US mutual fund performance studies

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US mutual fund performance studies compares various methodologies to determine stock mutual fund performance. Additional studies examine bond fund performance.

Stock funds

In a 2011 paper, "Mutual Funds",[1] authors Elton, Gruber and Blake provide a survey article in which they review the modern literature on the characteristics and performance of mutual funds. The following tables of are derived from the study. Studies include those which examine the performance of stock mutual funds (after expenses) and those which study the pre-expense performance of stock funds. Other studies examine stock fund managers' timing ability; additional studies explore the persistence of stock fund performance.

Performance

Early studies on stock fund performance (included in the "Mutual Fund Performance (post expenses)" table below) use benchmarks derived from single factor measures such as the Sharpe ratio[2] Treynor's alpha,[3] or Jensen's alpha,[4] all based on the CAPM (Capital Asset Pricing Model).[5] As many stock funds hold portfolios that differ from the overall market (for example, concentrating on mid cap or small cap stocks), later studies draw upon the development of multi-factor models, such as the Fama-French three factor model (market, size, and value) or a four factor model, created by adding momentum to the three Fama-French factors. A fifth factor, involving bond returns is also sometimes used.

Studies using mutual fund holdings data (included in the table "Using Holdings Data (Pre-Expenses)" below) attempt to determine manager skill.

Conclusion: Both sets of studies indicate that, before costs, managers, on average, possess stock selection skill, but actual performance is insufficient to overcome the costs of management.

Mutual Fund Performance (post expenses)[1][note 1]
Author(s) Methodology Average excess return annualized
Sharpe (1966) [2] Sharpe ratio Negative
Jensen (1968) [3] Single‐index model (CAPM) ‐1.1%
Lehmann & Modest (1987) [4] CAPM & multi‐factor models Negative
Elton, Gruber, Das, & Hlavka (1993) [5] Multi‐factor model ‐1.59%
Malkiel (1995) [6] Single‐index model (CAPM) ‐.24%
Gruber (1996) [7] CAPM & multi‐factor factor ‐.65%
Elton, Gruber & Blake (1996) [8] Multi‐factor model ‐.91%
Ferson & Schadt (1996) [9] Single‐index model (CAPM) ‐.37 to +.26%
Carhart (1997) [10] 4‐factor model ‐1.98%
Pastor & Stambaugh (2002) [11] Multi‐factor model ‐.86 to ‐1.25%
Elton, Gruber & Blake (2003) [12] Multi‐factor model ‐.91%
Kosowski, Timmerman, Wermers, & White (2005) [13] Carhart 4‐factor model ‐.5%
Fama & French (2010) [14] Fama‐French 3‐factor & Carhart 4‐factor models ‐.81 to ‐1.00%
Elton, Gruber, & Blake (2011) [15] Fama‐French 3‐factor & Carhart 4‐factor models Negative
Using Holdings Data (Pre-Expenses)[1][note 2]
Author(s) Average excess return annualized
Grinblatt & Titman (1989) [16] (slight positive)
Grinblatt & Titman (1993) [17] 2.00%
Daniel, Grinblatt, Titman & Wermers (1997) [18] .77%
Wermers (2012) [19] .71%

Timing

Researchers have used two different ways to measure mutual fund managers' timing ability. One method uses return data and a second uses holdings data. In addition, two computational models, and their variants, commonly serve as the basis for calculations used in timing studies: the Treynor and Mazuy (1966) method,[6] and the Henriksson (1984)[7] and Henriksson and Merton (1981) method.[8][9][1]

Early studies used returns data and found no evidence of successful timing. However subsequent studies have used fund holdings data to measure timing.[note 3] Using holdings data, these studies find evidence of positive timing:

Bollen and Busse (2001) found significant positive timing using daily data and a time series regression, and Kaplan and Sensoy (2005) and Jiang, Yao and Yu (2007) find positive timing using holdings data. All of these studies measure timing by looking at changes in the sensitivity to a single index.

