha, Fama-French 3-factor alpha, Carhart 4-factor alpha

1,892 U.S. equity funds 1962–1993 1–3 years 1–5 years

short-term persistence in total returns explained by characteristics of portfolio holdings and expense differences

1 year 1 year 2 years 2 years Phelps & Detzel

1997 several multi-index alphas 87 mutual funds 1984–1994

3 years 3 years

no reliable evidence of persistence (occasional persistence observed is explained by style differences)

1 year 1 year 3 years 3 years

Sauer 1997

total returns, Sharpe Ratio, Treynor Ratio, Jensen Alpha, and the Elton et al. 3-factor alpha

U.S. equity funds from 249 (1976) to 1,365 (1992)

1976–1992 5 years 5 years

weak evidence of persistence explained by style differences

Detzel & Weigand 1998

characteristic-adjusted returns 61 equity funds 1975–1995 1 year 1 year

weak persistence that deteriorates significantly after adjusting for beta, expense ratios, firm size, and investment style

Porter & Trifts 1998 total returns

93 mutual funds with experienced portfolio managers

1986–1995 5 years 5 years no general persistence; inferior performance persists particularly for funds with high expenses

1 year 1 year 2 years evidence of persistence

1 month 1 month Allen & Tan 1999 total returns, group-adjusted alpha

131 U.K. investment trusts 1989–1995

6 months 6 months no evidence of persistence, but rather performance reversal

Fletcher 1999 unconditional and conditional Jensen Alphas

85 U.K. American unit trusts 1985–1996 1 year 1 year no evidence of persistence

a SP refers to selection period b HP refers to holding period

As a part of the informational efficiency study of managed portfolios Elton et al. (1993) examine the persistence of the alphas of 143 mutual funds using the three-factor variant of the conventional CAPM3. They rank the decile-portfolios from two successive decades and find highly significant correlation between these two ranks. Furthermore, a regression of the three-factor alpha of

3 The factors employed by Elton, Gruber, Das, and Hlavka (EGDH 1993) are the return on the S&P 500 index, the return

on a non-S&P equity index that has been made orthogonal to the S&P index, and the return on a bond return index that has been made orthogonal to both the S&P and the non-S&P equity index.


the latter period on alpha of the earlier period is significant at the 5 percent level. However, the authors are somewhat reserved in generalizing the results due to the strong persistence of inferior performance.

In one of the most widely-cited studies of the fund literature Hendricks et al. (1993) examine performance persistence in a sample of open-end, no-load, growth oriented equity funds over the 1974-1988 time-period. The authors launch the already-established concept of “hot-hands” (which appears also in the title of this study) to describe the short-term nature of performance persistence; the results show that funds that outperform in the most recent year continue to outperform in the near term peaking at the holding period of the same length. Furthermore, funds that perform poorly during the most recent one-year period tend to underperform also in the near future. According to the results, the persistence of inferior performance is even stronger than persistence of superior performance. Moreover, Hendricks et al. (1993) prove that the results are robust on several potential biases (i.e., benchmark inefficiency, spurious persistence, nonlinearities between fund returns and benchmark returns, time-varying betas and data-snooping bias introduced by Lo and MacKinlay 1990).

Goetzmann and Ibbotson (1994) analyze monthly total returns of 728 mutual funds over 13-year period (1976-1988). Using total returns and the Jensen alphas as performance measures they examine the power of various lengths of selection periods to predict the performance measured from holding periods of the same length. The time horizons tested in this study are one year, two and three years and one month. Generally, the results are significant, i.e., past performance has some predictive power on future performance for all time horizons tested.

To test robustness of the results over the conjecture whether the performance persistence is related more to investment style than skill, Goetzmann and Ibbotson (1994) perform the same tests on a sub-sample that consists only of the relatively homogenous growth funds. The tests indicate that the performance persistence is not likely to be due to style differences. The study of Goetzmann and Ibbotson (1994) is innovative in the sense that for the first time in the mutual fund literature it controls for momentum effect; In order to discriminate whether the one-month persistence is due to momentum effect or a long-term phenomenon (related possibly to risk level), Goetzmann and Ibbotson perform a randomization test, which explicitly uses the long-term mean return to the fund as the control to test whether the preceding month return has any additional explanatory power. They find the preceding month’s ranking to have power to predict the next month’s ranking above and beyond the effects caused by differences in long-term means.

Brown and Goetzmann (1995) examine to what extent the previous-year performance of a fund can predict the performance of successive year over the 1976-1988 period. The authors use several alternative performance measures4 and find clear evidence of relative performance persistence but instead, evidence of absolute persistence is weaker and dependent of the time period being evaluated. Most of the persistence phenomenon observed is due to consistent underperformance rather than due to consistent outperformance. In this respect the results are parallel to those of Jensen (1968), Shukla and Trzcinka (1994), Carhart (1997), Lunde et al. (1999), Teo and Woo (2001) and Fletcher and Forbes (2002). In another respect, the findings of Brown and Goetzmann are parallel to those of Malkiel (1995), who ⎯ using quarterly data of equity mutual funds from 21-year period from 1971 to 1991 ⎯ tests the prediction power of the previous-year return of a fund on the corresponding return of successive year. He finds considerable persistence in fund returns during the 1970s, but no consistency of them during the 1980s. Similar results are also reported later by Droms and Walker (2001a) who hypothesize that time period dependency may be due to the size anomaly; small-cap stocks outperformed the S&P 500 during the 1970s, while reverse was true for the 1980s. The results of Detzel and Weigand (1998) reveal that besides size anomaly, also style characteristics of the stocks held by equity funds explain the persistence findings for the 1976-1985 period; allowing for the market-cap of the stocks included in funds’ portfolios and manager investment styles as additional explanatory variables, all of the persistence in fund performance disappears. However, the explanatory

4 The tests are done using the total return, the Jensen Alpha, the Treynor & Black (1973) Appraisal Ratio, the Three-index

alpha and the corresponding Appraisal Ratio, and “group-adjusted” return (the raw return minus the return for the fund style.


power of size anomaly is not unambiguous; Both Quigley and Sinquefield (2000), using U.K. fund data, and Davis (2001), using U.S. fund data, report persistence explained by the worst-performing small-cap funds.

