Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-08T07:20:53.269Z Has data issue: false hasContentIssue false
  • English
  • Français

Another Look at Mutual Fund Tournaments

Published online by Cambridge University Press:  06 April 2009

Jeffrey A. Busse
Get access Rights & Permissions [Opens in a new window]

Abstract

Daily retutns are used to examine how mutual funds actively alter the risk of their portfolios in response to past performance. Compared to monthly data, daily returns produce much more efficient estimates of fund volatility, which give vastly different inferences about the behavior of fund managers. In particular, monthly results consistent with under-performers increasing their risk relative to better performing funds disappear with daily data. The differences in the monthly and daily results arise from biases in the monthly volatility estimates attributable to daily return autocorrelation.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 36 , Issue 1 , March 2001 , pp. 53 - 73
Copyright
Copyright © School of Business Administration, University of Washington 2001

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Goizueta Business School, Emory University, 1300 Clifton Rd., Atlanta, GA 30322–2722, email: [email protected]. I especially appreciate the helpful comments of Wayne Ferson (associate editor and referee). I also appreciate the comments of Viral Acharya, Edwin Elton, Young Ho Eom, Martin Gruber, Anthony Lunch, Paul Malatesta (the editor), Lubos Pastor, Matthew Richardson, Charles Trzcinka, University of North Carolina, and the 1998 European Finance Association meetings.

References

Boudoukh, J.; Richardson, M.; and Whitelaw, R.. “A Tale of Three Schools: Insights on Autocorrelations of Short-Horizon Stock Returns.” Riview of Financial Studies, 7 (1994), 539–573.10.1093/rfs/7.3.539CrossRefGoogle Scholar
Brown, K.; Harlow, W.; and Starks, L.. “Of Tournaments and Temptations: An Analysis of Managerial Incentives in the Mutual Fund Industry.” Journal fo Finance, 51 (1996), 85–110.10.2307/2329303CrossRefGoogle Scholar
Busse, J.; “Volatility Timing in Mutual Funds: Evidence from Daily Returns.” Review of Financial Studies, 12 (1999), 1009–1041.10.1093/rfs/12.5.1009CrossRefGoogle Scholar
Carhart, M.; “On persistence in Mutual Fund Performance.” Journal of Finance, 52 (1997), 57–82.10.2307/2329556CrossRefGoogle Scholar
Chalmers, J.; Edelen, R.; and Kadlec, G.. “On the perils of Security Pricing by Financial Intermediaries: The Case of Open-End Mutual Funds.” Working Paper, Univ. of Oregon (2000).Google Scholar
Chevakuer, J.; and Ellison, G.. “Risk Taking by Mutual Funds as a Response to Incentives.” Journal of Political Economy. 105 (1997), 1167–1200.10.1086/516389Google Scholar
Dimson, E.; “Risk Measurement when Shares Are Subject to Infrequent Trading.” Journal of Financial Economics, 7 (1979), 197–226.10.1016/0304-405X(79)90013-8CrossRefGoogle Scholar
Fama, E.; and French, K.. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Financial Economics, 33 (1993), 3–56.10.1016/0304-405X(93)90023-5CrossRefGoogle Scholar
Ferson, W.; and Harvey, C.. “Conditioning Variables and the Cross Section of Stock Returns.” Journal of Finance, 54 (1999), 1325–1360.10.1111/0022-1082.0014810.1111/0022-1082.00148CrossRefGoogle Scholar
Ferson, W.; Sarkissian, S.; and simin, T.. “The Alpha Factor Asset Pricing Model: A Parable.” Journal of Financial Markets, 2 (1999), 49–68.10.1016/S1386-4181(98)00005-610.1016/S1386-4181(98)00005-6CrossRefGoogle Scholar
Grinblatt, M.; Titman, S.; and Wermers, R.. “Momentum Investment Strategies, Portfolio performance, and Herding: A study of Mutual Fund Behavior.” American Economic Review, 85 (1995), 1088–1105.Google Scholar
Hameed, A. “Time-Varying Factors and Cross-Autocorrelations in Short Horizon Stock Returns.” Journal of Financial Research, 20 (1997), 435–458.CrossRefGoogle Scholar
Jegadeesh, N., and Titman, S.. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” Journal of Finance, 48 (1993) 65–91.10.2307/2328882CrossRefGoogle Scholar
Kadlec, G., and patterson, D.. “A Transactions Data Analysis of Nonsynchronous Trading.” Review of Financial Studies, 12 (1999), 609–630.10.1093/rfs/12.3.609CrossRefGoogle Scholar
Keim, D. “Size-Related Anomalies and Stock Return Seasonality: Further Empirical Evidence.” Journal Economices, 12 (1983), 13–32.Google Scholar
Koski, J., and Pontiff, J.. “How Are Derivatives Used? Evidence from the Mutual Fund Industry.” Journal of Finance, 54 (1999), 791–816.10.1111/0022-1082.00126CrossRefGoogle Scholar
Nelosn, D. “Conditional Heteroskedasticity in Asset Returns: A New Approach.” Econometrica, 59 (1991), 347–370.10.2307/2938260CrossRefGoogle Scholar
Reinganum, M. “The Anomalous Stock Market Behaviorof Small Firms in January: Empirical Tests for Tax-Loss Selling Effects.” Journal of Financial Economics, 12 (1983), 89–104.10.1016/0304-405X(83)90029-6CrossRefGoogle Scholar
Sias, E., and Starks, L.. “Return Autocorrelation and Institutional Investors.” Journal of Financial Economics, 46 (1997), 103–131.10.1016/S0304-405X(97)00026-3CrossRefGoogle Scholar
Sirri, E., and Tufano, P.. “Costly Search and Mutual Fund Flows.” Journal of Finance, 53 (1998), 1589–1622.10.1111/0022-1082.00066CrossRefGoogle Scholar
Wiesenberger Inc. Mutual Funds Panorama. New York, NY: Wiesenberger Investment Companies, (1985).Google Scholar