— Mutual funds[1]

Other researchers, while in agreement with using fund holdings data, argue that funds need to be benchmarked using multi-factor models because changes in the sensitivity to the market often come about because of changes in sensitivity to other factors (for example, by adding smaller cap stocks or higher beta stocks to the fund portfolio). This approach is taken by Elton, Gruber and Blake (2011), using one-index, two-index (stocks/bonds), Fama-French, and sector rotation models,[10] and by Ferson and Qian (2006). Both of these studies find evidence of successful timing when measuring sensitivity to a single index, but find no evidence of positive timing when using multiple factors as benchmarks.[1]

Conclusion: Studies on timing using returns data show no evidence of positive timing. Using holdings data, funds show positive timing when measured by its sensitivity to a single index. Positive timing is not found when the funds are measured by sensitivity to multiple factors.

Timing[1][note 4]
Author(s) Timing ability
Daniel, Grinblatt, Titman & Wermers (1997) [20] Timing ability
Busse (1999) [21] Timing ability
Becker, Ferson, Myers & Schill (1999) [22] No timing ability
Bollen & Busse (2001) [23] Timing ability
Kaplan & Sensoy (2005) [24] Timing ability
Ferson & Qian (2006)[note 5] No timing ability
Jiang, Yao & Yu (2007) [25] Timing ability
Elton, Gruber & Blake (2011) [26] No timing ability

Persistence of fund manager performance

Academics judge outperformance by positive alpha from an appropriate multi-index model.

Almost all studies on persistence in mutual fund performance find that poor performance in one period predicts poor performance in subsequent periods. A common characteristic of these poor performing funds is high expenses.

Many researchers have found a positive alpha over subsequent periods when ranking is done by alpha or alpha over residual risk. These studies include:

Carhart (1997), who found when funds were ranked by alpha the top ranked group had positive alphas over the next five years; Busse and Irvine (2006), who found persistence and positive alphas using Bayesian estimates; Gruber (1996); Elton, Gruber and Blake (1996), Elton, Gruber and Blake (2011), and Cohen, Coval and Pastor (2005), all of which find persistence for the top-ranked group and that the top group has a positive alpha.

— Mutual funds[1]

Studies questioning the effectiveness of using multi-index models for judging persistence include Chan, Dimmock and Lakonishok (2010),[11], Cremers, Petajisto and Zitzewitz (2010),[12] and Elton, Gruber and Blake (1999).[13]

Chan, Dimmock and Lakonishok (2010) finds that results can vary depending on how the Fama-French factors are defined. For example they find that the Russell 1000 growth index can have an alpha ranging from -1.66% to +1.08% depending on how they define the factors. Cremers, Petajisto and Zitzewitz (2010) find the S&P index has a positive alpha using the Fama-French three-factor model. Elton, Gruber and Blake (1999) describe how growth is a complex variable that perhaps is not being modeled properly.[1]

Fama and French (2010)[14] note that fund performance showed stronger evidence of positive performance persistence during the 1975 to 2002 period, and that such performance has waned over the 1984 to 2006 period. The study concludes that a prediction that most fund managers have sufficient skill to cover their costs is not supported by the data. They find that poor performers do not appear to be so by chance, while those funds that have done extremely well may have obtained these results by chance.

Evans, Gil-Bazo and Lipson (2016)[15] find the existence of diseconomies of scope in mutual fund manager performance. While confirming that the scope of manager responsibilities is expanded in response to positive past performance, this expanded scope attenuates subsequent performance after controlling for effects related to fund size. Conversely, reductions in scope enhance performance.

Persistence[1][note 6]
Author(s) Ranking Measure Methodology Evaluation Measure Result Positive alpha for top group
Grinblatt & Titman (1992) [27] G&T Measure G&T Measure Persistence NR*
Hendricks, Patel & Zeckhauser (1993) [28] Returns Returns Persistence NR*
Brown & Goetzmann (1995) [29] Returns Returns Capm 3-factor Persistence Primarily worst group NR*
Carhart (1997) [30] Returns 4-factor Alpha Lowest Decile No
Carhart (1997) [31] Alpha 4-factor Alpha Lowest & highest decile Yes
Elton, Gruber & Blake (1996) [32] Alpha Alpha Persistence Yes
Gruber (1996) [33] Alpha Alpha Persistence Yes
Cohen, Coval & Pastor (2005) [34] Alpha Alpha Persistence Yes
Busse & Irvine (2006) [35] Bayesian Alpha Alpha Prediction Yes
Elton, Gruber & Blake (2011) [36] Alpha Alpha Persistence Yes
Elton, Gruber & Blake (2011) [37] Alpha Alpha Persistence Yes
Richard B. Evans, Javier Gil-Bazo & Marc L. Lipson (2016) Alpha Alpha No Persistence No
*NR means Not Relevant since the authors don’t measure performance relative to index or set of indexes.