Kahn and Rudd (1995) examine performance persistence of both equity and fixed income funds analyzing them separately. For equity funds, a selection period of three years is used to predict the performance of holding period of the same length, while for fixed income funds the corresponding length of periods is a year and five months for both selection and holding periods. In the case of equity funds, regression analysis finds evidence of persistence at the 5 % level only for Appraisal Ratios. Using the contingency tables approach none of the tests for three performance measures shows evidence of persistence. In the case of fixed income funds, both regression and contingency table analyses show significant persistence of both style-adjusted returns and Appraisal Ratios.

Elton et al. (1996) examine the survivorship bias-free sample of common stock funds followed from 1977 to the end of 1993. They extend the three-index model of Elton, Gruber, Das and Hlavka (EGDH 1993) by introducing one more index to account for the performance of growth versus value stocks. Furthermore, Elton et al. (1996) refine the EGDH model using differential returns in measuring size (i.e., differential return between a portfolio of small stocks and large stocks) and types of stocks (i.e., differential return between a portfolio of growth stocks and a portfolio of value stocks) as factors besides the return on the S&P 500 index and the bond index return. They form decile portfolios of funds based on four measures (i.e., total returns, one- and three-year four-index alpha and the t-statistic of the four-index alpha) and observe how the decile portfolios perform in follow-up period whose performance is measured with one- and three-year four-index alpha. For three-year holding period, any other ranking criteria studied, except for total return, leads to a significant rank correlation. The same analysis is repeated with one-year holding period. In this case, ranking techniques involving one year of past data generally perform much better than those involving 3 years of past data. Similarly to the results of Hendricks et al. (1993), the fraction portfolios formed on the basis of total return are highly correlated with future alpha when alpha is measured over a one-year period, but the relationship deteriorates when future alpha is measured over three years. However, when ranking is done on a risk-adjusted basis the predictability increases as performance is measured over the longer (three-year) period.

Using raw returns and the four-index alpha of Elton et al. (1996) as performance measures, Gruber (1996) studies the survivorship bias-free sample of common stock mutual funds over the 1985-1994 period. At the end of the each year, funds are ranked and placed to the decile portfolios on the basis of a particular selection criterion. Gruber finds strong performance persistence with both one- and three year horizons and also the four-index alpha’s superiority to forecast future performance determined on the basis of either risk-adjusted or raw returns.

Volkman and Wohar (1996) analyze the performance persistence of 112 mutual funds over the 1980-1989 period. They use three different empirical models to test the performance persistence in relation to each of 20 combinations of selection periods of 12, 24, 36, 48 and 60 months, and holding periods of 12, 24, 36 and 48 months. All three models show persistence in abnormal returns over a two- to three-year holding period based on a three- to four-year selection period.

In one of the most oft-cited studies in the mutual fund literature, Carhart (1997) examines the survivorship-bias free data consisting of monthly returns of diversified equity funds over the 1962-1993 period. Replicating the methodology of Hendricks et al. (1993), he forms decile portfolios of mutual funds on lagged one-year returns and estimates performance on the resulting portfolios. Though the results of Carhart strongly support the short-term performance persistence he notes that most of the short-term persistence observed is explained by common factor sensitivities of his four-factor model5, and differences in expenses and transaction costs.

5 Carhart (1997) constructs his 4-factor model by including on the Fama & French 3-factor model an additional factor

capturing Jegadeesh and Titman’s (1993) one-year momentum anomaly. This is motivated by the 3-factor model’s inability to explain cross-sectional variation in momentum-sorted portfolios (documented by Fama & French 1996).


Using selection periods of one year, three and five years and investment periods of equivalent length Sauer (1997) finds statistically significant performance persistence in all horizons studied for U.S. equity funds over the 1976-1992 period. Taking account of sporadic evidence of reversion in relative fund performance during some successive years, the shorter the horizons the stronger persistence. The same causality is also found for the zero-investment long/short octile portfolios formed on the basis of the 3-index EGDH alpha. In addition, Sauer examines persistence separately for the growth and growth and income mutual funds, respectively. When the full sample is partitioned by investment objective, the statistically significant persistence in mutual fund performance is no longer evident on five-year horizons. Unfortunately, Sauer does not report the corresponding results with shorter horizons.

An interesting contribution to persistence literature is provided by Phelps and Detzel (1997) who mimic the study of Goetzmann and Ibbotson (1994) by examining the predicting power of past alphas for the same performance measures for the subsequent period of equal length. Based on several empirical tests with the multi-index models with varied number of factors the authors argue that the positive persistence documented in several studies is the result of persistence in broad equity classes (macropersistence) rather than sustainable managerial ability (micropersistence). In other words, the observed persistence would result from factors that a generic index as a surrogate for market return cannot adequately capture. Also, according to Detzel and Weigand (1998), fund performance corresponds to the performance trends of the size and style classes in which funds invest. Employing the model suggested by Daniel and Titman (1997) that directly relates mutual fund returns to the characteristic of the stocks held by funds, the authors find that the adjustment of fund returns for both the size of the firms in which funds invest, and for financial ratios intended to capture fund manager investment styles explains all the persistence in mutual fund performance.

