Finance

Fund Performance

Fund Performance (.pdf)

  1. CARHART, Mark M., 1997. On Persistence in Mutual Fund Performance, The Journal of Finance, Vol. 52, No. 1. (Mar., 1997), pp. 57-82. [Cited by 990] (106.46/year)
    Abstract: "Using a sample free of survivor bias, I demonstrate that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual funds' mean and risk-adjusted returns. Hendricks, Patel and Zeckhauser’s (1993) “hot hands” result is mostly driven by the one-year momentum effect of Jegadeesh and Titman (1993), but individual funds do not earn higher returns from following the momentum strategy in stocks. The only significant persistence not explained is concentrated in strong underperformance by the worst-return mutual funds. The results do not support the existence of skilled or informed mutual fund portfolio managers."

  2. BERK, Jonathan B. and Richard C. GREEN, 2004. Mutual Fund Flows and Performance in Rational Markets. Journal of Political Economy. [Cited by 119] (51.76/year)
    Abstract: "We derive a parsimonious rational model of active portfolio management that reproduces many regularities widely regarded as anomalous. Fund flows rationally respond to past performance in the model even though performance is not persistent and investments with active managers do not outperform passive benchmarks on average. The lack of persistence in returns does not imply that differential ability across managers is nonexistent or unrewarded or that gathering information about performance is socially wasteful. The model can quantitatively reproduce many salient features in the data. The flow-performance relationship is consistent with high average levels of skills and considerable heterogeneity across managers."

  3. GRUBER, Martin J., 1996. Another Puzzle: The Growth in Actively Managed Mutual Funds, The Journal of Finance, Vol. 51, No. 3, Papers and Proceedings of the Fifty-Sixth Annual Meeting of the American Finance Association, San Francisco, California, January 5-7, 1996. (Jul., 1996), pp. 783-810. [Cited by 375] (36.41/year)
    Abstract: "Mutual funds represent one of the fastest growing type of financial intermediary in the American economy. The question remains as to why mutual funds and in particular actively managed mutual funds have grown so fast, when their performance on average has been inferior to that of index funds. One possible explanation of why investors buy actively managed open end funds lies in the fact that they are bought and sold at net asset value, and thus management ability may not be priced. If management ability exists and it is not included in the price of open end funds, then performance should be predictable. If performance is predictable and at least some investors are aware of this, then cash flows into and out of funds should be predictable by the very same metrics that predict performance. Finally, if predictors exist and at least some investors act on these predictors in investing in mutual funds, the return on new cash flows should be better than the average return for all investors in these funds. This article presents empirical evidence on all of these issues and shows that investors in actively managed mutual funds may have been more rational than we have assumed."

  4. WERMERS, Russ, 2000. Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses, The Journal of Finance, Vol. 55, No. 4, Papers and Proceedings of the Sixtieth Annual Meeting of the American Finance Association, Boston, Massachusetts, January 7-9, 2000. (Aug., 2000), pp. 1655-1695. [Cited by 193] (30.64/year)
    Abstract: "We use a new database to perform a comprehensive analysis of the mutual fund industry. We find that funds hold stocks that outperform the market by 1.3 percent per year, but their net returns underperform by one percent. Of the 2.3 percent difference between these results, 0.7 percent is due to the underperformance of nonstock holdings, whereas 1.6 percent is due to expenses and transactions costs. Thus, funds pick stocks well enough to cover their costs. Also, high-turnover funds beat the Vanguard Index 500 fund on a net return basis. Our evidence supports the value of active mutual fund management."

  5. GRINBLATT, Mark, Sheridan TITMAN and Russ WERMERS, 1995. Momentum Investment Strategies, Portfolio Performance, and Herding: A Study of Mutual Fund Behavior, The American Economic Review, Vol. 85, No. 5. (Dec., 1995), pp. 1088-1105. [Cited by 342] (30.27/year)
    Abstract: "This study analyzes the extent to which mutual funds purchase stocks based on their past returns as well as their tendency to exhibit “herding” behavior (i.e., buying and selling the same stocks at the same time). We find that 77 percent of the mutual funds were “momentum investors,” buying stocks that were past winners; however, most did not systematically sell past losers. On average, funds that invested on momentum realized significantly better performance than other funds. We also find relatively weak evidence that funds tended to buy and sell the same stocks at the same time."