Bond funds

The four bond fund studies each develop and use a differing array of benchmarks to evaluate bond mutual funds.

Blake, Elton & Gruber (1994)

This study evaluates bond funds using three sets of benchmarks:

  1. A one-index model (either a general bond index or the submarket index that Morningstar identified as most like the bond fund).
  2. Two three-index models.
  3. A six- index model. The six indexes were based on the major types of securities held by the fund and included an intermediate government bond index, a long-term government bond index, an intermediate corporate bond index, a long-term corporate bond index, a high-yield bond index, and a mortgage bond index.[1]

Elton, Gruber and Blake (1995)

This study employs both time series and cross sectional tests on bond pricing and developes a new six-index model of bond pricing. The six variables include:

  1. An aggregate index of stock returns;
  2. An aggregate index of bond returns;
  3. A measure of risk premium in the bond market (return on high yield bonds minus a government bond index);
  4. A series to represent option valuation (the return on mortgage bonds)
  5. Two variables to measure unanticipated changes in inflation and unanticipated changes in GNP.[16]

Comer and Rodriguez (2006)

Comer and Rodriguez use a single model and test a six-index model:

  1. Single index model.
  2. The six indexes they employ include three corporate government maturity return indexes (1 to 5 years, 5 to 10 years, and beyond 10 years), the return on high-yield bonds, the return on mortgages, and the return on Treasury bills.[17]

Chen, Ferson and Peters (2010)

Chen, Ferson and Peters chose indexes based on:

  1. The term structure of interest rates;
  2. Credit spreads;
  3. Liquidity spreads;
  4. Mortgage spreads;
  5. Exchange rates;
  6. A measure of dividend yield and equity volatility.[18]

Conclusion: All models show consistent bond fund underperformance. These studies suggest that models of bond fund performance should include at least three indexes: a general bond index, a risk index (capturing high yield bond performance), and an index to measure option-like qualities (capturing mortgage-backed security performance).

Bond funds[1][note 7]
Author(s) Average excess return annualized
Blake, Elton, Gruber (1994)[note 8] -.51%
Elton, Gruber & Blake (1995) [38] -.75% to -1.3%
Comer & Rodriguez (2006) [39] -1.00 to -1.14%
Chen, Ferson & Peters (2010) [40] -.70%

Mutual fund investor performance

The following papers examine individual investor mutual fund performance in the US contributory pension program. These papers document numerous behavioral pitfalls identified by behavioral economics.

Mutual fund investor performance[note 9]
Author(s) Subject
Gruber (1996) [41] Growth of active mutual funds
Benartzi and Thaler (2001) [42] 1/n investment strategy
Madrian and Shea (2001) [43] default behavior
Liang and Weisbenner (2002) [44] company stock and 1/n investment strategy
Elton, Gruber and Busse (2004) [45] index fund selection
Ameriks and Zeldes (2004) [46] participant asset allocation and activity
Huberman and Jiang (2006) [47] participant asset allocation
Elton, Gruber and Blake (2007) [48] participant reaction to funds offered in 401(k) plans
Agnew and Balduzzi (2010) [49] 401(k) transfers and daily returns