Porter and Trifts (1998) examine the performance of 93 experienced fund managers over the ten-year period of 1986-1995 using relative percentile ranks based on quarterly compounded, annual total returns measured against funds with the same investment objective. The results show that for the experienced managers studied, superior performance in one five-year period is not predictive of superior performance over the next five years. However, inferior performance persists particularly for funds with above average expense ratios.

Allen and Tan (1999) investigate the performance persistence of 131 U.K. investment trust company managers over the 1989-1995 period. The authors examine the prediction ability of both raw returns and that of style-index alphas for the one-year, half-year and monthly periods. According to the results, prior one-year performance includes definite information about future performance for the periods of both one year and two years on the basis of both measures. By contrast, for shorter periods the results support performance reversal rather than persistence.

Fletcher (1999) examines the performance of a sample of 85 UK American unit trusts using both the unconditional Jensen alpha and the conditional Jensen alpha (developed by Ferson and Schadt (1996)) as follows: At the beginning of each year all trusts are ranked on the basis of their cumulative excess returns over the previous year and grouped into quartile portfolios. Equally weighted monthly excess returns are then estimated over the next year. Fletcher finds no evidence of the persistence in performance for this sample of trusts. 4. The Studies of the 2000s Table 3 provides a summary of persistence studies published heretofore in the new millennium. Compared to the studies published in the previous decade the average length of both selection period and holding period has decreased. Thus, the long-term tendency in the persistence literature towards using shorter past data to predict future performance for shorter holding periods has continued also in 2000s.

Blake and Morey (2000) compares the Morningstar ratings as a predictor of mutual fund performance to the established performance metrics (i.e., total returns, Sharpe Ratio, Jensen alpha, and


4-index alpha of Elton et al. (1996)). Based on two sample groups for time periods of different length the comparison indicates that the Morningstar ratings are in the middle in terms of predicting future performance. For the longer sample period based on 10-year selection period, total returns and the 4-index alpha do worse, but the Sharpe Ratio does considerably better than the Morningstar ratings. For the shorter sample period based on 3-year selection period the results show somewhat surprisingly that Morningstar ratings predict the future performance significantly better than the above-mentioned established performance metrics. However, after controlling for the fact that for the majority of funds in the sub-sample employed the Morningstar stars are based on up to 10 years of return data in contrast with 3-year selection period of performance metrics being compared, the superior ability of the Morningstar method disappears. Thus, in contrast to the prevailing trend of the persistence literature, this finding of Blake and Morey (2000) would indicate that it could be still worthwhile to use return history older than 3 years for the purposes of predicting future performance. The authors conclude that the Morningstar rating system is able to "identify" low-performing funds since funds with less than three stars generally have much worse future performance than other groups. Instead, only weak evidence that the five-star (highest-rated) funds would outperform the four- and three-star funds is found. Thus, the Morningstar rating system, like the other established performance metrics, seems to be more capable in identifying inferior than superior performers of the future due to the persistence in poor performance.

As a part of the larger study of the value of active mutual fund management Chen et al. (2000) investigate performance persistence by examining the performance of both the holdings and the trades of mutual funds for the 1975-1994 period. Controlling for differences in stock characteristics, the results generally do not support the persistence of fund performance, although persistence in unadjusted returns on mutual fund portfolio holdings exist.

Dahlquist et al. (2000) estimate performance persistence of Swedish mutual funds by treating previous-year alphas obtained from various regressions as an attribute of future success. The results show persistence neither for equity nor bond funds, but among money market funds it does exist. Using monthly returns of all U.K. equity funds for the 1978-1997 period Quigley and Sinquefield (2000) find evidence of persistence among inferior performers but no persistence among superior performers. Contrary to size anomaly, persistent underperformance is concentrated on small-cap funds.

Jain and Wu (2000) examine 117 mutual funds that were advertised from July 1994 through June 1996 in Barron’s or Money magazine by comparing pre- and post-advertisement performance of these funds. Using four different performance measures6 they find that advertised funds have superior performance prior to advertisement year, but turn to underperformers in the year following advertising.

6 Jain and Wu (2000) employ excess return over return on funds with the same investment objective (noted as the similar-

funds-adjusted return), and that over return on S & P 500 index (noted as the S&P 500-adjusted return), the Jensen alpha and the Carhart 4-factor alpha as performance metrics.


Table 3: Performance persistence studies of the 2000s Table 3 provides a summary of persistence studies published heretofore in the new millennium. Compared to the studies published in the previous decade the average length of both selection period and holding period has decreased. The majority of the studies of the 2000s find evidence of persistence but many of them with provisions. Evidence of persistence at least among worst-performing funds can be considered noteworthy. However, overall results are somewhat mixed varying from strong persistence to reversal depending on performance metrics, observation period and the sample data employed.

Authors Method for


Type of funds and size of sample

Time period



Results

1 year 3 years 263 U.S. equity funds 1983–1997 10 years 5 years

evidence of persistence particularly in inferior performance (the best predictor: Sharpe Ratio)

1 year 3 years

Blake & Morey 2000

Morningstar ratings, total returns, Sharpe Ratio, Jensen Alpha, 4-index alpha of Elton et al. (1996) 635 U.S. equity funds 1990–1997 3 years

5 years

evidence of persistence particularly in inferior performance (the best predictor: Morningstar rating)

Chen et al. 2000

total returns, characteristic-based alpha of DGTWa (1997)

U.S. mutual funds from 393 (1975) to 2,424 (1994)

1975–1994 1 year 1 year

no general persistence using characteristic-based alphas; persistence using unadjusted returns explained by momentum effect