  6. DANIEL, Kent, et al., 1997. Measuring Mutual Fund Performance with Characteristic-Based Benchmarks, The Journal of Finance, Vol. 52, No. 3, Papers and Proceedings Fifty-Seventh Annual Meeting, American Finance Association, New Orleans, Louisiana January 4-6, 1997. (Jul., 1997), pp. 1035-1058. [Cited by 274] (29.46/year)
    Abstract: "This article develops and applies new measures of portfolio performance which use benchmarks based on the characteristics of stocks held by the portfolios that are evaluated. Specifically, the benchmarks are constructed from the returns of 125 passive portfolios that are matched with stocks held in the evaluated portfolio on the basis of the market capitalization, book-to-market, and prior-year return characteristics of those stocks. Based on these benchmarks, “Characteristic Timing” and “Characteristic Selectivity” measures are developed that detect, respectively, whether portfolio managers successfully time their portfolio weightings on these characteristics and whether managers can select stocks that outperform the average stock having the same characteristics. We apply these measures to a new database of mutual fund holdings covering over 2500 equity funds from 1975 to 1994. Our results show that mutual funds, particularly aggressive-growth funds, exhibit some selectivity ability, but that funds exhibit no characteristic timing ability."

  7. FERSON, Wayne E. and Rudi W. SCHADT, 1996. Measuring Fund Strategy and Performance in Changing Economic Conditions, The Journal of Finance, Vol. 51, No. 2. (Jun., 1996), pp. 425-461. [Cited by 294] (28.55/year)
    Abstract: "The use of predetermined variables to represent public information and time-variation has produced new insights about asset pricing models, but the literature on mutual fund performance has not exploited these insights. This paper advocates conditional performance evaluation in which the relevant expectations are conditioned on public information variables. We modify several classical performance measures to this end and find that the predetermined variables are both statistically and economically significant. Conditioning on public information controls for biases in traditional market timing models and makes the average performance of the mutual funds in our sample look better."

  8. BROWN, Stephen J. and William N. GOETZMANN, 1995. Performance Persistence. The Journal of Finance., Vol. 50, No. 2. (Jun., 1995), pp. 679-698. [Cited by 299] (26.46/year)
    Abstract: "We explore performance persistence in mutual funds using absolute and relative benchmarks. Our sample, largely free of survivorship bias, indicates that relative risk-adjusted performance of mutual funds persists; however, persistence is mostly due to funds that lag the S&P 500. A probit analysis indicates that poor performance increases the probability of disappearance. A year-by-year decomposition of the persistence effect demonstrates that the relative performance pattern depends upon the time period observed, and it is correlated across managers. Consequently, it is due to a common strategy that is not captured by standard stylistic categories or risk adjustment procedures."

  9. SHARPE, William F., 1992. Asset Allocation: Management Style and Performance Measurement. The Journal of Portfolio Management, Volume 18, Winter 1992, pages 7-19. [Cited by 315] (22.03/year)

  10. BROWN, Keith C., W. V. HARLOW and Laura T. STARKS, 1996. Of Tournaments and Temptations: An Analysis of Managerial Incentives in the Mutual Fund Industry, The Journal of Finance, Vol. 51, No. 1. (Mar., 1996), pp. 85-110. [Cited by 225] (21.85/year)
    Abstract: "We test the hypothesis that when their compensation is linked to relative performance, managers of investment portfolios likely to end up as “losers” will manipulate fund risk differently than those managing portfolios likely to be “winners.” An empirical investigation of the performance of 334 growth-oriented mutual funds during 1976 to 1991 demonstrates that mid-year losers tend to increase fund volatility in the latter part of an annual assessment period to a greater extent than mid-year winners. Furthermore, we show that this effect became stronger as industry growth and investor awareness of fund performance increased over time."