Notes

  1. ↑ The papers in the Mutual Fund Performance table are:
    • Sharpe, William, "Mutual Fund Performance", The Journal of Business, January, 1966.
    • Jensen, Michael C., The Performance of Mutual Funds in the Period 1945-1964. (May 1, 1967). Journal of Finance, Vol. 23, No. 2, pp. 389-416, 1967.
    • Lehmann, Bruce N. and Modest, David, "Mutual Fund Performance Evaluation: a Comparison of Benchmarks and Benchmark Comparisons", (August 1987). NBER Working Paper No. w1721.
    • Elton, Edwin J.; Gruber, Martin J.; Das, Sanjiv; and Hlavka, Matthew, "Efficiency with costly information: a reinterpretation of evidence from manager portfolios", (1993) Review of Financial Studies 6:1-23.
    • Malkiel, Burton G., "Returns from Investing in Equity Mutual Funds 1971 to 1991", The Journal of Finance Vol. 50, No. 2 (Jun., 1995), pp. 549-572.
    • Gruber, Martin J., "Another puzzle: the growth in actively managed mutual funds", (1996) Journal of Finance 51:783-810.
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "The Persistence of Risk-Adjusted Mutual Fund Performance", Journal of Business, Vol. 69 No. 2, April 1996.
    • Ferson, Wayne E. and Schadt, Rudi W., "Measuring Fund Strategy and Performance in Changing Economic Conditions", The Journal of Finance
    Vol. 51, No. 2 (Jun., 1996), pp. 425-461.
    • Carhart, Mark M., "On Persistence in Mutual Fund Performance" , The Journal of Finance Vol. 52, No. 1 (Mar., 1997), pp. 57-82.
    • Pastor, Lubos and Stambaugh, Robert, "Mutual fund performance and seemingly unrelated assets", (2002) Journal of Financial Economics 63:315-349.
    • Kosowski, Robert and Timmermann, Allan G. and Wermers, Russ and White, Jr., Halbert L., "Can Mutual Fund 'Stars' Really Pick Stocks? New Evidence from a Bootstrap Analysis", (September 1, 2005).
    • Fama, Eugene F. and French, Kenneth R., "Luck Versus Skill in the Cross Section of Mutual Fund Returns", (December 14, 2009). Tuck School of Business Working Paper No. 2009-56; Chicago Booth School of Business Research Paper; Journal of Finance, Forthcoming.
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "An Examination of Mutual Fund Timing Ability Using Monthly Holdings Data' (July 13, 2009).
  2. ↑ The papers in the Using Holdings Data table are:
    • Grinblatt, Mark and Titman, Sheridan, "Mutual fund performance: an analysis of quarterly portfolio holdings", (1989) Journal of Business 62:393-416.
    • Grinblatt, Mark and Titman, Sheridan, "Performance measurement without benchmarks: an examination of mutual fund returns", (1993) Journal of Business 66:47-68.
    • Daniel, Kent; Grinblatt, Mark; Titman, Sheridan; and Wermers, Russ, "Measuring mutual fund performance with characteristic-based benchmarks", (1997) Journal of Finance 52:1035-1058.
    • Wermers, Russ, "Matter of Style: The Causes and Consequences of Style Drift in Institutional Portfolios", (March 15, 2012).
  3. ↑ EG&B state:

    In comparing timing measures we have a strong preference for measures based on holdings data. The use of holdings data allows the researcher to observe the pattern of changes in betas and sector or industry weights over time. It also captures much more complicated timing strategies than, for example, assuming the manager switches between two betas depending on his or her market forecast. We also prefer thinking of timing as deviations from a target beta since this is how plan sponsors view timing. However, there is merit in asking whether a manager gained or lost due to changing beta from the level held in the prior period. It also seems to us that measuring timing requires measuring changes with respect to all factors that affect return, not just timing with respect to the market. Managers changing sensitivity to factors other than the market will also affect market sensitivity, and it is the sum of all effects that determines the impact on and returns from this decision. Likewise, managers, by changing market sensitivity, are also likely to be changing sensitivity to other factors, and again it is the sum of all these effects that measures the impact of this decision on shareholder returns.