Dahlquist et al. 2000

unconditional and conditional 2-index alphas for equity and bond funds

210 Swedish funds (126 equity funds, 42 bond funds, 42 money market funds)

1993–1997 1 year 1 year

robust persistence among money market funds, no persistence among other funds

Jain & Wu 2000

similar-funds-adjusted return, S&P 500-adjusted return, Jensen Alpha, 4-factor alpha

117 mutual funds (recently advertised)

7/1993–6/1997 1 year 1 year no persistence among

recently advertised funds

1 year 1 year persistence limited to the high-yield bond funds Philpot et

al. 2000 Sharpe Ratio

73 non-conventional bond funds (high-yield, global, and convertible bond funds)

1988–1997 5 years 5 years no persistence

1 year 1 year Quigley & Sinquefield 2000

total returns, Fama-French 3-factor alpha

311 U.K. equity unit trusts (on average) 1978–1997 3 years 3 years

persistence only among worst-performing small-cap funds

Davis 2001

Fama-French 3-factor alpha 4,686 equity funds 1962–1988 3 years 1 year

weak evidence of short-term persistence among the best-performing growth funds and among the worst-performing small-cap funds

raw returns Jensen Alphas 10 years 10 years no long-term persistence Droms &

Walker 2001a raw returns

151 U.S. equity funds 1971–1990 1 year 1-3 yrs

ahead short-term persistence

Droms & Walker 2001b

raw returns International equity funds from 11 (1977) to 473 (1996)

1977–1996 1 year 1-4 years performance persists over 1-year holding period but not over longer holding periods

1 year 1 year total returns 3 years 3 years

short-term persistence particularly in growth fund returns Jensen Alpha ter Horst

et. al. 2001

Carhart 4-factor alpha

growth and income equity funds from sample of 2,678 U.S. equity funds (number of funds within fund classes not reported)

1989–1994

3 years 3 years

evidence of persistence among worst-performing funds (esp. among income equity funds)

1 year 1 year 5 years 5 years Group-adjusted returns,

total returns Carhart et al. 2002

4-factor alpha

2,071 diversified equity funds 1962–1995

3 years 3 years

persistence in total and group-adjusted returns deteriorating after end-of-sample or look-ahead


Authors Method for


Type of funds and size of sample

Time period



Results

conditioning

Detzler 2002

4-factor alpha of Detzler (2002) 423 mutual funds 1990–1996 3 years 1 year

no evidence of persistence among publicly-ranked funds

Carhart 4-factor alpha Jensen Alpha APT alpha Fletcher &

Forbes 2002

Conditional alpha

U.K. equity trusts from 139 (1982) to 724 (1996)

1982–1996 1 year 1 year

ambiguous; (performance reversal based on conditional alpha – persistence based on unconditional alphas but no persistence based on Carhart alpha)

relative excess returns (over the equally-weighted average return of all the funds)

6 months 6 months evidence for short-term persistence (particularly for the 1995–1999 period)

Collinet & Firer 2003

Sharpe ratios

South African general equity unit trusts from 7 (1980) to 43 (1998)

1980–1999

3 years 3 years medium term persistence

Jan & Hung 2003 efficient set approach 16,345 funds of all

type 1961–2000 1 year 1 year persistence for most equity and money market funds; reversal for most bond funds

5-factor model Deaves 2004 conditional CAPM

alpha

Canadian equity funds from 110 (1988) to 300 (1998)

1988–1998 1 year 1-5 years ahead

short-term persistence; some evidence for medium-term persistence

Jan & Hung 2004 Carhart 4-factor alpha 3,316 U.S. equity

funds 1961–2000

Combination of 1-yr &

3-yr rankings (lagged)

1 year short- and medium-term persistence

Prather et al. 2004 multi-factor alpha

equity funds from 2,124 (1996) to 3,391 (1999)

1996–2000 1 year 1 year no persistence

Bollen & Busse 2005

Carhart 4-factor alpha 230 U.S. equity funds (new funds after 1985 not added)

1985–1995 3 months 3 months very short-term persistence

Morey 2005

Morningstar ratings/Sharpe Ratio, Jensen Alpha, 4-factor alphas of both Elton et al. (1996) and Carhart (1997)

273 U.S. equity funds 4/1987–6/2000 3 years 3 years

no persistence among the funds upgraded for the first time to five-star funds by Morningstar

1 year 3 months

Busse & Irvine 2006

various multi-factor alphas (Bayesian) for SP; standard multi-factor alphas for HP

230 U.S. equity funds (new funds after 1985 not added)

1985–1995 3 years

3 months short-term persistence particularly by using annual selection period

1 month 3 months

Harlow & Brown 2006

Fama-French 3-factor alpha


1979–2003 3 years 1 year

strong persistence for 1-month and 3-month holding periods

1 year Kosowski et al. 2006 Carhart 4-factor alpha

U.S. equity funds from 231 (1971-1975) to 1,788 (1975-2002)

1975–2002 3 years 1 year

persistence among growth-oriented funds; non-persistence among income-oriented funds

raw returns 1 year Polwitoon & Tawatnuntachai 2006

Sharpe Ratios

global bond funds from 103 (2003) to 183 (1997)

1993–2004 3 years 1 year

mixed results; persistence for some consecutive years – reversal for some other consecutive years

Huij & Verbeek 2007

Carhart 4-factor alpha (Bayesian)


1984-2003 1 year 1 month

short-term performance persists but varies across styles (strongest for small cap/growth funds)

a DGTW refers to the method introduced by Daniel, Grinblatt, Titman & Wermers (1997)


Philpot et al. (2000) analyze performance persistence of 73 non-conventional bond funds (high-yield bonds, global issues and convertible bonds) for the 1988-1997 time period and find evidence of short-term performance persistence for the high-yield bond fund sub-sample, but no persistence for the general class or for other classes of funds. The persistence found on the basis of one-year Sharpe Ratios disappears, as the selection period is extended to five years and the sample period examined is divided into two sub-periods of the equal length.