  11. BOLLEN, Nicolas P. B. and Jeffrey A. BUSSE, 2005. Short-Term Persistence in Mutual Fund Performance, Review of Financial Studies, Volume 18, Number 2, 2005, pp. 569-597. [Cited by 28] (21.55/year)
    Abstract: "We estimate parameters of standard stock selection and market timing models using daily mutual fund returns and quarterly measurement periods. We then rank funds quarterly by abnormal return and measure the performance of each decile the following quarter. The average abnormal return of the top decile in the post-ranking quarter is 39 basis points. The post-ranking abnormal return disappears when funds are evaluated over longer periods. These results suggest that superior performance is a short-lived phenomenon that is observable only when funds are evaluated several times a year."

  12. ACKERMANN, Carl, Richard McENALLY and David RAVENSCRAFT, 1999. The Performance of Hedge Funds: Risk, Return, and Incentives, The Journal of Finance, Vol. 54, No. 3. (Jun., 1999), pp. 833-874. [Cited by 155] (21.23/year)
    Abstract: "Hedge funds display several interesting characteristics that may influence performance, including: flexible investment strategies, strong managerial incentives, substantial managerial investment, sophisticated investors, and limited government oversight. Using a large sample of hedge fund data from 1988-1995, we find that hedge funds consistently outperform mutual funds, but not standard market indices. Hedge funds, however, are more volatile than both mutual funds and market indices. Incentive fees explain some of the higher performance, but not the increased total risk. The impact of six data-conditioning biases is explored. We find evidence that positive and negative survival-related biases offset each other."

  13. EDELEN, Roger M., 1999. Investor flows and the assessed performance of open-end mutual funds, Journal of Financial Economics, Volume 53, Issue 3, September 1999, Pages 439-466. [Cited by 151] (20.69/year)
    Abstract: "Open-end equity funds provide a diversified equity positions with little direct cost to investors for liquidity. This study documents a statistically significant indirect cost in the form of a negative relation between a fund’s abnormal return and investor flows. Controlling for this indirect cost of liquidity changes the average fund's abnormal return (net of expenses) from a statistically significant −1.6% per year to a statistically insignificant −0.2% and also fully explains the negative market-timing performance found in this and other studies of mutual fund returns. Thus, the common finding of negative return performance at open-end mutual funds is attributable to the costs of liquidity-motivated trading."

  14. JENSEN, Michael C., 1968. The Performance of Mutual Funds in the Period 1945-1964, The Journal of Finance, Vol. 23, No. 2, Papers and Proceedings of the Twenty-Sixth Annual Meeting of the American Finance Association Washington, D.C. December 28-30, 1967. (May, 1968), pp. 389-416. [Cited by 744] (19.43/year)

  15. CHEVALIER, Judith and Glenn ELLISON, 1999. Are Some Mutual Fund Managers Better than Others? Cross-Sectional Patterns in Behavior and Performance, The Journal of Finance, Vol. 54, No. 3. (Jun., 1999), pp. 875-899. [Cited by 136] (18.63/year)
    Abstract: "We examine whether mutual fund performance is related to characteristics of fund managers that may indicate ability, knowledge, or effort. In particular, we study the relationship between performance and the manager's age, the average composite SAT score at the manager's undergraduate institution, and whether the manager has an MBA. Although the raw data suggest striking return differences between managers with different characteristics, most of these can be explained by behavioral differences between managers and by selection biases. After adjusting for these, some performance differences remain. In particular, managers who attended higher-SAT undergraduate institutions have systematically higher risk-adjusted excess returns."

