International Research Journal of Finance and Economics - Issue 34 (2009) 118seems that everyone choosing active managers, from pension plan sponsors to individual investors, putsome weight on past performance in portfolio selection. However, the scholars do not agree on the added-value of the performance evaluation industryfor the community of investors; plenty of studies have found evidence of performance persistence butthere are almost as many studies that have not found it. The topic has fascinated scholars because theexistence of performance persistence would question not only the weak form efficiency of capitalmarkets, but also that of mutual fund markets. This would imply that abnormal profits over randomfund selection might be earned on the basis of past performance records. This paper provides the extensive review to the literature of mutual fund performancepersistence from the very first pioneer studies till the most recent advances in tracking performancepersistence. To my knowledge, this is the most comprehensive literature review ever made of thepersistence studies. Besides a review this paper discusses potential explanations for inconsistentfindings of the abundant literature on performance persistence. Also, the time-varying trends of thepersistence literature are presented. This kind of review of the “lessons learned” from the previouspersistence studies may help scholars to improve the research design and hopefully, also the validity ofthe forthcoming studies. Also the investment practitioners can exploit the conclusions in their decisionson mutual fund selection. Numerous studies that examine performance persistence of institutional portfolios of othertypes, such as pension funds, hedge funds, publicly offered commodity funds, and REIT funds havealso been published in the financial journals. For the sake of proliferation of the overall performancepersistence literature, this paper focuses on relative performance persistence of common open-endmutual funds.2. The Pioneer Studies of Performance PersistenceThe issue of performance persistence is discussed already in the seminal mutual fund studies. Thedistinctive feature of the earlier studies is the use of long selection period and typically holding periodof the same length (see Table 1). Sharpe (1966) compares the performance rank orders based on theSharpe Ratios of two successive decades and finds positive though not statistically significantcorrelation. He also uses the rankings of funds based on the Treynor Ratio computed from the earlierperiod data to predict rankings based on the Sharpe Ratio of the later period but the results remain thesame. Jensen (1968) uses the same lengths of both selection and holding period as Sharpe, butexamines the persistence of abnormal performance determined by the Jensen Alpha. He finds positivecorrelation in the performance between the selection period and the holding period indicating that somefunds may be consistently inferior and others consistently superior. However, Jensen emphasizes thatone must be very careful in interpreting these results so that a fund manager who experienced superiorperformance in the earlier period would be far more likely to experience superior results in the latterperiod. He notes further that positive correlation between these two periods is mainly due topersistence of inferior performance. Carlson (1970) analyzes performance persistence of 57 mutual funds on the basis of the sampledata from the time-period of 1948-1967. Splitting this two-decade data like Sharpe and Jensen, he findsthat the interdecade rankings based on the Sharpe Ratio show no evidence of persistence thoughrankings based on total return or risk (volatility) do so. As a consequence of his findings that broadlydefined investment objectives might influence performance measurement, Carlson (1970) examinesalso smaller sample of 33 funds consisting only of common stock funds but the main results do notchange. Despite the lack of overall consistency in rankings based on the Sharpe Ratio, there appears tobe 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 rankingsbased 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 strongtendency for funds to remain within top or bottom groupings. Sarnat (1972) examines the performance persistence of 56 mutual funds viewing the size of theefficient 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 thecomposition 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 thebasis of total returns from two successive five-year periods and finds no relationship between past andfuture 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). Usingthe data on mutual fund returns for the subperiods of 11 years (1959-69 and 1970-80) the authorsconclude, parallel to the results of Sarnat (1972), that the composition of the efficient sets over time isnot 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 thepersistence 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. Thestudy of Lehmann and Modest (1987) can be considered one of the cornerstone studies of mutual fundperformance evaluation, since this is the first time when multifactor models are used as the basis ofperformance measurement. Although evidence of persistence is found, the authors note that results arehighly dependent on performance metrics employed; the results show considerable differences betweenrankings 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 commonfactors 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).
International Research Journal of Finance and Economics - Issue 34 (2009) 120Table 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. Method for Type of funds Time Length of Length ofAuthors performance and size of period selection holding Results evaluation sample period period Sharpe RatioTreynorSharpe 1966 Ratio for SPa/Sharpe 34 mutual funds 1944–1963 10 years 10 years weak evidence of persistence Ratio for HPbJensen 1968 Jensen Alpha 115 mutual funds 1945–1964 10 years 10 years weak evidence of persistence Treynor Ratio for no persistence based on risk- 57 mutual funds 10 years 10 yearsCarlson 1970 SP/Sharpe Ratio for 1948–1967 adj. performance metrics HP Sharpe Ratio 33 equity funds 5 years 5 years significant persistence no economically exploitable persistence (no improvementSarnat 1972 efficient set approach 56 mutual funds 1946–1969 12 years 12 years compared to the random choice selection) the composition of efficientLevy & Sarnat efficient set approach 100 mutual funds 1959–1980 11 years 11 years sets not better than that based1984 on random choice Appraisal Ratios, evidence of persistence butLehmann & Jensen Alpha & 130 mutual funds 1968–1982 5 years 5 years results are sensitive toModest 1987 several APT alphas performance metrics persistence when using MVRc,Levy & Lerman efficient set approach 100 mutual funds 1959–1980 11 years 1–11 years SSDRd, or TSDRe criteria1988 (riskless asset included)a SP refers to selection periodb HP refers to holding periodc MVR refers to mean-variance efficiency criterion with riskless assetd SSDR refers to the second degree stochastic dominance efficiency criterion with riskless assete 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 theformers to test the predictive power of investment decision criteria that use also information about theriskless asset. While keeping the selection period always at the 11 years, Levy and Lerman vary thelength of the holding period from a maximum of eleven years for entry in 12th year to one year for theultimate year entry. Generally, the results indicate that there is a definite value to using ex postinformation 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 stochasticdominance criterion with riskless asset (SSDR or TSDR criterion, respectively).3. The Studies of the 1990sTable 2 provides an overview of persistence studies of the 1990s and reveals one general trend in theresearch design of the performance persistence studies; i.e., the shift to the use of shorter selectionperiod and holding period compared to those used in the earlier studies carried out in the time periodfrom 1960s to 1980s. Christopherson and Turner (1991) classify managers according to the style and use a singleindex reflecting that style instead of a broad market index in determining the manager alpha (named asstyle index alpha). They conclude that the relationship between alpha over a previous three-year periodand 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 forthe 1981-1990 time period. By comparing the average ranking of the TOP 20 funds for the former
121 International Research Journal of Finance and Economics - Issue 34 (2009)period to their average ranking for the subsequent period he finds no persistence in rankings from oneyear to the next. In the interdecade return comparisons (1971-1980 vs. 1981-1990), the rankings areeven less meaningful Grinblatt and Titman (1992) examine the performance persistence of 279 mutual funds over the1975-1984 period using the methodology based on the eight-portfolio benchmark (P8)2 . A cross-sectionalregression of abnormal returns computed from the last five years of data on abnormal returns computedfrom the first five years of data reveals positive persistence which cannot be explained by inefficiencies inthe 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 metricsnamed as Portfolio Change Measure which evaluates performance on the basis of changes in quarterlyportfolio holdings of 155 funds for the time period 1975-84. The results show strong evidence ofpersistence for the entire sample of funds and weaker evidence of persistence for subsamples ofaggressive growth, growth, and growth-income funds. Therefore, authors conclude that the observedpersistence in performance of the entire sample of funds is not due to consistent outperformance ofaggressive 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 ofthe models used by Blake et al. produce broadly similar ranking of funds, none of them is useful inselecting funds that have higher alphas in subsequent periods. The authors analyze also the largersamples in which the potential survivorship bias were not taken into account and find some evidence ofpredictability.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. Method for Type of funds Time Length of Length of Authors performance and size of period selection holding Results evaluation sample period period Christophersson & style index alphas 177 equity funds –1989 3 years 1–3 years no persistence Turner 1991 equity funds from 330 (1981) to 829 1981–1990 1 year 1 year no persistence Bogle 1992 total returns (1990) 177 equity funds 1971–1990 10 years 10 years no persistence Grinblatt & Titman 8-factor (P8) alpha 279 equity funds 1975–1984 5 years 5 years evidence of persistence 1992 several one-, 3-, 6- 41 non-municipal 1979–1988 5 years 5 years Blake et al. 1993 no persistence index alphas bond funds 1980–1988 3 years 3 years persistence concentrated on inferior Elton et al. 1993 3-index alpha 143 equity funds 1965–1984 10 years 10 years performance Portfolio Change evidence of persistence – weaker Grinblatt & Titman Measure (no 155 mutual funds 1975–1984 56 months 55 months evidence when style differences are 1993 benchmarks required) taken into account 3 months total returns, Sharpe Hendricks et al. 165 U.S. equity 6 months short-term persistence (particularly Ratio, alphas based on 1974–1988 1 year 1993 growth funds 1 year among worst-performing funds) various bechmarks 2 years2 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.