    — EG&B
  4. ↑ The papers in the Timing table are:
    • Daniel, Kent; Grinblatt, Mark; Titman, Sheridan; and Wermers, Russ, "Measuring mutual fund performance with characteristic-based benchmarks", (1997) Journal of Finance 52:1035-1058.
    • Busse, Jeffrey (1999). "Volatility timing in mutual funds: evidence from daily returns', Review of Financial Studies 12: 1009-1041.
    • Becker, Connie; Ferson, Wayne; Myers, David; and Schill, Michael, "Conditional market timing with benchmark investors", (1999) Journal of Financial Economics 52:119-148.
    • Bollen, Nicolas P. B., and Busse, Jeffrey A., "On the Timing Ability of Mutual Fund Managers", EFA 0687
    • Kaplan, Steven N. and Sensoy, Berk A., Do Mutual Funds Time their Benchmarks? (November 2005)
    • Jiang, George J. and Yao, Tong and Yu, Tong, "Do Mutual Funds Time the Market? Evidence from Portfolio Holdings", (October 1, 2006). AFA 2005 Philadelphia Meetings Paper; Journal of Financial Economics (JFE), Vol. 86, 2007.
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "An Examination of Mutual Fund Timing Using Monthly Holdings Data", (February 14, 2009)
  5. ↑ Ferson & Qian (2006) is an unpublished monograph
  6. ↑ The papers in the Persistence table are:
    • Grinblatt, Mark and Titman, Sheridan "The persistence of mutual fund performance", (1992) Journal of Finance 47:1977-1984.
    • Hendricks, Darryll; Patel, Jayendu; and Zeckhauser, Richard "Hot hands in mutual funds: short-run persistence of relative performance, 1974-1988" (1993) Journal of Finance 48:93-130.
    • Brown, Stephen J. and Goetzmann, William N. "Performance persistence'"", (1995) Journal of Finance 50:679-698.
    • Carhart, Mark M., "On persistence in mutual fund performance", (1997) Journal of Finance 52:57-82.
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "The Persistence of Risk-Adjusted Mutual Fund Performance", (May 1995). NYU
    • Gruber, Martin J., "Another puzzle: the growth in actively managed mutual funds", (1996) Journal of Finance 51:783-810.Working Paper No. FIN-95-018.
    • Cohen, R., Coval, J. and Pastor, L., "Judging fund managers by the company they keep", (2005) Journal of Finance 60:1057-1096.
    • Busse, Jeffrey A. and Irvine. Paul J., "Bayesian alphas and mutual fund persistence", (2006) Journal of Finance 61:2251-2288.
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "Holdings Data, Security Returns and the Selection of Superior Mutual Funds", (July 8, 2009).
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "Does Size Matter? The Relationship between Size and Performance", (May 17, 2011). Fordham University Schools of Business Research Paper No. 1826406.
    • Evans, Richard B. and Gil-Bazo, Javier and Lipson, Marc L., Diseconomies of Scope and Mutual Fund Manager Performance (November 23, 2016).
  7. ↑ The papers in the Bond funds table include:
    • Elton, Edwin J. and Gruber, Martin J. and Blake, Christopher R., "Fundamental Variables, Apt, and Bond Fund Performance", (March 1995). NYU Working Paper No. FIN-94-028.
    • Comer, George and Rodriguez, Javier, "Corporate and Government Bond Funds: An Analysis of Investment Style, Performance, and Cash Flows", (September 11, 2006)
    • Chen, Yong and Ferson, Wayne E. and Peters, Helen, "Measuring the Timing Ability and Performance of Bond Mutual Funds", (September 25, 2009).
  8. ↑ The paper is not available online. Blake, Christopher R., Elton, Edwin J., and Gruber, Martin J., The Performance of Bond Mutual Funds, The Journal of Business Vol. 66, No. 3 (Jul., 1993), pp. 71-403
  9. ↑ The papers in the Mutual fund investor performance table include:
    • Gruber, Martin J., "Another puzzle: the growth in actively managed mutual funds", (1996) Journal of Finance 51:783-810.
    • Benartzi, Shlomo and Thaler, Richard, "Naive diversification strategies in defined contribution saving plans", (2001) American Economic Review 91:79-98.
    • Madrian, Brigitte and Shea, Dennis, "The power of suggestion: inertia in 401(k) participants’ savings", (2001) Quarterly Journal of Economics 116;1149-1187.
    • Liang, Nellie and Weisbenner, Scott J., "Investor Behavior and the Purchase of Company Stock in 401(k) Plans - The Importance of Plan Design", (December 2002) FEDS Working Paper No. FEDS2002-36; AFA 2003 Washington, DC Meetings. Available at SSRN.
    • Elton, Edwin J. and Busse, Jeffrey A. and Gruber, Martin J., "Are Investors Rational? Choices Among Index Funds", (June 2002). NYU Working Paper. Available at SSRN.
    • Ameriks, John and Zeldes, Stephen P., "How Do Household Portfolio Shares Vary With Age?", (September 25, 2000). TIAA-CREF Working Paper. Available at SSRN.
    • Huberman, Gur and Jiang, Wei, "Offering vs. Choice in 401(k) Plans: Equity Exposure and Number of Funds", Journal of Finance, Forthcoming. Available at SSRN.
    • Elton, Edwin J.; Gruber, Martin J.; and Blake, Christopher R, "Participant reaction and the performance of funds offered by 401(k) plans", (2007) Journal of Financial Intermediation 42:240-271.
    • Agnew, Julie and Balduzzi, Pierluigi, "The Reluctant Retirement Trader: Do Asset Returns Overcome Inertia?"' Networks Financial Institute: Working Paper Series: 2012-WP-01. Available at SSRN.