  16. ELTON, Edwin J., Martin J. GRUBER and Christopher R. BLAKE, 1996. The Persistence of Risk-Adjusted Mutual Fund Performance, The Journal of Business, Vol. 69, No. 2. (Apr., 1996), pp. 133-157. [Cited by 173] (16.80/year)
    Abstract: "We examine predictability for stock mutual funds using risk-adjusted returns. We find that past performance is predictive of future risk-adjusted performance. Applying modern portfolio theory techniques to past data improves selection and allows us to construct a portfolio of funds that significantly outperforms a rule based on past rank alone. In addition, we can form a combination of actively managed portfolios with the same risk as a portfolio of index funds but with higher mean return. The portfolios selected have small but statistically significant positive risk-adjusted returns during a period where mutual funds in general had negative risk-adjusted returns."

  17. BROWN, Stephen J., et al., 1992. Survivorship bias in performance studies, The Review of Financial Studies, Vol. 5, No. 4. (1992), pp. 553-580. [Cited by 215] (14.97/year)
    Abstract: "Recent evidence suggests that past mutual fund performance predicts future performance. We analyze the relationship between volatility and returns in a sample that is truncated by survivorship and show that this relationship gives rise to the appearance of predictability. We present some numerical examples to show that this effect can be strong enough to account for the strength of the evidence favoring return predictability."

  18. HENDRICKS, Darryll, Jayendu PATEL and Richard ZECKHAUSER, 1993. Hot Hands in Mutual Funds: Short-Run Persistence of Relative Performance, 1974-1988, The Journal of Finance [Cited by 194] (14.59/year)
    Abstract: "The relative performance of no-load, growth-oriented mutual funds persists in the near term, with the strongest evidence for a one-year evaluation horizon. Portfolios of recent poor performers do significantly worse than standard benchmarks; those of recent top performers do better, though not significantly so. The difference in risk-adjusted performance between the top and bottom octile portfolios is six to eight percent per year. These results are not attributable to known anomalies or survivorship bias. Investigations with a different (previously used) data set and with some post-1988 data confirm the finding of persistence."

  19. SHARPE, William F., 1966. Mutual Fund Performance, The Journal of Business, Vol. 39, No. 1, Part 2: Supplement on Security Prices. (Jan., 1966), pp. 119-138. [Cited by 588] (14.59/year)
    Conclusions: "This paper represents an attempt to bring to bear on the measurement and prediction of mutual fund performance some of the results of recent work in capital theory and the behavior of stock-market prices. We have shown that performance can be evaluated with a simple yet theoretically meaningful measure that considers both average return and risk. This measure precludes the “discovery” of differences in performance due solely to differences in objectives (e.g., the high average returns typically obtained by funds who consciously hold risky portfolios). However, even when performance is measured in this manner there are differences among funds; and such differences do not appear to be entirely transitory. To a major extent they can be explained by differences in expense ratios, lending support to the view that the capital market is highly efficient and that good managers concentrate on evaluating risk and providing diversification, spending little effort (and money) on the search for incorrectly priced securities. However, past performance per se also explains some of the differences. Further work is required before the significance of this result can be properly evaluated. But the burden of proof may reasonably be placed on those who argue the traditional view—that the search for securities whose prices diverge from their intrinsic values is worth the expense required, even for a mutual fund operating under severe constraints on the proportion of funds invested in any single security.28 Fortunately many who hold this view have both the means and the data required to perform extensive analyses; we will all look forward to their results."

  20. GRINBLATT, Mark and Sheridan TITMAN, 1989. Mutual Fund Performance: An Analysis of Quarterly Portfolio Holdings, The Journal of Business, Vol. 62, No. 3. (Jul., 1989), pp. 393-416. [Cited by 251] (14.51/year)
    Abstract: "This article employs the 1975–84 quarterly holdings of a sample of mutual funds to construct an estimate of their gross returns. This sample, which is not subject to survivorship bias, is used in conjunction with a sample that contains the actual (net) returns of the mutual funds. In addition to allowing us to estimate the bias in measured performance that is due to the survival requirement and to estimate total transaction costs, the sample is used to test for the existence of abnormal performance. The tests indicate that the risk-adjusted gross returns of some funds were significantly positive."