International Research Journal of Finance and Economics - Issue 34 (2009) 122 Method for Type of funds Time Length of Length of Authors performance and size of period selection holding Results evaluation sample period period 1 month 1 month total returns Goetzmann & 1–3 years 1–3 years evidence of persistence at its strongest 728 equity funds 1976–1988 Ibbotson 1994 1 month 1 months on the very short term Jensen Alphas 2 years 2 years total returns, Jensen Alpha, Appraisal equity funds from evidence of persistence within top- Brown & Ratio, 3-index alpha, 372 (1976) to 829 1976–1988 1 year 1 year and worst-performers but also Goetzmann 1995 3-index Appraisal (1988) occasional reversals Ratio, and characteristic return 300 U.S. equity 1988–1993 3 years 3 years ambiguous results total returns, Appraisal funds Kahn & Rudd 1995 Ratio, and selection persistence in risk-adjusted returns 195 bond funds 10/90–9/93 1 yr 5 mos 1 yr 5 mos performance, no persistence in total returns equity funds from mixed results; strong persistence 220 (1971-1972) Malkiel 1995 total returns 1971–1991 1 year 1 year during 1970s, no persistence during to 684 (1990- 1980s 1991) 4-index alpha of Elton 188 U.S. equity evidence of persistence at its strongest Elton et al. 1996 1977–1993 1–3 years 1–3 years et al. (1996) funds using equal lengths of SP and HP total returns strong evidence of persistence 270 common Gruber 1996 4-index alpha of Elton 1985–1994 1–3 years 1–3 years particularly when 4-index alpha is equity funds et al. (1996) used as performance metric on SP a abnormal returns Volkman & Vohar 10/80– persistence over 1- to 3-year HPb based on various 332 funds 1–5 years 1–4 years 1996 12/89 based on 3- and 4-year SP models total returns, Jensen short-term persistence in total returns Alpha, Fama-French 1,892 U.S. equity explained by characteristics of Carhart 1997 1962–1993 1–3 years 1–5 years 3-factor alpha, Carhart funds portfolio holdings and expense 4-factor alpha differences 1 year 1 year no reliable evidence of persistence Phelps & Detzel several multi-index 87 mutual funds 1984–1994 2 years 2 years (occasional persistence observed is 1997 alphas 3 years 3 years explained by style differences) total returns, Sharpe 1 year 1 year Ratio, Treynor Ratio, U.S. equity funds 3 years 3 years weak evidence of persistence Sauer 1997 Jensen Alpha, and the from 249 (1976) 1976–1992 explained by style differences Elton et al. 3-factor to 1,365 (1992) 5 years 5 years alpha weak persistence that deteriorates Detzel & Weigand characteristic-adjusted significantly after adjusting for beta, 61 equity funds 1975–1995 1 year 1 year 1998 returns expense ratios, firm size, and investment style 93 mutual funds no general persistence; inferior with experienced Porter & Trifts 1998 total returns 1986–1995 5 years 5 years performance persists particularly for portfolio funds with high expenses managers 1 year 1 year evidence of persistence total returns, group- 131 U.K. 2 years Allen & Tan 1999 1989–1995 adjusted alpha investment trusts 1 month 1 month no evidence of persistence, but rather 6 months 6 months performance reversal unconditional and 85 U.K. American Fletcher 1999 conditional Jensen 1985–1996 1 year 1 year no evidence of persistence unit trusts Alphasa SP refers to selection periodb 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 theconventional CAPM3. They rank the decile-portfolios from two successive decades and find highlysignificant correlation between these two ranks. Furthermore, a regression of the three-factor alpha of3 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.
123 International Research Journal of Finance and Economics - Issue 34 (2009)the latter period on alpha of the earlier period is significant at the 5 percent level. However, the authorsare 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) examineperformance 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 alsoin the title of this study) to describe the short-term nature of performance persistence; the results show thatfunds that outperform in the most recent year continue to outperform in the near term peaking at theholding period of the same length. Furthermore, funds that perform poorly during the most recent one-yearperiod tend to underperform also in the near future. According to the results, the persistence of inferiorperformance 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, spuriouspersistence, 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-yearperiod (1976-1988). Using total returns and the Jensen alphas as performance measures they examine thepower of various lengths of selection periods to predict the performance measured from holding periods ofthe 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 futureperformance for all time horizons tested. To test robustness of the results over the conjecture whether the performance persistence isrelated more to investment style than skill, Goetzmann and Ibbotson (1994) perform the same tests ona sub-sample that consists only of the relatively homogenous growth funds. The tests indicate that theperformance persistence is not likely to be due to style differences. The study of Goetzmann andIbbotson (1994) is innovative in the sense that for the first time in the mutual fund literature it controlsfor momentum effect; In order to discriminate whether the one-month persistence is due to momentumeffect or a long-term phenomenon (related possibly to risk level), Goetzmann and Ibbotson perform arandomization test, which explicitly uses the long-term mean return to the fund as the control to testwhether the preceding month return has any additional explanatory power. They find the precedingmonth’s ranking to have power to predict the next month’s ranking above and beyond the effectscaused by differences in long-term means. Brown and Goetzmann (1995) examine to what extent the previous-year performance of a fundcan predict the performance of successive year over the 1976-1988 period. The authors use severalalternative performance measures4 and find clear evidence of relative performance persistence butinstead, 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 toconsistent outperformance. In this respect the results are parallel to those of Jensen (1968), Shukla andTrzcinka (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 ofsuccessive year. He finds considerable persistence in fund returns during the 1970s, but no consistencyof them during the 1980s. Similar results are also reported later by Droms and Walker (2001a) whohypothesize that time period dependency may be due to the size anomaly; small-cap stocksoutperformed the S&P 500 during the 1970s, while reverse was true for the 1980s. The results ofDetzel and Weigand (1998) reveal that besides size anomaly, also style characteristics of the stocksheld by equity funds explain the persistence findings for the 1976-1985 period; allowing for themarket-cap of the stocks included in funds’ portfolios and manager investment styles as additionalexplanatory variables, all of the persistence in fund performance disappears. However, the explanatory4 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.