Davis (2001) examines the relationship between equity fund performance and manager style by employing the Fama-French (1993) alpha as performance metrics. Particularly, Davis addresses whether any particular investment style reliably delivers abnormal performance and furthermore, whether any evidence of performance persistence can be found when funds with similar styles are compared. Davis does not find positive abnormal returns over the 1965-1998 period although he does find some evidence of short-term performance persistence among best-performing growth funds. However, this persistence is not sustained beyond one year.

The study of Droms and Walker (2001a) follows the methodology developed by Goetzmann and Ibbotson (1994), Brown and Goetzmann (1995), and Malkiel (1995) to test for performance persistence among equity mutual funds over the two decades from 1971 to 1990. The results show no long-term persistence based on either total returns or the Jensen Alphas. Instead, evidence of short-term persistence is found for periods of one, two and three years. Consistent with the findings of Brown and Goetzmann (1995), and Malkiel (1995), the persistence is more pronounced during the first decade of the 1970s than the 1980s.

Droms and Walker (2001b) follows the same type of methodology also on another study that tests for short-term performance persistence in international equity mutual funds over the 20-year period from 1977 to 1996. Using annual returns as performance measures, Droms and Walker (2001b) find statistically significant performance persistence for 1-year holding periods, but no persistence for 2-, 3- or 4-year periods. The similar conclusions are also drawn by ter Horst et al. (2001) who examine the impacts of survivorship bias and look-ahead bias with the sample of U.S. growth and income equity funds for the 1989-1994 period. For 3-year selection period and holding period the results show evidence of risk-adjusted performance persistence only among worst-performing funds (particularly among income equity funds). Without any risk-adjustment procedures the same analysis shows no signs of medium-term persistence.

In a comprehensive study of selection bias issues in the context of mutual fund research Carhart et al. (2002) find persistence in the performance of U.S. mutual funds. Employing three different performance metrics7 the authors undertake Hendricks, Patel and Zeckhauser’s (1997) test for spurious persistence due to survivorship8 and find the results to be robust to survivorship bias.

Using the sample consisting of 757 funds Detzler (2002) examines the performance of an investment strategy based on mutual fund rankings by the popular press (Barron’s, Business Week and Forbes). The results show that rankings correspond to higher returns 3, 6, and 12 months before the publication dates of rankings, but the funds do not have superior performance in the post-ranking periods of equal lengths. Furthermore, the ranked funds have often higher risk than their non-ranked peers in both the pre-ranking and post-ranking periods, suggesting that funds receiving rankings may also be risk-takers. The 4-factor alpha9 shows that the funds with rankings have higher risk-adjusted performance during the pre-ranking period and negative performance in the post-ranking period providing evidence against persistence. Thus, the results are very much consistent with the findings of Jain and Wu (2000).

7 The three performance measures used by Carhart et al. (2002) are “group-adjusted” returns, the Jensen Alpha, and the

Carhart 4-factor model. 8 Hendricks et al. (1997) show that when performance is categorized finely, the relation between pre- and post-period

rankings will be J-shaped in a survivor-biased sample or using a look-ahead biased methodology. They devise a regression test for this convexity, which Carhart et al. (2002) employ in their survivorship- and look-ahead -biased samples.

9 The Detzler 4-factor alpha is based on following indices: S&P 500 index, the MSCI EAFE index, a small-cap index, and the Lehman Brothers Aggregate Bond index.


Fletcher and Forbes (2002) find evidence of persistence in UK unit trust performance when performance is determined by means of factor models based on the CAPM or APT. However, when performance is estimated relative to the Carhart 4-factor model, the persistence disappears. Interestingly, the use of the conditional performance measure developed by Ferson and Schadt (1996) turns the observed persistence into significant reversal. Thus, Fletcher and Forbes (2002) conclude that the persistence in performance of UK trusts is not a manifestation of superior stock selection strategy, but can be explained by factors that are known to capture cross-sectional differences in stock returns.

Collinet and Firer (2003) analyze the relative performance of South African general equity unit trusts from 1980 to 1999 using the relative excess returns (over the equally-weighted mean return of all the funds in existence during the period) as a performance measure. The authors find evidence of persistence when the selection of funds for 6-month holding period is based on performance from the selection period of 6-12 months. According to the results, persistence is particularly evident during the 1995–1999 period using 6-month selection period. However, even within this period, there are cases where rankings from one holding period to the next are random and also cases of reversed rankings. Furthermore, the results of tests with longer holding periods are less conclusive; although strong persistence is found over certain periods, the results are very sensitive to variations in both the ending date of the selected sample period and the time period studied.

As a part of the larger study of mutual fund attributes and performance Jan and Hung (2003) examine performance persistence of U.S. mutual funds over the 1961-2000 period. Forming winner and loser portfolios based on one-year raw returns and testing the efficiency of these portfolios of funds the authors find that persistence exists among 13 out of 24 fund categories examined. On the other hand, evidence of performance reversal is found among 7 fund categories. According to the results, persistence is more common among equity funds while reversal is typical in most bond fund categories.

Another study of Jan and Hung (2004), using the same time period but somewhat smaller sample of the same database, hypothesize that if mutual fund performance persists in the short run, it should also persist in the long run. A division of the funds in the database on the basis of past 4-factor alpha of Carhart (1997) – funds with strong past short-run and long-run performance rated as best – reveals that in the subsequent year the best funds significantly outperforms the worst funds. The authors conclude that mutual fund investors can likely benefit from selecting funds on the basis of not only past short-run performance but also past long-run performance.