  21. WARTHER, V.A., 1995. Aggregate mutual fund flows and security returns. Journal of Financial Economics. [Cited by 161] (14.25/year)

  22. GRINBLATT, M. and S. TITMAN, 1992. The Persistence of Mutual Fund Performance, The Journal of Finance, Vol. 47, No. 5. (Dec., 1992), pp. 1977-1984. [Cited by 196] (13.71/year)
    Abstract: "This paper analyzes how mutual fund performance relates to past performance. These tests are based on a multiple portfolio benchmark that was formed on the basis of securities characteristics. We find evidence that differences in performance between funds persist over time and that this persistence is consistent with the ability of fund managers to earn abnormal returns."

  23. BROWN, S.J., W.N. GOETZMANN and R.G. IBBOTSON, 1997. Offshore Hedge Funds: Survival and Performance 1989-1995. mfainfo.org. [Cited by 127] (13.66/year)

  24. CHEN, J., et al., 2004. Does fund size erode mutual fund performance? The role of liquidity and organization. American Economic Review. [Cited by 31] (13.48/year)

  25. GRINBLATT, M. and S. TITMAN, 1993. Performance Measurement without Benchmarks: An Examination of Mutual Fund Returns. The Journal of Business. [Cited by 175] (13.16/year)

  26. BROWN, S.J. and W.N. GOETZMANN, 2001. Hedge Funds With Style. [Cited by 68] (12.83/year)

  27. FUNG, W. and D.A. HSIEH, 2000. Performance Characteristics of Hedge Funds and Commodity Funds: Natural vs. Spurious Biases. The Journal of Financial and Quantitative Analysis. [Cited by 77] (12.22/year)

  28. AGARWAL, V. and N.Y. NAIK, 2000. Multi-Period Performance Persistence Analysis of Hedge Funds. The Journal of Financial and Quantitative Analysis. [Cited by 73] (11.59/year)

  29. KOTHARI, S.P. and Jerold B. WARNER, 2001. Evaluating Mutual Fund Performance. The Journal of Finance, Vol. 56, No. 5. (Oct., 2001), pp. 1985-2010. [Cited by 59] (11.13/year)
    Abstract: "We study standard mutual fund performance measures, using simulated funds whose characteristics mimic actual funds. We find that performance measures used in previous mutual fund research have little ability to detect economically large magnitudes (e.g., three percent per year) of abnormal fund performance, particularly if a fund's style characteristics differ from those of the value-weighted market portfolio. Power can be substantially improved, however, using event-study procedures that analyze a fund's stock trades. These procedures are feasible using time-series data sets on mutual fund portfolio holdings."

  30. ELTON, Edwin J., Martin J. GRUBER and Christopher R. BLAKE, 1996. Survivorship Bias and Mutual Fund Performance, The Review of Financial Studies, Vol. 9, No. 4. (Winter, 1996), pp. 1097-1120. [Cited by 110] (10.68/year)
    Abstract: "Mutual fund attrition can create problems for a researcher because funds that disappear tend to do so due to poor performance. In this article we estimate the size of the bias by tracking all funds that existed at the end of 1976. When a fund merges we calculate the return, taking into account the merger terms. This allows a precise estimate of survivorship bias. In addition, we examine characteristics of both mutual funds that merge and their partner funds. Estimates of survivorship bias over different horizons and using different models to evaluate performance are provided."

  31. LIANG, Bing, 1999. On the Performance of Hedge Funds. Financial Analysts Journal, July/August 1999, Vol. 55, No. 4: 72-85. [Cited by 77] (10.55/year)
    Abstract: "Empirical evidence indicates that hedge funds differ substantially from traditional investment vehicles, such as mutual funds. Unlike mutual funds, hedge funds follow dynamic trading strategies and have low systematic risk. Hedge funds' special fee structures apparently align managers' incentives with fund performance. Funds with "high watermarks" (under which managers are required to make up previous losses before receiving any incentive fees) significantly outperform those without. Hedge funds provide higher Sharpe ratios than mutual funds, and their performance in the period of January 1992 through December 1996 reflects better manager skills, although hedge fund returns are more volatile. Average hedge fund returns are related positively to incentive fees, fund assets, and the lockup period."