International Research Journal of Finance and Economics - Issue 34 (2009) 124power of size anomaly is not unambiguous; Both Quigley and Sinquefield (2000), using U.K. funddata, and Davis (2001), using U.S. fund data, report persistence explained by the worst-performingsmall-cap funds. Kahn and Rudd (1995) examine performance persistence of both equity and fixed income fundsanalyzing them separately. For equity funds, a selection period of three years is used to predict theperformance of holding period of the same length, while for fixed income funds the correspondinglength of periods is a year and five months for both selection and holding periods. In the case of equityfunds, 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 showsevidence of persistence. In the case of fixed income funds, both regression and contingency tableanalyses 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 followedfrom 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 valuestocks. Furthermore, Elton et al. (1996) refine the EGDH model using differential returns in measuringsize (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 factorsbesides the return on the S&P 500 index and the bond index return. They form decile portfolios offunds based on four measures (i.e., total returns, one- and three-year four-index alpha and the t-statisticof the four-index alpha) and observe how the decile portfolios perform in follow-up period whoseperformance is measured with one- and three-year four-index alpha. For three-year holding period, anyother ranking criteria studied, except for total return, leads to a significant rank correlation. The sameanalysis is repeated with one-year holding period. In this case, ranking techniques involving one yearof past data generally perform much better than those involving 3 years of past data. Similarly to theresults of Hendricks et al. (1993), the fraction portfolios formed on the basis of total return are highlycorrelated with future alpha when alpha is measured over a one-year period, but the relationshipdeteriorates 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 thebasis of a particular selection criterion. Gruber finds strong performance persistence with both one- andthree year horizons and also the four-index alpha’s superiority to forecast future performancedetermined on the basis of either risk-adjusted or raw returns. Volkman and Wohar (1996) analyze the performance persistence of 112 mutual funds over the1980-1989 period. They use three different empirical models to test the performance persistence inrelation to each of 20 combinations of selection periods of 12, 24, 36, 48 and 60 months, and holdingperiods of 12, 24, 36 and 48 months. All three models show persistence in abnormal returns over atwo- 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 thesurvivorship-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 ofmutual funds on lagged one-year returns and estimates performance on the resulting portfolios. Thoughthe results of Carhart strongly support the short-term performance persistence he notes that most of theshort-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).
125 International Research Journal of Finance and Economics - Issue 34 (2009) Using selection periods of one year, three and five years and investment periods of equivalentlength Sauer (1997) finds statistically significant performance persistence in all horizons studied forU.S. equity funds over the 1976-1992 period. Taking account of sporadic evidence of reversion inrelative fund performance during some successive years, the shorter the horizons the strongerpersistence. The same causality is also found for the zero-investment long/short octile portfoliosformed on the basis of the 3-index EGDH alpha. In addition, Sauer examines persistence separately forthe growth and growth and income mutual funds, respectively. When the full sample is partitioned byinvestment objective, the statistically significant persistence in mutual fund performance is no longerevident on five-year horizons. Unfortunately, Sauer does not report the corresponding results withshorter 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 pastalphas for the same performance measures for the subsequent period of equal length. Based on severalempirical tests with the multi-index models with varied number of factors the authors argue that thepositive persistence documented in several studies is the result of persistence in broad equity classes(macropersistence) rather than sustainable managerial ability (micropersistence). In other words, theobserved persistence would result from factors that a generic index as a surrogate for market returncannot adequately capture. Also, according to Detzel and Weigand (1998), fund performancecorresponds to the performance trends of the size and style classes in which funds invest. Employingthe model suggested by Daniel and Titman (1997) that directly relates mutual fund returns to thecharacteristic of the stocks held by funds, the authors find that the adjustment of fund returns for boththe size of the firms in which funds invest, and for financial ratios intended to capture fund managerinvestment styles explains all the persistence in mutual fund performance. Porter and Trifts (1998) examine the performance of 93 experienced fund managers over theten-year period of 1986-1995 using relative percentile ranks based on quarterly compounded, annualtotal returns measured against funds with the same investment objective. The results show that for theexperienced managers studied, superior performance in one five-year period is not predictive ofsuperior performance over the next five years. However, inferior performance persists particularly forfunds with above average expense ratios. Allen and Tan (1999) investigate the performance persistence of 131 U.K. investment trustcompany managers over the 1989-1995 period. The authors examine the prediction ability of both rawreturns and that of style-index alphas for the one-year, half-year and monthly periods. According to theresults, prior one-year performance includes definite information about future performance for theperiods of both one year and two years on the basis of both measures. By contrast, for shorter periodsthe results support performance reversal rather than persistence. Fletcher (1999) examines the performance of a sample of 85 UK American unit trusts usingboth 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 cumulativeexcess returns over the previous year and grouped into quartile portfolios. Equally weighted monthlyexcess returns are then estimated over the next year. Fletcher finds no evidence of the persistence inperformance for this sample of trusts.4. The Studies of the 2000sTable 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 periodand holding period has decreased. Thus, the long-term tendency in the persistence literature towardsusing shorter past data to predict future performance for shorter holding periods has continued also in2000s. Blake and Morey (2000) compares the Morningstar ratings as a predictor of mutual fundperformance to the established performance metrics (i.e., total returns, Sharpe Ratio, Jensen alpha, and
International Research Journal of Finance and Economics - Issue 34 (2009) 1264-index alpha of Elton et al. (1996)). Based on two sample groups for time periods of different lengththe comparison indicates that the Morningstar ratings are in the middle in terms of predicting futureperformance. 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. Forthe shorter sample period based on 3-year selection period the results show somewhat surprisingly thatMorningstar ratings predict the future performance significantly better than the above-mentionedestablished performance metrics. However, after controlling for the fact that for the majority of fundsin the sub-sample employed the Morningstar stars are based on up to 10 years of return data in contrastwith 3-year selection period of performance metrics being compared, the superior ability of theMorningstar 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 returnhistory older than 3 years for the purposes of predicting future performance. The authors conclude thatthe Morningstar rating system is able to "identify" low-performing funds since funds with less thanthree stars generally have much worse future performance than other groups. Instead, only weakevidence that the five-star (highest-rated) funds would outperform the four- and three-star funds isfound. Thus, the Morningstar rating system, like the other established performance metrics, seems tobe more capable in identifying inferior than superior performers of the future due to the persistence inpoor 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 tradesof mutual funds for the 1975-1994 period. Controlling for differences in stock characteristics, theresults generally do not support the persistence of fund performance, although persistence inunadjusted returns on mutual fund portfolio holdings exist. Dahlquist et al. (2000) estimate performance persistence of Swedish mutual funds by treatingprevious-year alphas obtained from various regressions as an attribute of future success. The resultsshow persistence neither for equity nor bond funds, but among money market funds it does exist. Usingmonthly returns of all U.K. equity funds for the 1978-1997 period Quigley and Sinquefield (2000) findevidence 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 throughJune 1996 in Barron’s or Money magazine by comparing pre- and post-advertisement performance ofthese funds. Using four different performance measures6 they find that advertised funds have superiorperformance 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.