Deaves (2004) examines performance persistence of Canadian equity funds on the basis of several performance measures. Using carefully constructed bias-free sample for the 1988-1998 period he finds evidence of short-term persistence at its strongest when one-year selection period is used to predict next year’s performance.

Prather et al. (2004) analyze the impact of numerous fund-specific characteristic on performance of equity funds. The analysis includes 25 individual fund factors or characteristics within the four broad categories of popularity, growth, cost and management. For the 1996-2000 period, they find no evidence of persistence, but instead, a reversal pattern in mutual fund performance.

Studying daily returns of 230 U.S. equity funds from the 1985-1995 period, Bollen and Busse (2005) find that the top decile funds managers generates statistically significant quarterly abnormal returns that persist for the following quarter. The results are robust across stock selection, market timing, and mixed strategy models, which suggests that misspecification of the performance model is not the reason for evidence of persistence. However, the authors note that the economic significance of the post-ranking abnormal returns is questionable given the transaction costs and taxes levied on a strategy capturing the persistent abnormal returns of the top decile.

Morey (2005) examines the performance persistence of U.S. equity funds that have just received their first 5-star rating from Morningstar. During the 3-year period following the rating upgrade performance deteriorates dramatically in spite of the performance metrics used in evaluating performance of holding period. In this sense, the results are parallel to those of Detzler (2002).


Morey’s results are also robust across different sub-samples of funds (i.e., samples of actively managed funds and growth funds).

Using a 3 × 3 classification system similar to that of Morningstar Harlow and Brown (2006) sort the fund universe based on alphas of the Fama & French 3-factor model (1992, 1993), and examine performance persistence both within these fund classes and in the aggregate level. Based on the three-year selection period, the results indicate a strong degree of performance persistence in the active U.S. equity fund sample for holding periods up to one year. The authors state that persistence is particularly strong and highly statistically significant in the near short-term, i.e. for time periods of one month and three months.

Applying a new bootstrap technique to the monthly net returns of the universe of U.S. equity funds during the 1975-2002 period, Kosowski et al. (2006) find strong evidence of superior performance and performance persistence among growth-oriented funds, but no corresponding evidence of income-oriented funds. They rank funds using the unconditional four-factor alpha measured over one and three years prior to one-year holding period.

Polwitoon and Tawatnuntachai (2006) examine performance persistence of US-based global bond funds during the period of 1993–2004. Following the methodology of Elton et al. (1996) funds are ranked on the basis of 1- and 3-year raw returns and 1- and 3-year Sharpe Rratios prior to subsequent 1-year holding period. The results show that persistence is stronger using shorter selection period, i.e., 1 year instead of 3 years. Although some evidence of performance persistence among global bond funds is found, and the rank correlation is significant for all years, it is negative in 5 out of 11 years, indicating performance reversal almost as often as it indicates persistence.

Recently, several scholars have used Bayesian alphas as a performance measure (e.g., see Baks et al., 2001; Pástor and Stambaugh, 2002a, 2002b; Bollen and Busse, 2005; Busse and Irvine, 2006; Huij and Verbeek, 2007). The basic idea of the Bayesian approach is to include prior information related to such issues as funds’ expenses, investors’ beliefs about managerial skills, benchmark pricing abilities, or the returns on other mutual funds and benchmark factors, in the resulting estimates. Such an approach can be motivated both by cross-sectional learning of investors (as noted by Jones and Shanken 2005) and on the basis of statistical arguments only. The results of the studies applying the Bayesian approach are promising since the superior prediction power of Bayesian alphas over standard OLS alphas is documented most often.

Using daily returns of 230 U.S. equity funds and the Bayesian approach suggested by Pástor and Stambaugh (2002b)10, Busse and Irvine (2006) compare the performance predictability of Bayesian alphas with standard frequentist measures. When the returns on passive nonbenchmark assets are correlated with fund holdings, incorporating histories of these returns in a Bayesian framework produces alphas that predict future performance better than standard alphas do. During the 1985-1995 period being evaluated, persistence is at its strongest when the Bayesian alphas estimated over one-year ranking period are used to predict subsequent standard quarterly alphas. Also, the other selection periods tested (i.e., one quarter and three years) show evidence of prediction power. Of Bayesian alphas based on various performance models the best is that of the Carhart 4-factor model.

However, the predictive accuracy of Bayesian alphas is in most studies greatly affected by the investor’s prior belief about managerial skill. Huij and Verbeek (2007) apply the Bayesian approach so that it does not require investors to explicitly formulate their beliefs about managerial skill (i.e. the prior), or to make assumptions about cross-sectional characteristics that drive performance. This is done by incorporating the large cross-section of mutual fund alphas in measuring the skill of an individual fund manager. The basic principle is to allow the prior to learn across other funds included in the sample, in which case the resulting belief in managerial skill is no longer fully subjective, but instead, it is entirely based on sample-period data. Using monthly return data of more than 6,400 U.S. equity mutual funds Huij and Verbeek investigate short-run performance persistence over the period

10 Pástor & Stambaugh (2002b) show that the precision of estimates of fund performance could be improved by

incorporating a long time series of passive asset returns using Bayesian approach. Thus, mutual fund performance measures need not be restricted to information on fund and passive assets over the life of the fund.


1984–2003. They find that when funds are sorted into decile portfolios based on 12-month ranking periods, the top decile of funds earns a statistically significant, abnormal return of 0.26 percent in the first month after ranking. This effect is robust to load fees that are involved with a strategy of chasing winners. Furthermore, their results show that persistence varies across investment styles and it is mainly concentrated in relatively young, small cap/growth funds. 5. Concluding Remarks The preceding review of performance persistence literature reveals that plenty of studies have been published both for and against the prediction power of past performance. The results of previous studies also indicate that there is not only one truth on this issue. Firstly, as shown in several studies, even contrary conclusions may sometimes be drawn by using the same sample but different methodology of performance evaluation (e.g., see Kahn and Rudd, 1995; Fletcher and Forbes, 2002).