  32. AMIN, G. and H. KAT, 2003. Hedge Fund Performance 1990-2000: DO the Money Machines Really Add Value?. Journal of Financial and Quantitative Analysis. [Cited by 34] (10.31/year)

  33. P?STOR, L. and R.F. STAMBAUGH, 2001. Mutual Fund Performance and Seemingly Unrelated Assets. finance.wharton.upenn.edu. [Cited by 53] (10.00/year)

  34. DANIEL, K. and S. TITMAN, 1999. Market Efficiency in an Irrational World. Financial Analysts Journal. [Cited by 71] (9.73/year)

  35. GRINBLATT, M. and S. TITMAN, 1994. A Study of Monthly Mutual Fund Returns and Performance Evaluation Techniques. The Journal of Financial and Quantitative Analysis. [Cited by 110] (8.94/year)
  36. GOETZMANN, W.N. and N. PELES, 1997. Cognitive dissonance and mutual fund investors. Journal of Financial Research, Vol. XX, No. 2, pp. 145-158. [Cited by 83] (8.93/year)
    Abstract: "We present evidence from questionnaire studies of mutual fund investors about recollections of past fund performance. We find that investor memories exhibit a positive bias, consistent with current psychological models. We find that the degree of bias is conditional upon previous investor choice, a phenomenon related to the well known theory of cognitive dissonance.
    The magnitude of psychological and economic frictions in the mutual fund industry is examined via a cross-sectional study of equity mutual funds. We find an unusually high frequency of poorly performing funds, consistent with investor "inertia." Analysis of aggregate dollar investments however, shows the net effect of this inertia is small. Thus the regulatory implications with respect to additional disclosure requirements are limited.
    We examine one widely documented empirical implication of mutual fund investor inertia: the differential response of investment dollars to past performance. We perform tests that control for the crucial problem of survivorship. These confirm the presence of differential response, but find the effect is confined to the top quartile. There is little evidence that the response to poor performance is unusual."

  37. BAUER, R., K. KOEDIJK and R. OTTEN, 2002. International Evidence on Ethical Mutual Fund Performance and Investment Style. sustainabilityfund.nl. [Cited by 36] (8.37/year)

  38. BLAKE, David, Bruce N. LEHMANN and Allan TIMMERMANN, 1999. Asset Allocation Dynamics and Pension Fund Performance, The Journal of Business, Vol. 72, No. 4. (Oct., 1999), pp. 429-461. [Cited by 61] (8.36/year)
    Abstract: "Using a data set on more than 300 U.K. pension funds’ asset holdings, this article provides a systematic investigation of the performance of managed portfolios across multiple asset classes. We find evidence of slow mean reversion in the funds’ portfolio weights toward a common, time-varying strategic asset allocation. We also find surprisingly little cross-sectional variation in the average ex post returns arising from the strategic-asset-allocation, market-timing, and security-selection decisions of the fund managers. Strategic asset allocation accounts for most of the time-series variation in portfolio returns, while market timing and asset selection appear to have been far less important."

  39. OTTENB, R. and D. BAMS, 2002. European Mutual Fund Performance. European Financial Management. [Cited by 34] (7.91/year)

  40. LIANG, Bing, 2001. Hedge Fund Performance: 1990–1999, Financial Analysts Journal, January/February 2001, Vol. 57, No. 1: pp. 11-18. [Cited by 41] (7.74/year)
    Abstract: "Using a large database, I studied hedge fund performance and risk during an almost 10-year period from 1990 to mid-1999. The empirical results show that hedge funds had an annual return of 14.2 percent in this period, compared with 18.8 percent for the S&P 500 Index. The S&P 500 is much more volatile, however, than hedge funds as a whole. Annual survivorship bias for hedge funds was 2.43 percent. I examined year 1998 in detail because hedge funds were heavily affected by the global financial market tumble in that year. For example, the highest volatility for hedge fund returns occurred in 1998, and more funds died and fewer were born in 1998 than in any other year of the period studied. Few funds changed their fee structures. In those that did, the fee changes were performance related; poor performers lowered their incentive fees."