127 International Research Journal of Finance and Economics - Issue 34 (2009)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. Method for Type of funds and Time Length of Length of Authors performance size of sample period selection holding Results evaluation period period 1 year evidence of persistence 3 years particularly in inferior 263 U.S. equity funds 1983–1997 10 years Morningstar ratings, performance (the best 5 years Blake & total returns, Sharpe predictor: Sharpe Ratio) Morey Ratio, Jensen Alpha, 4- 1 year evidence of persistence 2000 index alpha of Elton et 3 years particularly in inferior al. (1996) 635 U.S. equity funds 1990–1997 3 years performance (the best 5 years predictor: Morningstar rating) no general persistence using total returns, U.S. mutual funds characteristic-based alphas; Chen et al. characteristic-based from 393 (1975) to 1975–1994 1 year 1 year persistence using unadjusted 2000 alpha of DGTWa (1997) 2,424 (1994) returns explained by momentum effect unconditional and 210 Swedish funds robust persistence among Dahlquist conditional 2-index (126 equity funds, 42 money market funds, no 1993–1997 1 year 1 year et al. 2000 alphas for equity and bond funds, 42 money persistence among other bond funds market funds) funds similar-funds-adjusted Jain & Wu return, S&P 500- 117 mutual funds 7/1993– no persistence among 1 year 1 year 2000 adjusted return, Jensen (recently advertised) 6/1997 recently advertised funds Alpha, 4-factor alpha 73 non-conventional persistence limited to the 1 year 1 year bond funds (high- high-yield bond funds Philpot et Sharpe Ratio yield, global, and 1988–1997 al. 2000 convertible bond 5 years 5 years no persistence funds) Quigley & 1 year 1 year persistence only among total returns, Fama- 311 U.K. equity unit Sinquefiel 1978–1997 worst-performing small-cap French 3-factor alpha trusts (on average) 3 years 3 years d 2000 funds weak evidence of short-term persistence among the best- Davis Fama-French 3-factor 4,686 equity funds 1962–1988 3 years 1 year performing growth funds 2001 alpha and among the worst- performing small-cap funds raw returns Droms & 10 years 10 years no long-term persistence Jensen Alphas Walker 151 U.S. equity funds 1971–1990 2001a 1-3 yrs raw returns 1 year short-term persistence ahead Droms & International equity performance persists over 1- Walker raw returns funds from 11 (1977) 1977–1996 1 year 1-4 years year holding period but not 2001b to 473 (1996) over longer holding periods 1 year 1 year short-term persistence total returns growth and income particularly in growth fund equity funds from 3 years 3 years returns ter Horst Jensen Alpha sample of 2,678 U.S. 1989–1994 evidence of persistence et. al. 2001 equity funds (number of funds within fund among worst-performing 3 years 3 years Carhart 4-factor alpha classes not reported) funds (esp. among income equity funds) 1 year 1 year persistence in total and Group-adjusted returns, Carhart et 2,071 diversified 5 years 5 years group-adjusted returns total returns 1962–1995 al. 2002 equity funds deteriorating after end-of- 3 years 3 years 4-factor alpha sample or look-ahead
International Research Journal of Finance and Economics - Issue 34 (2009) 128 Method for Type of funds and Time Length of Length of Authors performance size of sample period selection holding Results evaluation period period conditioning no evidence of persistence Detzler 4-factor alpha of 423 mutual funds 1990–1996 3 years 1 year among publicly-ranked 2002 Detzler (2002) funds Carhart 4-factor alpha ambiguous; (performance Jensen Alpha reversal based on Fletcher & APT alpha U.K. equity trusts conditional alpha – Forbes from 139 (1982) to 1982–1996 1 year 1 year persistence based on 2002 724 (1996) unconditional alphas but no Conditional alpha persistence based on Carhart alpha) relative excess returns evidence for short-term (over the equally- South African general Collinet & 6 months 6 months persistence (particularly for weighted average return equity unit trusts from 1980–1999 Firer 2003 the 1995–1999 period) of all the funds) 7 (1980) to 43 (1998) Sharpe ratios 3 years 3 years medium term persistence persistence for most equity Jan & 16,345 funds of all efficient set approach 1961–2000 1 year 1 year and money market funds; Hung 2003 type reversal for most bond funds 5-factor model Canadian equity funds short-term persistence; some Deaves 1-5 years conditional CAPM from 110 (1988) to 1988–1998 1 year evidence for medium-term 2004 ahead alpha 300 (1998) persistence Combinatio n of 1-yr & Jan & 3,316 U.S. equity short- and medium-term Carhart 4-factor alpha 1961–2000 3-yr 1 year Hung 2004 funds persistence rankings (lagged) equity funds from Prather et multi-factor alpha 2,124 (1996) to 3,391 1996–2000 1 year 1 year no persistence al. 2004 (1999) Bollen & 230 U.S. equity funds Busse Carhart 4-factor alpha (new funds after 1985 1985–1995 3 months 3 months very short-term persistence 2005 not added) Morningstar ratings/Sharpe Ratio, no persistence among the Morey Jensen Alpha, 4-factor 4/1987– funds upgraded for the first 273 U.S. equity funds 3 years 3 years 2005 alphas of both Elton et 6/2000 time to five-star funds by al. (1996) and Carhart Morningstar (1997) various multi-factor 1 year Busse & 230 U.S. equity funds short-term persistence alphas (Bayesian) for 3 months Irvine (new funds after 1985 1985–1995 3 months particularly by using annual SP; standard multi- 2006 not added) 3 years selection period factor alphas for HP Harlow & U.S. equity funds 1 month strong persistence for 1- Fama-French 3-factor Brown from 131 (1981) to 1979–2003 3 years 3 months month and 3-month holding alpha 2006 5,614 (2003) 1 year periods 1 year persistence among growth- U.S. equity funds Kosowski oriented funds; non- Carhart 4-factor alpha from 231 (1971-1975) 1975–2002 1 year et al. 2006 3 years persistence among income- to 1,788 (1975-2002) oriented funds Polwitoon raw returns 1 year mixed results; persistence global bond funds & for some consecutive years – from 103 (2003) to 1993–2004 1 year Tawatnunt Sharpe Ratios 3 years reversal for some other 183 (1997) achai 2006 consecutive years short-term performance Huij & U.S. equity funds Carhart 4-factor alpha persists but varies across Verbeek from 362 (1984) to 1984-2003 1 year 1 month (Bayesian) styles (strongest for small 2007 4,973 (2003) cap/growth funds)a DGTW refers to the method introduced by Daniel, Grinblatt, Titman & Wermers (1997)
129 International Research Journal of Finance and Economics - Issue 34 (2009) 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 ofshort-term performance persistence for the high-yield bond fund sub-sample, but no persistence for thegeneral class or for other classes of funds. The persistence found on the basis of one-year SharpeRatios disappears, as the selection period is extended to five years and the sample period examined isdivided into two sub-periods of the equal length. Davis (2001) examines the relationship between equity fund performance and manager style byemploying the Fama-French (1993) alpha as performance metrics. Particularly, Davis addresseswhether any particular investment style reliably delivers abnormal performance and furthermore,whether any evidence of performance persistence can be found when funds with similar styles arecompared. Davis does not find positive abnormal returns over the 1965-1998 period although he doesfind 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 Goetzmannand Ibbotson (1994), Brown and Goetzmann (1995), and Malkiel (1995) to test for performancepersistence among equity mutual funds over the two decades from 1971 to 1990. The results show nolong-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 ofBrown and Goetzmann (1995), and Malkiel (1995), the persistence is more pronounced during the firstdecade of the 1970s than the 1980s. Droms and Walker (2001b) follows the same type of methodology also on another study that testsfor short-term performance persistence in international equity mutual funds over the 20-year period from1977 to 1996. Using annual returns as performance measures, Droms and Walker (2001b) find statisticallysignificant performance persistence for 1-year holding periods, but no persistence for 2-, 3- or 4-yearperiods. The similar conclusions are also drawn by ter Horst et al. (2001) who examine the impacts ofsurvivorship bias and look-ahead bias with the sample of U.S. growth and income equity funds for the1989-1994 period. For 3-year selection period and holding period the results show evidence of risk-adjustedperformance 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 Carhartet al. (2002) find persistence in the performance of U.S. mutual funds. Employing three differentperformance metrics7 the authors undertake Hendricks, Patel and Zeckhauser’s (1997) test for spuriouspersistence 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 aninvestment strategy based on mutual fund rankings by the popular press (Barron’s, Business Week andForbes). The results show that rankings correspond to higher returns 3, 6, and 12 months before thepublication dates of rankings, but the funds do not have superior performance in the post-rankingperiods of equal lengths. Furthermore, the ranked funds have often higher risk than their non-rankedpeers in both the pre-ranking and post-ranking periods, suggesting that funds receiving rankings mayalso be risk-takers. The 4-factor alpha9 shows that the funds with rankings have higher risk-adjustedperformance during the pre-ranking period and negative performance in the post-ranking periodproviding evidence against persistence. Thus, the results are very much consistent with the findings ofJain 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.