Some methodologies seem to be more sensitive than some others to identify performance persistence. For example, comparing performance differences between quantile portfolios may result in contrary conclusions than employing the rank correlation test for the same sample.

Another source of bias that may affect the inferences on performance persistence stems from performance model employed. In most cases, when the performance model takes account of differences in portfolio characteristics, the evidence of persistence usually deteriorates, and in some cases vanishes completely. Adding other factors such as size, book-to-market, or momentum besides general market factor into the performance model may change the results drastically. E.g., the results of Carhart (1997) show that evidence of persistence may be explained by the omitting momentum factor. The above-described bias is explained by differences in investment styles of fund managers. For example, in the second half of 1990s many funds followed either value or growth strategy. Had style bias not been taken into account in the performance model, the chances that a value-oriented fund would have outperformed a growth-oriented fund were very low. Correspondingly, in the beginning of the ongoing millennium the case has been contrary. Unfortunately, style bias cannot be completely circumvented by employing performance metrics (such as the Sharpe Ratio, for example) that are not based any benchmarks. Pätäri (2008) compares an extensive set of performance metrics that are based on both full-scale and partial-scale measures of risk (i.e., measures of downside risk) derived from a portfolio’s own return distribution without using any benchmarks. The results show that due to the asymmetries of return distributions the relative performance of funds depends on a risk measure employed. It is highly probable that the sensitivity of total-risk based performance rankings to the selection of a risk measure is a reflection of style bias.

Style bias has been tried to alleviate by using style-adjusted performance metrics but even that approach can not protect from another source of bias. While style bias stems from performance metrics employed, a misclassification bias is caused by a fund’s deflection from its stated investment policy. Several studies have documented severe and frequent divergences between the actual and stated investment policies of mutual funds (e.g., see diBartolomeo and Witkowski, 1997; Brown and Goetzmann, 1997; Kim et al., 2000; Castellanos and Alonso, 2005; Detzel, 2006). According to the results the average divergence rate ranges from 33 per cent to as high as 50 per cent within some fund categories. Therefore, the fact that very many mutual funds are benchmarked against irrelevant factors may induce spurious persistence.

As noted by several scholars, performance persistence studies are prone to several biases that stems from ex-post conditioning of data. The most well-known of these is survivorship bias that stems from including only the funds that exist at the end of sample period. Though the survivorship bias is quite often offered as an explanation for the results supporting performance persistence the opinions on the degree of the impact of survivorship bias on the results of persistence studies vary strongly among scholars (e.g., compare the views of Grinblatt and Titman, 1989; Hendricks et al., 1993; Wermers, 1997, and/or Sauer (1997) to those of Malkiel 1995; Gruber, 1996; ter Horst et al., 2001; Carhart et al., 2002, and/or Deaves, 2004). According to some studies, persistence is even stronger in full samples


than survivor-only samples (e.g., see Hendricks et al., 1993; Carpenter and Lynch, 1999; Carhart et al., 2002) while some other studies concludes that survivorship bias may in certain conditions induce performance reversal rather than persistence (e.g., see Brown et al., 1992; Grinblatt and Titman, 1992).

Another form of data-conditioning stems from look-ahead bias, which is inherent any test of performance persistence. A common methodology in performance persistence studies is to rank funds and assign them to fraction portfolios on the basis of their performance from the preceding selection period. Look-ahead bias arises because funds disappear in non-random way during the selection period or holding period, i.e., the attrition rate of funds within fraction portfolios is not stable. Thus, an essential approach to control look-ahead bias is to model the survival process of funds, and secondly, to analyze how it relates to their past performance. Though this approach is followed very seldom in mutual fund persistence studies the recent studies indicate that look-ahead bias is not very severe in samples of mutual funds if survivorship bias is controlled (e.g. see ter Horst et al., 2001; Carhart et al., 2002; Deaves, 2004).

The third form of data-conditioning bias called a self-selection bias is caused by the voluntary nature of data provision. It exists in mutual fund research mainly because underperforming funds do not necessarily send their records to data vendors. A self-selection bias may also occur in the context of fund mergers when a fund management company launches two funds at year-end, and decides to merge the underperformed fund with the outperformed fund at the end of the next year. When there is typically 12-month delay before a fund’s records are sent to the administrator of mutual fund database the company may be tempted to provide the full record of the outperformed fund while omitting the data of the underperformed fund. It is therefore likely that companies can sometimes use this opportunity as timing option which creates an obvious potential for upward performance bias.

The practice of data vendors to backfill the return history of funds while adding a new fund to their database creates the fourth form of data-conditioning bias, also known as an instant history bias. A backfilling bias is closely related to self-selection bias, and sometimes these two biases are integrated to each other (e.g., see Deaves, 2004). However, the distinguishing factor between them is that a backfilling bias is caused by the practice of data vendors, whereas a self-selection bias stems from omission of funds. Since underperforming funds are more prone to be excluded from databases than are their outperforming counterparts, the sample of fund records to be backfilled biases average initial performance upwards. Nevertheless, the influence of a backfilling bias on performance persistence is not so clear since initial outperformance during the first recorded year may strengthen the short-term persistence, but on the other hand, it may weaken the longer-term persistence. Therefore, a backfilling bias might give a partial explanation why performance persistence is found more often when relatively short selection and holding periods are employed in research design.