See also

References

  1. ↑ 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 Elton, Edwin J. and Gruber, Martin J., Mutual Funds, (July 27, 2011). Available at SSRN.
  2. ↑ The Sharpe Ratio, William Sharpe, Reprinted from The Journal of Portfolio Management, Fall 1994
  3. ↑ Treynor ratio, Morningstar
  4. ↑ Jenson's alpha, Morningstar
  5. ↑ Measure Your Portfolio's Performance, Cathy Pareto, investopedia, December 16, 2012
  6. ↑ Description of the Treynor - Mazuy Measure
  7. ↑ Henriksson, Roy D., "Market Timing and Mutual Fund Performance: An Empirical Investigation", The Journal of Business Vol. 57, No. 1, Part 1 (Jan., 1984), pp. 73-96
  8. ↑ Henriksson ,Roy D., and Merton, Robert C., "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills" The Journal of Business Vol. 54, No. 4 (Oct., 1981), pp. 513-533
  9. ↑ Description of the Henriksson - Merton Measure
  10. ↑ Elton, Gruber & Blake (2011) [1]
  11. ↑ Chan, Dimmock and Lakonishok, "Benchmarking Money Manager Performance: Issues and Evidence", (August 2006) NBER Working Paper No. 12461.
  12. ↑ Cremers, Martijn and Petajisto, Antti and Zitzewitz, Eric, "Should Benchmark Indices Have Alpha? Revisiting Performance Evaluation", (January 21, 2010). EFA 2009 Bergen Meetings Paper; AFA 2010 Atlanta Meetings Paper. Available at SSRN.
  13. ↑ Elton, Gruber and Blake (1999), "Common Factors in Active and Passive Portfolios",European Finance Review,Vol 3, No 1, 1999. Available at Edwin J. Elton Working Papers
  14. ↑ Fama, Eugene F. and French, Kenneth R., "Versus Skill in the Cross Section of Mutual Fund Returns", (December 14, 2009). Tuck School of Business Working Paper No. 2009-56; Chicago Booth School of Business Research Paper; Journal of Finance, Forthcoming. Available at SSRN
  15. ↑ Evans, Richard B. and Gil-Bazo, Javier and Lipson, Marc L., [ https://ssrn.com/abstract=2874975D Diseconomies of Scope and Mutual Fund Manager Performance] (November 23, 2016),
  16. ↑ Elton, Gruber & Blake "Fundamental Variables, Apt, and Bond Fund Performance", (March 1995). NYU Working Paper No. FIN-94-028.
  17. ↑ Comer & Rodriguez "Corporate and Government Bond Funds: An Analysis of Investment Style, Performance, and Cash Flows", (September 11, 2006)
  18. ↑ Chen, Ferson & Peters "Measuring the Timing Ability and Performance of Bond Mutual Funds", (September 25, 2009).
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