International Research Journal of Finance and Economics - Issue 34 (2009) 130 Fletcher and Forbes (2002) find evidence of persistence in UK unit trust performance whenperformance is determined by means of factor models based on the CAPM or APT. However, whenperformance 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 thatthe 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 unittrusts from 1980 to 1999 using the relative excess returns (over the equally-weighted mean return of allthe funds in existence during the period) as a performance measure. The authors find evidence ofpersistence when the selection of funds for 6-month holding period is based on performance from theselection period of 6-12 months. According to the results, persistence is particularly evident during the1995–1999 period using 6-month selection period. However, even within this period, there are caseswhere 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 strongpersistence is found over certain periods, the results are very sensitive to variations in both the endingdate 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 winnerand loser portfolios based on one-year raw returns and testing the efficiency of these portfolios offunds the authors find that persistence exists among 13 out of 24 fund categories examined. On theother hand, evidence of performance reversal is found among 7 fund categories. According to theresults, persistence is more common among equity funds while reversal is typical in most bond fundcategories. Another study of Jan and Hung (2004), using the same time period but somewhat smallersample of the same database, hypothesize that if mutual fund performance persists in the short run, itshould also persist in the long run. A division of the funds in the database on the basis of past 4-factoralpha 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. Theauthors conclude that mutual fund investors can likely benefit from selecting funds on the basis of notonly past short-run performance but also past long-run performance. Deaves (2004) examines performance persistence of Canadian equity funds on the basis ofseveral performance measures. Using carefully constructed bias-free sample for the 1988-1998 periodhe finds evidence of short-term persistence at its strongest when one-year selection period is used topredict next year’s performance. Prather et al. (2004) analyze the impact of numerous fund-specific characteristic onperformance of equity funds. The analysis includes 25 individual fund factors or characteristics withinthe four broad categories of popularity, growth, cost and management. For the 1996-2000 period, theyfind 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 abnormalreturns that persist for the following quarter. The results are robust across stock selection, markettiming, and mixed strategy models, which suggests that misspecification of the performance model isnot the reason for evidence of persistence. However, the authors note that the economic significance ofthe post-ranking abnormal returns is questionable given the transaction costs and taxes levied on astrategy capturing the persistent abnormal returns of the top decile. Morey (2005) examines the performance persistence of U.S. equity funds that have justreceived their first 5-star rating from Morningstar. During the 3-year period following the ratingupgrade performance deteriorates dramatically in spite of the performance metrics used in evaluatingperformance of holding period. In this sense, the results are parallel to those of Detzler (2002).
131 International Research Journal of Finance and Economics - Issue 34 (2009)Morey’s results are also robust across different sub-samples of funds (i.e., samples of actively managedfunds 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), andexamine performance persistence both within these fund classes and in the aggregate level. Based onthe three-year selection period, the results indicate a strong degree of performance persistence in theactive U.S. equity fund sample for holding periods up to one year. The authors state that persistence isparticularly strong and highly statistically significant in the near short-term, i.e. for time periods of onemonth and three months. Applying a new bootstrap technique to the monthly net returns of the universe of U.S. equity fundsduring the 1975-2002 period, Kosowski et al. (2006) find strong evidence of superior performance andperformance persistence among growth-oriented funds, but no corresponding evidence of income-orientedfunds. They rank funds using the unconditional four-factor alpha measured over one and three years prior toone-year holding period. Polwitoon and Tawatnuntachai (2006) examine performance persistence of US-based globalbond funds during the period of 1993–2004. Following the methodology of Elton et al. (1996) fundsare ranked on the basis of 1- and 3-year raw returns and 1- and 3-year Sharpe Rratios prior tosubsequent 1-year holding period. The results show that persistence is stronger using shorter selectionperiod, i.e., 1 year instead of 3 years. Although some evidence of performance persistence amongglobal bond funds is found, and the rank correlation is significant for all years, it is negative in 5 out of11 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 Bakset 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 informationrelated to such issues as funds’ expenses, investors’ beliefs about managerial skills, benchmark pricingabilities, or the returns on other mutual funds and benchmark factors, in the resulting estimates. Suchan approach can be motivated both by cross-sectional learning of investors (as noted by Jones andShanken 2005) and on the basis of statistical arguments only. The results of the studies applying theBayesian approach are promising since the superior prediction power of Bayesian alphas over standardOLS alphas is documented most often. Using daily returns of 230 U.S. equity funds and the Bayesian approach suggested by Pástor andStambaugh (2002b)10, Busse and Irvine (2006) compare the performance predictability of Bayesian alphaswith standard frequentist measures. When the returns on passive nonbenchmark assets are correlated withfund holdings, incorporating histories of these returns in a Bayesian framework produces alphas that predictfuture 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 topredict subsequent standard quarterly alphas. Also, the other selection periods tested (i.e., one quarter andthree years) show evidence of prediction power. Of Bayesian alphas based on various performance modelsthe best is that of the Carhart 4-factor model. However, the predictive accuracy of Bayesian alphas is in most studies greatly affected by theinvestor’s prior belief about managerial skill. Huij and Verbeek (2007) apply the Bayesian approach sothat it does not require investors to explicitly formulate their beliefs about managerial skill (i.e. theprior), or to make assumptions about cross-sectional characteristics that drive performance. This isdone by incorporating the large cross-section of mutual fund alphas in measuring the skill of anindividual fund manager. The basic principle is to allow the prior to learn across other funds includedin the sample, in which case the resulting belief in managerial skill is no longer fully subjective, butinstead, 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 period10 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.
International Research Journal of Finance and Economics - Issue 34 (2009) 1321984–2003. They find that when funds are sorted into decile portfolios based on 12-month rankingperiods, the top decile of funds earns a statistically significant, abnormal return of 0.26 percent in thefirst month after ranking. This effect is robust to load fees that are involved with a strategy of chasingwinners. Furthermore, their results show that persistence varies across investment styles and it ismainly concentrated in relatively young, small cap/growth funds.5. Concluding RemarksThe preceding review of performance persistence literature reveals that plenty of studies have beenpublished both for and against the prediction power of past performance. The results of previousstudies 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 differentmethodology 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 performancepersistence. For example, comparing performance differences between quantile portfolios may result incontrary conclusions than employing the rank correlation test for the same sample. Another source of bias that may affect the inferences on performance persistence stems fromperformance model employed. In most cases, when the performance model takes account ofdifferences in portfolio characteristics, the evidence of persistence usually deteriorates, and in somecases vanishes completely. Adding other factors such as size, book-to-market, or momentum besidesgeneral market factor into the performance model may change the results drastically. E.g., the results ofCarhart (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. Forexample, in the second half of 1990s many funds followed either value or growth strategy. Had stylebias not been taken into account in the performance model, the chances that a value-oriented fundwould have outperformed a growth-oriented fund were very low. Correspondingly, in the beginning ofthe ongoing millennium the case has been contrary. Unfortunately, style bias cannot be completelycircumvented by employing performance metrics (such as the Sharpe Ratio, for example) that are notbased any benchmarks. Pätäri (2008) compares an extensive set of performance metrics that are basedon both full-scale and partial-scale measures of risk (i.e., measures of downside risk) derived from aportfolio’s own return distribution without using any benchmarks. The results show that due to theasymmetries of return distributions the relative performance of funds depends on a risk measureemployed. It is highly probable that the sensitivity of total-risk based performance rankings to theselection 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 thatapproach can not protect from another source of bias. While style bias stems from performance metricsemployed, 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 statedinvestment policies of mutual funds (e.g., see diBartolomeo and Witkowski, 1997; Brown andGoetzmann, 1997; Kim et al., 2000; Castellanos and Alonso, 2005; Detzel, 2006). According to theresults the average divergence rate ranges from 33 per cent to as high as 50 per cent within some fundcategories. Therefore, the fact that very many mutual funds are benchmarked against irrelevant factorsmay induce spurious persistence. As noted by several scholars, performance persistence studies are prone to several biases thatstems from ex-post conditioning of data. The most well-known of these is survivorship bias that stemsfrom including only the funds that exist at the end of sample period. Though the survivorship bias isquite often offered as an explanation for the results supporting performance persistence the opinions onthe degree of the impact of survivorship bias on the results of persistence studies vary strongly amongscholars (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