In addition, the research community is tempted to report results that are against market efficiency than results supporting it (for excellent discussion of this tendency, see Black, 1993). Therefore, it is presumable that the results of the studies published in financial journals are biased towards showing performance persistence more often than found in all persistence studies made. It is also clear that many more combinations of selection period and holding periods of various lengths may have been tested than reported in journal articles (The bias of this kind stemming from the behavior of scholars is known as data-snooping bias (e.g., see Lo and MacKinlay, 1990). Data-snooping is also known as data-mining (e.g., see Black, 1993) or data-dredging (e.g., see Fama, 1991) who also introduces the related concepts of model-dredging and factor-dredging which both might bias the aggregate results of persistence studies as well). Thus, the direction of bias is most likely such that results showing no persistence are omitted more often than those showing persistence.

When drawing conclusions from performance persistence studies it must be noted that the results are always sample-specific and can not be generalized as such. First, based on the aggregate results of the studies it is obvious that both the degree and direction of consistency in performance vary over time. There are some time periods of clear evidence of persistence no matter what performance metrics is employed. Correspondingly, there are other time periods for which almost all the performance metrics show no evidence of persistence. On the contrary, results may indicate rather


performance reversal than persistence. The occasional mean-reversion effect documented in stock returns (e.g., see DeBondt and Thaler, 1985, 1987; Fama and French, 1988; Poterba and Summers 1988; Malliaropulos and Priestley, 1999; Balvers et al., 2000; Chaudhuri and Wu, 2004; Balvers and Wu, 2006; Ho and Sears, 2006; Nam et al., 2006) is also reported in several mutual fund studies (e.g., see Jain and Wu, 2000; Prather et al., 2004, for evidence from equity funds, and Jan and Hung, 2003; Polwitoon and Tawatnuntachai, 2006, for evidence from bond funds). Both kind of consistencies described above may arise from the market conditions that often favor some investment strategy over some other until the conditions change. Due to the seasonality in persistence it is very difficult for a mutual fund investor to find outperforming strategy on the basis of past performance.

Moreover, the evidence of persistence varies not only over time periods but also over markets during the same time period. For example, Fletcher and Forbes (2002) find that much of the persistence of U.K. unit trust performance is concentrated in 1980s, while as Malkiel’s (1995) results based on U.S. data show considerable persistence during the 1970s but no persistence during the 1980s. Of course, the contrary results may also be explained by differences in methodologies employed in detecting persistence. The existence of persistence varies also across fund types; for example, for equity and bond funds, the aggregate results are quite diverse, whereas for money markets, the results support quite unanimously performance persistence (e.g., see Dominian and Reichenstein, 1997; Dahlquist et al. 2000; Jan and Hung, 2003) explained by small gross return differences between the money market funds and the dominant role of expense ratio in determining the net return of money market funds.

In addition, the optimal length of selection period on which the selection of fund or fund portfolio is based seems to vary over time and it also seems to depend on not only the moment of decision-making, but also on the methodology used in performance evaluation (e.g., see ter Horst and Verbeek, 2000; Jan and Chiu, 2007). Though the general trend in the research design of the performance persistence studies has been towards shorter selection and holding periods there is no unambiguous proof that shorter selection period would always increase the prediction power of past performance (for the contrary proof, see Allen and Tan, 1999; Blake and Morey, 2000, for example). The most widely-used lengths of selection periods in the studies of the 2000s are one and three years, but quite recently, also selection periods as short as 3 months have been adopted in the studies using daily returns (e.g., see Bollen and Busse, 2005; Busse and Irvine, 2006).

The persistence literature seems to be quite unanimous that if performance persistence exists it is rather short-term phenomenon ranging from one month (e.g., see Goetzmann and Ibbotson ,1994; Harlow and Brown, 2006; Huij and Verbeek, 2007) to one year (e.g., see Hendricks et al., 1993; Philpot et al., 2000; Droms and Walker, 2001a, 2001b; Jan and Hung, 2003, 2004; Polwitoon and Tawatnuntachai, 2006) and in addition, that it can be to large extent explained by persistence in inferior performance (e.g., see Hendricks et al., 1993; Shukla and Trzcinka, 1994; Blake and Morey (2000; Quigley and Sinquefield, 2000; Detzler, 2002). 6. Summary The lively debate on performance persistence of mutual funds continues among both scholars and investment practitioners. The preceding review of persistence studies indicates that the direction of the results often depends on the methodology and the performance model employed, as well as on the sample data and the time period examined. Also the lengths of selection and holding periods affect the results, and there is also inter-dependency between the period lengths and the methodology. The general trend in the research design of the performance persistence studies has been towards shorter selection and holding periods. This tendency coupled with the recent methodological refinements has indisputably increased the proportion of the studies in which performance persistence is documented. However, further evidence from longer time period is required to show that winning funds could be identified ex ante by employing these advanced techniques in performance evaluation. On the other hand, the shorter the holding period, the more difficult it is to economically benefit from performance persistence due to increasing costs of more frequent rebalancing. In addition, there is hardly any evidence that picking only the best-performing fund of the selection period would result in superior performance in the subsequent holding period. At best, the odds to achieve better-than-average


performance during the holding period can be somewhat increased by selecting a portfolio of funds on the basis of past performance.

Furthermore, conventional test procedures employed in persistence studies are subject to many biases that may have implications on inferences about performance persistence. Though the survivorship bias is controlled for almost in every recent persistence study, other biases such as look-ahead bias, self-selection bias, backfilling bias, or data-snooping bias induce more often spurious persistence than spurious non-persistence. Therefore, an investor should be cautious in generalizing the unquestionably abundant evidence of performance persistence of mutual funds. Though taking advantage of past superior performance is cumbersome for mutual fund investor he/she can still benefit from the findings of the persistence literature by avoiding repetitive underperforming funds that have high expense ratios. References [1] Allen, David E., and M.L. Tan, 1999. “A Test of the Persistence in the Performance of UK

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