  41. MASSA, M., 2003. How do family strategies affect fund performance? When performance-maximization is not the only game …. Journal of Financial Economics. [Cited by 25] (7.58/year)

  42. CAPOCCI, D. and G. HUBNER, 2004. Analysis of hedge fund performance. Journal of Empirical Finance. [Cited by 17] (7.39/year)

  43. IPPOLITO, Richard A., 1989. Efficiency with costly information: A study of mutual fund performance, 1965–1984, The Quarterly Journal of Economics, Vol. 104, No. 1. (Feb., 1989), pp. 1-23. [Cited by 127] (7.34/year)
    Abstract: "If information is costly to collect and implement, then it is efficient for trades by informed investors to occur at prices sufficiently different from full-information prices to compensate them for the cost of becoming informed. This notion is tested by evaluating investment performance in the mutual fund industry over a 20-year period. The study finds evidence that is consistent with optimal trading in efficient markets. Risk-adjusted returns in the mutual fund industry, net of fees and expenses, are comparable to returns available in index funds; and portfolio turnover and management fees are unrelated to fund performance."

  44. LEHMANN, B. and D.M. MODEST, 1987. Mutual Fund Performance Evaluation: A Comparison of Benchmarks and Benchmark Comparisons. [Cited by 139] (7.20/year)

  45. FERSON, Wayne E. and Vincent A. WARTHER, 1996. Evaluating fund performance in a dynamic market. Financial Analysts Journal, November/December 1996, Vol. 52, No. 6: pp. 20-28. [Cited by 69] (6.70/year)
    Abstract: "Previous studies show that interest rates, dividend yields, and other commonly available variables are useful market indicators, but until now, measures of fund performance have not used the information. This article modifies classical performance measures to take account of well-known market indicators. The conditional performance evaluation approach avoids some of the biases that plague traditional measures. Applied to a sample of mutual funds, the conditional measures make the funds' performance look better."

  46. CUMBY, R.E. and J.D. GLEN, 1990. Evaluating the Performance of International Mutual Funds. The Journal of Finance. [Cited by 107] (6.56/year)

  47. EDWARDS, F.R. and M.O. CAGLAYAN, 2001. Hedge Fund Performance and Manager Skill. Journal of Futures Markets. [Cited by 34] (6.42/year)

  48. BLAKE, C.R., E.J. ELTON and M.J. GRUBER, 1993. The Performance of Bond Mutual Funds. The Journal of Business. [Cited by 83] (6.24/year)

  49. 25
  50. DAHLQUIST, M., S. ENGSTROM and P. SODERLIND, 2000. Performance and Characteristics of Swedish Mutual Funds. The Journal of Financial and Quantitative Analysis. [Cited by 38] (6.03/year)

  51. Journal of Financial and Quantitative Analysis, Vol. 35, No. 3 (Sep., 2000), pp. 409-423
  52. WERMERS, R., 2000. Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style. Transactions Costs, and Expenses, Journal of Finance. [Cited by 38] (6.03/year)

  53. 21
  54. BLAKE, D. and A. TIMMERMANN, 1998. Mutual Fund Performance: Evidence from the UK. European Finance Review. [Cited by 48] (5.78/year)

  55. Volume 2, Number 1 / January, 1998
  56. BLAKE, C.R. and M.R. MOREY, 2000. Morningstar Ratings and Mutual Fund Performance. The Journal of Financial and Quantitative Analysis. [Cited by 35] (5.56/year)