133 International Research Journal of Finance and Economics - Issue 34 (2009)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 induceperformance 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 ofperformance persistence. A common methodology in performance persistence studies is to rank fundsand assign them to fraction portfolios on the basis of their performance from the preceding selectionperiod. Look-ahead bias arises because funds disappear in non-random way during the selection periodor holding period, i.e., the attrition rate of funds within fraction portfolios is not stable. Thus, anessential 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 inmutual fund persistence studies the recent studies indicate that look-ahead bias is not very severe insamples 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 voluntarynature of data provision. It exists in mutual fund research mainly because underperforming funds donot necessarily send their records to data vendors. A self-selection bias may also occur in the context offund mergers when a fund management company launches two funds at year-end, and decides to mergethe underperformed fund with the outperformed fund at the end of the next year. When there istypically 12-month delay before a fund’s records are sent to the administrator of mutual fund databasethe company may be tempted to provide the full record of the outperformed fund while omitting thedata of the underperformed fund. It is therefore likely that companies can sometimes use thisopportunity 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 totheir 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 areintegrated to each other (e.g., see Deaves, 2004). However, the distinguishing factor between them isthat a backfilling bias is caused by the practice of data vendors, whereas a self-selection bias stemsfrom omission of funds. Since underperforming funds are more prone to be excluded from databasesthan are their outperforming counterparts, the sample of fund records to be backfilled biases averageinitial performance upwards. Nevertheless, the influence of a backfilling bias on performancepersistence is not so clear since initial outperformance during the first recorded year may strengthen theshort-term persistence, but on the other hand, it may weaken the longer-term persistence. Therefore, abackfilling bias might give a partial explanation why performance persistence is found more oftenwhen relatively short selection and holding periods are employed in research design. In addition, the research community is tempted to report results that are against marketefficiency 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 biasedtowards showing performance persistence more often than found in all persistence studies made. It isalso clear that many more combinations of selection period and holding periods of various lengths mayhave been tested than reported in journal articles (The bias of this kind stemming from the behavior ofscholars is known as data-snooping bias (e.g., see Lo and MacKinlay, 1990). Data-snooping is alsoknown as data-mining (e.g., see Black, 1993) or data-dredging (e.g., see Fama, 1991) who alsointroduces the related concepts of model-dredging and factor-dredging which both might bias theaggregate results of persistence studies as well). Thus, the direction of bias is most likely such thatresults showing no persistence are omitted more often than those showing persistence. When drawing conclusions from performance persistence studies it must be noted that theresults are always sample-specific and can not be generalized as such. First, based on the aggregateresults of the studies it is obvious that both the degree and direction of consistency in performance varyover time. There are some time periods of clear evidence of persistence no matter what performancemetrics is employed. Correspondingly, there are other time periods for which almost all theperformance metrics show no evidence of persistence. On the contrary, results may indicate rather
International Research Journal of Finance and Economics - Issue 34 (2009) 134performance reversal than persistence. The occasional mean-reversion effect documented in stockreturns (e.g., see DeBondt and Thaler, 1985, 1987; Fama and French, 1988; Poterba and Summers1988; Malliaropulos and Priestley, 1999; Balvers et al., 2000; Chaudhuri and Wu, 2004; Balvers andWu, 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 consistenciesdescribed above may arise from the market conditions that often favor some investment strategy oversome other until the conditions change. Due to the seasonality in persistence it is very difficult for amutual 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 thesame time period. For example, Fletcher and Forbes (2002) find that much of the persistence of U.K. unit trustperformance is concentrated in 1980s, while as Malkiel’s (1995) results based on U.S. data show considerablepersistence during the 1970s but no persistence during the 1980s. Of course, the contrary results may also beexplained by differences in methodologies employed in detecting persistence. The existence of persistencevaries 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 Dominianand Reichenstein, 1997; Dahlquist et al. 2000; Jan and Hung, 2003) explained by small gross return differencesbetween the money market funds and the dominant role of expense ratio in determining the net return of moneymarket funds. In addition, the optimal length of selection period on which the selection of fund or fund portfolio isbased seems to vary over time and it also seems to depend on not only the moment of decision-making, but alsoon 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 shorterselection and holding periods there is no unambiguous proof that shorter selection period would always increasethe 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 andthree years, but quite recently, also selection periods as short as 3 months have been adopted in the studies usingdaily 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 itis 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 andTawatnuntachai, 2006) and in addition, that it can be to large extent explained by persistence in inferiorperformance (e.g., see Hendricks et al., 1993; Shukla and Trzcinka, 1994; Blake and Morey (2000;Quigley and Sinquefield, 2000; Detzler, 2002).6. SummaryThe lively debate on performance persistence of mutual funds continues among both scholars andinvestment practitioners. The preceding review of persistence studies indicates that the direction of theresults often depends on the methodology and the performance model employed, as well as on thesample data and the time period examined. Also the lengths of selection and holding periods affect theresults, and there is also inter-dependency between the period lengths and the methodology. Thegeneral trend in the research design of the performance persistence studies has been towards shorterselection and holding periods. This tendency coupled with the recent methodological refinements hasindisputably 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 beidentified ex ante by employing these advanced techniques in performance evaluation. On the otherhand, the shorter the holding period, the more difficult it is to economically benefit from performancepersistence due to increasing costs of more frequent rebalancing. In addition, there is hardly anyevidence that picking only the best-performing fund of the selection period would result in superiorperformance in the subsequent holding period. At best, the odds to achieve better-than-average
135 International Research Journal of Finance and Economics - Issue 34 (2009)performance during the holding period can be somewhat increased by selecting a portfolio of funds onthe basis of past performance. Furthermore, conventional test procedures employed in persistence studies are subject to manybiases that may have implications on inferences about performance persistence. Though thesurvivorship 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 spuriouspersistence than spurious non-persistence. Therefore, an investor should be cautious in generalizing theunquestionably abundant evidence of performance persistence of mutual funds. Though takingadvantage of past superior performance is cumbersome for mutual fund investor he/she can still benefitfrom the findings of the persistence literature by avoiding repetitive underperforming funds that havehigh expense ratios.References Allen, David E., and M.L. Tan, 1999. “A Test of the Persistence in the Performance of UK Managed Funds”, Journal of Business Finance and Accounting 26, pp. 559-593. Baks, Klaas P., Andrew Metrick, and Jessica Wachter, 2001. “Should Investors Avoid All Actively Managed Mutual Funds? A Study in Bayesian Performance Evaluation”, Journal of Finance, 56, pp. 45–85. Balvers, Ronald J., Yangru Wu, and Erik Gilliland, 2000. “Mean Reversion across National Stock Markets and Parametric Contrarian Investment”, Journal of Finance 55, pp. 745-772. Balvers, Ronald J., and Yangru Wu, 2006. “Momentum and Mean Reversion across National Equity Markets”, Journal of Empirical Finance 13, pp. 24-48. Bergstresser, David and James M. Poterba, 2002. “Do After-Tax Returns Affect Mutual Fund Inflows?”, Journal of Financial Economics 63, pp. 381-414. Black, Fischer, 1993, “Beta and Return”, Journal of Portfolio Management 20, pp. 8-18. Blake, Cristopher R., Edwin J. Elton, and Martin J. Gruber, 1993. “The Performance of Bond Mutual Funds”, Journal of Business 66, pp. 371 403. Blake, Cristopher R., and Matthew R. Morey, 2000. “Morningstar Ratings and Mutual Fund Performance”, Journal of Financial and Quantitative Analysis 35, pp. 451-483. Bodie, Zvi, Alex Kane and Alan J. Marcus, 2005. Investments, Singapore. Bogle, John C., 1992. “Selecting Equity Mutual Funds”, Journal of Portfolio Management 18, pp. 94–100. Bollen, Nicolas P., and Jeffrey A. Busse, 2005. “Short-term Persistence in Mutual Fund Performance”, Review of Financial Studies 18, pp. 569–597. Brown, Stephen J., and William N. Goetzmann, 1995. “Performance Persistence”, Journal of Finance 50, pp. 679 698. Brown, Stephen J., and William N. Goetzmann, 1997. “Mutual Fund Styles”, Journal of Financial Economics 43, pp. 373 399. Brown, Stephen J., William N. Goetzmann, Roger G. Ibbotson, and Stephen A. Ross, 1992. “Survivorship Bias in Performance Studies”, Review of Financial Studies 5, pp. 553-580. Busse, Jeffrey A., and Paul J. Irvine, 2006. “Bayesian Alphas and Mutual Fund Persistence”, Journal of Finance 61, pp. 2251–2288. Carhart, Mark M, 1997. “On Persistence in Mutual Fund Performance”, Journal of Finance 52, pp. 57-82. Carhart, Mark M., Jennifer N. Carpenter, Anthony W. Lynch, and David K. Musto, 2002. “Mutual Fund Survivorship”, Review of Financial Studies 15 pp. 1439-1463. Carlson, Robert S., 1970. “Aggregate Performance of Mutual Funds 1948 1967”, Journal of Financial and Quantitative Analysis 5, pp. 1-32. Carpenter, Jennifer N., and Anthony W. Lynch, 1999. “Survivorship Bias and Attrition Effects in Measures of Performance Persistence”, Journal of Financial Economics 54, pp. 337-374.
International Research Journal of Finance and Economics - Issue 34 (2009) 136 Castellanos, Arturo R., and Belén V. Alonso, 2005. “Spanish Mutual Fund Misclassification: Empirical Evidence”, Journal of Investing 14, pp. 41-48. Chaudhuri, Kausik, and Yangru Wu, 2004. “Mean Reversion in Stock Prices: Evidence from Emerging Markets”, Managerial Finance 29, pp. 22-37. Chen, Hsiu-Lang, Narasimhan Jegadeesh, and Russ Wermers, 2000. “The Value of Active Mutual Fund Management: An Examination of the Stockholdings and Trades of Fund Managers”, Journal of Financial and Quantitative Analysis 35, pp. 343-368. Christopherson, Jon A., and Andrew L. Turner, 1991. “Volatility and Predictability of Manager Alpha”, Journal of Portfolio Management 18, pp. 5-12. Collinet, Lance, and Collin Firer, 2003. “Characterising Persistence of Performance amongst South African General Equity Unit Trusts”, Omega 31, pp. 523-538. Dahlquist, Magnus, Stefan Engström, and Paul Söderlind, 2000. “Performance and Characteristics of Swedish Mutual Funds.” Journal of Financial and Quantitative Analysis 35, pp. 409-423. Daniel, Kent, Mark Grinblatt, Sheridan Titman, and Russ Wermers, 1997. “Measuring Mutual Fund Performance with Characteristic-Based Benchmarks”, Journal of Finance 52, pp. 1035- 1058. Daniel, Kent, and Sheridan Titman, 1997. “Evidence on the Characteristics of Cross Sectional Variation in Stock Returns”, Journal of Finance 52, pp. 1-33. Davis, James L., 2001. “Mutual Fund Performance and Manager Style”, Financial Analysts Journal 57, pp. 19-27. Deaves, Richard, 2004. “Data-conditioning Biases, Performance, Persistence and Flows: The Case of Canadian Equity Funds”, Journal of Banking and Finance 28, pp. 673-694. DeBondt, Werner F.M., and Richard H. Thaler, 1985. “Does the Stock Market Overreact?/Discussion”, Journal of Finance 40, pp. 793-805. DeBondt, Werner F.M., and Richard H. Thaler, 1987. “Further Evidence on Investor Overreaction and Stock Market Seasonality”, Journal of Finance 42, pp. 557 581. Detzel, F. Larry, 2006. “Determining a Mutual Fund’s Equity Class”, Financial Services Review 15, pp. 199-212. Detzel, F. Larry, and Robert A. Weigand, 1998. “Explaining Persistence in Mutual Fund Performance”, Financial Services Review 7, pp. 45-55. Detzler, Miranda L, 2002. “The Value of Mutual Fund Rankings to the Individual Investor”, Journal of Business and Economic Studies 8, pp. 48-72. diBartolomeo, Dan, and Erik Witkowski, 1997. “Mutual Fund Misclassification: Evidence Based on Style Analysis”, Financial Analysts Journal 54, pp. 32-43. Domian, Dale L., and William Reichenstein, 1997. “Performance Persistence in Money Market Fund Returns”, Financial Services Review 6, pp. 169-183. Droms, William G., and David A. Walker, 2001a. “Persistence of Mutual Fund Operating Characteristics: Returns, Turnover Rates, and Expense Ratios”, Applied Financial Economics 11, pp. 457-466. Droms, William G., and David A. Walker, 2001b. “Performance Persistence of International Mutual Funds”, Global Finance Journal 12, pp. 237-238. Edelen, Roger M., 1999. “Investor Flows and the Assessed Performance of Open-end Mutual Funds”, Journal of Financial Economics 53, pp. 439-466. Elton, Edwin J., Martin J. Gruber, and Christopher R. Blake, 1996. “The Persistence of Risk- Adjusted Mutual Fund Performance”, Journal of Business 69, pp. 133-158. Elton, Edwin J., Martin J. Gruber, Sanjiv Das, and Matthew Hlavka, 1993. “Efficiency with Costly Information: A Reinterpretation of Evidence from Managed Portfolios”, Review of Financial Studies 6, pp. 1-22. Fama, Eugene F., 1991. “Efficient Capital Markets: II”, Journal of Finance 46, pp. 1575-1617.
137 International Research Journal of Finance and Economics - Issue 34 (2009) Fama, Eugene F., and Kenneth R. French, 1988. “Permanent and Temporary Components of Stock Prices”, Journal of Political Economy 96, pp. 246-273. Fama, Eugene F., and Kenneth R. French, 1992. “The Cross-section of Expected Stock Returns”, Journal of Finance 47, pp. 427-465. Fama, Eugene F., and Kenneth R. French, 1993. “Common Risk Factors in the Returns on Stocks and Bonds”, Journal of Financial Economics 33, pp. 3-56. Fama, Eugene F., and Kenneth R. French, 1996. “Multifactor Explanations of Asset Pricing Anomalies”, Journal of Finance 51, 55-84. Ferson Wayne E., and Rudi W. Schadt, 1996. “Measuring Fund Strategy and Performance in Changing Economic Conditions”, Journal of Finance 51, pp. 425-461. Fletcher, Jonathan, 1999. “The Evaluation of the Performance of UK American Unit Trusts”, International Review of Economics and Finance 8, pp. 455–466. Fletcher, Jonathan, and David Forbes, 2002. “An Exploration of the Persistence of UK Unit Trust Performance”, Journal of Empirical Finance 9, pp. 475-493. Goetzmann William N., and Roger G. Ibbotson, 1994. “Do Winners Repeat? Pattern in Mutual Fund Performance”, Journal of Portfolio Management 20, pp. 9-17. Goetzmann William N., and Nadav Peles, 1997. “Cognitive Dissonance and Mutual Fund Performance”, Journal of Financial Research 20, pp. 145-158. Grinblatt, Mark, and Sheridan Titman, 1989. “Mutual Fund Performance: An Analysis of Quarterly Portfolio Holdings”, Journal of Business 62, pp. 393-416. Grinblatt, Mark, and Sheridan Titman, 1992. “The Persistence of Mutual Fund Performance”, Journal of Finance 47, pp. 1977-1984. Grinblatt, Mark, and Sheridan Titman, 1993. “Performance Measurement without Benchmarks: an Examination of Mutual Fund Returns”, Journal of Business 66, pp. 47-68. Grinold, Richard C. & Ronald N. Kahn, 1995. Active Portfolio Management: Quantitative Theory and Applications, Chicago: Illinois. Gruber, Martin J., 1996. “Presidential Address: Another Puzzle: The Growth in Actively Managed Mutual Funds”, Journal of Finance 51, pp. 783-810. Harlow, W. Van, and Keith C. Brown, 2006. “The Right Answer to the Wrong Question: Identifying Superior Active Portfolio Management”, Journal of Investment Management 4, pp. 1-26. Hendricks Darryll, Jayendu Patel, and Richard J. Zeckhauser, 1993. “Hot Hands in Mutual Funds; Short-Run Persistence of Relative Performance 1974-1988”, Journal of Finance 48, pp. 93-130. Hendricks Darryll, Jayendu Patel, and Richard J. Zeckhauser, 1997. “The J-Shape of Performance Persistence Given Survivorship Bias”, Review of Economics and Statistics 79, pp. 161-166. Ho, Chia-Cheng, and R. Stephen Sears, 2006. “Is There Conditional Mean Reversion in Stock Returns?” Quarterly Journal of Business and Economics 45, pp. 91-112. ter Horst, Jenke R., Theo E. Nijman, and Marno Verbeek, 2001. “Eliminating Look-Ahead Bias in Evaluating Persistence in Mutual Fund Performance”, Journal of Empirical Finance 8, pp. 345–373. ter Horst, Jenke R. and Marno Verbeek, 2000. “Estimating Short-Run Persistence in Mutual Fund Performance”, Review of Economics and Statistics 82, pp. 646–655. Huij, Joop, and Marno Verbeek, 2007. “Cross-Sectional Learning and Short-Run Persistence in Mutual Fund Performance”, Journal of Banking and Finance 31, pp. 973-997. Ippolito Richard A., 1992. “Consumer Reaction to Measures of Poor Quality: Evidence from the Mutual Fund Industry”, Journal of Law and Economics 35, pp. 45-70. Jain, Prem C., and Johanna S. Wu, 2000. “Truth in Mutual Fund Advertising: Evidence on Future Performance and Fund Flows”, Journal of Finance 55, pp. 937-958.