  57. HENRIKSSON, Roy D., 1984. Market Timing and Mutual Fund Performance: An Empirical Investigation, The Journal of Business, Vol. 57, No. 1, Part 1. (Jan., 1984), pp. 73-96. [Cited by 122] (5.47/year)
    Abstract: "The evaluation of the performance of investment managers is a topic of considerable interest to practitioners and academics alike. Using both the parametric and non-parametric tests for the evaluation of forecasting ability presented by Henriksson and Merton, the market-timing ability of 116 open-end mutual funds is evaluated for the period 1968-80. The empirical results do not support the hypothesis that mutual fund managers are able to follow an investment strategy that successfully times the return on the market portfolio."

  58. INDRO, Daniel C., et al., 1999. Mutual fund performance: Does fund size matter? Financial Analysts Journal, May 1999, Vol. 55, No. 3: 74-87. [Cited by 38] (5.21/year)
    Abstract: "Fund size (net assets under management) affects mutual fund performance. Mutual funds must attain a minimum fund size in order to achieve sufficient returns to justify their costs of acquiring and trading on information. Furthermore, there are diminishing marginal returns to information acquisition and trading, and the marginal returns become negative when the mutual fund exceeds its optimal fund size. In a sample of 683 nonindexed U.S. equity funds over the 1993–95 period, we found that 20 percent of the mutual funds were smaller than the breakeven-cost fund size and 10 percent of the largest funds overinvested in information acquisition and trading. In addition, we found that value funds and blend (value-and-growth) funds have more to gain than growth funds from these information activities."

  59. COGGIN, T. Daniel, Frank J. FABOZZI and Shafiqur RAHMAN, 1993. The Investment Performance of US Equity Pension Fund Managers: An Empirical Investigation. The Journal of Finance, Vol. 48, No. 3, Papers and Proceedings of the Fifty-Third Annual Meeting of the American Finance Association: Anaheim, California January 5-7, 1993. (Jul., 1993), pp. 1039-1055. [Cited by 69] (5.19/year)
    Abstract: "This paper presents an empirical examination of the selectivity and market timing performance of a sample of U.S. equity pension fund managers. Regardless of the choice of benchmark portfolio or estimation model, the average selectivity measure is positive and the average timing measure is negative. However both selectivity and timing appear to be somewhat sensitive to the choice of a benchmark when managers are classified by investment style. Meta-analysis revealed some real variation around the mean values for each measure. The 80 percent probability intervals for selectivity revealed that the best managers produced substantial risk-adjusted excess returns. We also found a negative correlation between selectivity and timing, but we argue that the observed negative correlation in our data is largely an artifact of negatively correlated sampling errors for the two estimates."

  60. ELTON, Edwin J., Martin J. GRUBER and Christopher R. BLAKE, 1995. Fundamental Economic Variables, Expected Returns, and Bond Fund Performance. The Journal of Finance, Vol. 50, No. 4. (Sep., 1995), pp. 1229-1256. [Cited by 58] (5.13/year)
    Abstract: "In this article, we develop relative pricing (APT) models that are successful in explaining expected returns in the bond market. We utilize indexes as well as unanticipated changes in economic variables as factors driving security returns. An innovation in this article is the measurement of the economic factors as changes in forecasts. The return indexes are the most important variables in explaining the time series of returns. However, the addition of the economic variables leads to a large improvement in the explanation of the cross-section of expected returns. We utilize our relative pricing models to examine the performance of bond funds.

  61. CARHART…, M., 2001. Survivor Bias and Mutual Fund Performance. Goldman Sachs Asset Management, August. [Cited by 27] (5.10/year)

  62. BASSO, A. and S. FUNARI, 2001. A data envelopment analysis approach to measure the mutual fund performance. European Journal of Operational Research. [Cited by 25] (4.72/year)
  63. KAHN, R.N. and A. RUDD, 1995. Does Historical Performance Predict Future Performance?. Financial Analysts Journal. [Cited by 47] (4.16/year)
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