International Research Journal of Finance and Economics - Issue 34 (2009) 138 Jan, Yin-Ching and Su-Ling Chiu, 2007. “On the Robustness of Performance Measures in Fund Persistence”, Journal of Performance Measurement 11, pp. 44-50. Jan, Yin-Ching, and Mao-Wei Hung, 2003. “Mutual Fund Attributes and Performance”, Financial Services Review 12, pp. 165-178. Jan, Yin-Ching, and Mao-Wei Hung, 2004. “Short-Run and Long-Run Persistence in Mutual Funds”, Journal of Investing 13, pp. 67-71. Jegadeesh, Narasimhan, and Sheridan Titman, 1993. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency”, Journal of Finance 48, pp. 65-91. Jensen, Michael C., 1968. “The Performance of Mutual Funds in the Period 1945-1964”, Journal of Finance 23, pp. 389-416. Jones, Christopher S., and Jay Shanken, 2005. “Mutual Fund Performance with Learning across Funds”, Journal of Financial Economics 78, pp. 507-522. Kahn, Ronald N., and Andrew Rudd, 1995. “Does Historical Performance Predict Future Performance?” Financial Analysts Journal 51, no. 6, pp. 43-52. Kim, Moon, Ravi Shukla, and Michael Tomas, 2000. “Mutual Fund Objective Misclassification”, Journal of Economics and Business 52, pp. 309-323. Kosowski, Robert, Allan Timmermann, Russ Wermers, and Hal White, 2006. “Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis”, Journal of Finance 61, pp. 2551–2595. Kritzman, Mark, 1983. “Can Bond Managers Perform Consistently?” Journal of Portfolio Management 9, pp. 54-56. Lehmann, Bruce N., and David M. Modest, 1987. “Mutual Fund Performance Evaluation: A Comparison of Benchmarks and Benchmark Comparisons”, Journal of Finance, 42, pp. 233- 265. Levy, Haim, and Zvi Lerman, 1988. “Testing the Predictive Power of Ex Post Efficient Portfolios”, Journal of Financial Research 11, pp. 241 254. Levy, Haim, and Marshall Sarnat, 1984. “Portfolio and Investment Selection: Theory and Practice”, Englewood Cliffs: New Jersey, (1984). Lo, Andrew W., and A. Craig MacKinlay, 1990. “Data Snooping Biases in Tests of Financial Asset Pricing Models”, Review of Financial Studies 3, pp. 431 467. Lunde, Asger, Allan Timmermann, and David Blake, 1999. “The Hazards of Mutual Fund Underperformance: A Cox Regression Analysis”, Journal of Empirical Finance 6, pp. 121-152. Malkiel, Burton G., 1995. “Returns from Investing in Equity Mutual Funds 1971 to 1991”, Journal of Finance 50, pp. 549-572. Malliaropulos, Dimitrios, and Richard Priestley, 1999. “Mean Reversion in Southeast Asian Stock Markets”, Journal of Empirical Finance 6, pp. 355-384 Morey, Matthew R., 2005. “The Kiss Of Death: A 5-Star Morningstar Mutual Fund Rating?”, Journal of Investment Management 3, pp. 41-52. Nam, Kiseok, Sei-Wan Kim, and Augustine C. Arize, 2006. “Mean Reversion of Short-Horizon Stock Returns: Asymmetry Property”, Review of Quantitative Finance and Accounting 26, pp. 137-163. Pástor, Lubos, and Robert F. Stambaugh, 2002a. “Investing in Equity Mutual Funds”, Journal of Financial Economics 63, pp. 351–380. Pástor, Lubos, and Robert F. Stambaugh, 2002b. “Mutual Fund Performance and Seemingly Unrelated Assets”, Journal of Financial Economics 63, pp. 315–349. Patel, Jayendu, Richard J. Zeckhauser, and Darryll Hendricks, 1994. “Investment Flows and Performance: Evidence from Mutual Funds, Cross-Border Investments, and New Issues”, In: Sato, R., Levich, R. & Ramachanday, R. V. (Eds.), Japan, Europe and International Financial Markets: An Analytical and Empirical Perspective, Cambridge: England, pp. 34-48. Phelps, Shawn, and F. Larry Detzel, 1997. “The Nonpersistence of Mutual Fund Performance”, Quarterly Journal of Business and Economics 36, pp. 55-69.
139 International Research Journal of Finance and Economics - Issue 34 (2009) Philpot, James, Douglas Hearth, and James Rimbey, 2000. “The Performance Persistence and Manager Skill in Non-Conventional Bond Mutual Funds”, Financial Services Review 9, pp. 247-258. Polwitoon, Sirabat, and Oranee Tawatnuntachai, 2006. “Diversification Benefits and Persistence of US-based Global Bond Funds”, Journal of Banking and Finance 30, pp. 2767- 2786. Porter, Gary E., and Jack W. Trifts, 1998. “The Performance Persistence of Experienced Mutual Fund Managers”, Financial Services Review 7, pp. 57-68. Poterba, James M., and Lawrence H. Summers, 1988. “Mean Reversion in Stock Prices: Evidence and Implications”, Journal of Financial Economics 22, pp. 27-59. Prather, Laurie, William Bertin, and Thomas Henker, 2004. “Mutual Fund Characteristics, Managerial Attributes, and Fund Performance”, Review of Financial Economics 13, pp. 315– 349. Pätäri, Eero J., 2008. “Comparative Analysis of Total Risk-Based Performance Measures”, Journal of Risk 10, pp. 69-112. Quigley, Garret, and Rex A. Sinquefield, 2000. “Performance of UK Equity Unit Trusts”, Journal of Asset Management 1, pp. 72-92. Sarnat, Marshall, 1972. “A Note on the Prediction of Portfolio Performance from Ex Post Data”, Journal of Finance 27, pp. 903-906. Sauer, David A., 1997. “Information Content of Prior Period Mutual Fund Performance Rankings”, Journal of Economics and Business 49, pp. 549-567. Sharpe, William F., 1966. “Mutual Fund Performance”, Journal of Business 39, pp. 119-138. Shukla, Ravi, and Charles Trzcinka, 1994. “Persistent Performance in the Mutual Fund Market: Tests with Funds and Investment Advisors”, Review of Quantitative Finance and Accounting 4, pp. 115-135. Sirri, Erik R., and Peter Tufano, 1993. “Buying and Selling Mutual funds: Flows, Performance, Fees, and Services”, Working Paper, Harvard Business School. Teo, Melvin, and Sun-Jung Woo, 2001. “Persistence in Style-Adjusted Mutual Fund Returns”, Working Paper, Harvard University. Treynor, Jack L., and Fischer Black, 1973. “How to use Security Analysis to Improve Portfolio Selection?” Journal of Business 46, pp. 66-86. Volkman, David A., and Mark E. Wohar, 1996. “Abnormal Profits and Relative Strength in Mutual Fund Returns”, Review of Financial Economics 5, pp. 101-116. Wermers, R., 1997 “Momentum Investment Strategies of Mutual Funds, Performance Persistence, and Survivorship Bias”, Working Paper, University of Colorado.