A meta-analysis of mutual fund performance

  • T. Daniel Coggin
  • John E. Hunter


The purpose of this article is to introduce the statistical technique of meta-analysis of regression results using as our example the Lee and Rahmann (1990) study of the performance of 93 mutual funds. Specifically, we derive and estimate the meta-analysis formulas, explicitly adjusted for correlated regression residuals, which quantify the effect of sampling error on their reported regression results. Our analysis of selectivity reveals some real variation around a mean risk-adjusted excess return of about 1% per year; while our analysis of market timing reveals some real variation around a negative mean value and confirms that the correction for heteroscedasticity does make a difference. An examination of the 80% probability interval for the mean selectivity value indicates that the best mutual funds can deliver substantial risk-adjusted excess returns.

Key words

Meta-analysis econometric estimation investment performance measurement U.S. mutual funds 


  1. Bhattacharya, S and Pfleiderer, P., “A Note on Performance Evaluation.” Technical Report No. 714, Graduate School of Business, Stanford University, Stanford, CA (1983).Google Scholar
  2. Birge, R.T., “The Calculation of Errors by the Method of Least Squares.”Physical Review 40, 207–227, (1932).CrossRefGoogle Scholar
  3. Breen, W., Jagannathan, R. and Ofer, A.R., “Correcting for Heteroscedasticity in Tests for Market Timing.”Journal of Business 59, 585–598, (1986).CrossRefGoogle Scholar
  4. Chang, E.C. and Lewellen, W.G., “Market Timing and Mutual Fund Investment Peformance.”Journal of Business 56, 57–72, (1984).CrossRefGoogle Scholar
  5. Christie, A.A., “Aggregation of Test Statistics.”Journal of Accounting and Economics 12, 15–36, (1990).CrossRefGoogle Scholar
  6. Chua, J.H. and Woodward, R.S.,Gains from Market Timing. Monograph No. 1986-2, Graduate School of Business Administration, New York University, New York, NY (1986).Google Scholar
  7. Coggin, T.D. and Hunter, J.E., “Problems in Measuring the Quality of Investment Information.”Financial Analysts Journal 39, 25–33, (1983).CrossRefGoogle Scholar
  8. Coggin, T.D. and Hunter, J.E., “A Meta-Analysis of Pricing ‘Risk’ Factors in APT.”Journal of Portfolio Management 14, 35–38, (1987).CrossRefGoogle Scholar
  9. Cohen, J.,Statistical Power Analysis for the Behavioral Sciences. 2nd ed., Hillsdale, NJ: Lawrence Erlbaum Associates, (1988).Google Scholar
  10. Connor, G. and Korajczyk, R.A., “The Attributes, Behavior and Performance of U.S. Mutual Funds.”Review of Quantitative Finance and Accounting 1, 5–26, (1991).Google Scholar
  11. Dimson, E. and Marsh, P., “An Analysis of Brokers' and Analysts' Unpublished Forecasts of UK Stock Returns.”Journal of Finance 39, 1257–1292, (1984).Google Scholar
  12. Farley J.U. and Lehmann, D.R.,Meta-Analysis in Marketing. Lexington, MA: Lexington Books, 1986.Google Scholar
  13. Glass, G.V., “Primary, Secondary and Meta-Analysis of Research.”Educational Researcher 5, 3–8, (1976).CrossRefGoogle Scholar
  14. Glass, G.V., “Integrating Findings.”Review of Research in Education 5, 351–379, (1977).CrossRefGoogle Scholar
  15. Grinblatt, M. and Titman, S., “Mutual Fund Performance.”Journal of Business 62, 393–416, (1989).CrossRefGoogle Scholar
  16. Halvorsen, K.T., “Combining Results from Independent Investigations.” in J.C. Bailar and F. Mosteller, eds.,Medical Uses of Statistics. Waltham, MA: NEJM Books, 1986.Google Scholar
  17. Hedges, L.V. and Olkin, I.,Statistical Methods for Meta-Analysis. Orlando, FL: Academic Press, 1985.Google Scholar
  18. Henriksson, R.D., “Market Timing and Mutual Fund Performance.”Journal of Business 57, 73–96, (1984).CrossRefGoogle Scholar
  19. Henriksson, R.D. and Merton, R.C., “On Market Timing and Investment Performance II.”Journal of Business 54, 513–533, (1981).CrossRefGoogle Scholar
  20. Hunter, J.E. and Coggin, T.D., “The Sampling Error in the Average Correlation.” Working Paper, Michigan State University, East Lansing, MI (1992).Google Scholar
  21. Hunter, J.E., Coggin, T.D. and Rahman, S., “The Correlation Between Sampling Errors in Estimating Security Selection and Market Timing Ability.” Working Paper, Michigan State University, East Lansing, MI (1992).Google Scholar
  22. Hunter, J.E. and Schmidt, F.L.,Methods of Meta-Analysis. Newbury Park, CA: Sage Publications, 1990.Google Scholar
  23. Jagannathan, R. and Korajczyk, R.A., “Assessing the Market Timing Performance of Managed Portofolios.”Journal of Business 59, 217–235, (1986).CrossRefGoogle Scholar
  24. Johnston, J.,Econometric Methods. 3rd ed., New York, NY: McGraw-Hill, 1984.Google Scholar
  25. Kon, S.J., “The Market-Timing Performance of Mutual Fund Managers.”Journal of Business 56, 323–347, (1983).CrossRefGoogle Scholar
  26. Lee, C.F. and Rahman, S. “Market Timing, Selectivity, and Mutual Fund Performance.”Journal of Business 63, 261–278, (1990).CrossRefGoogle Scholar
  27. Lehmann, B.N. and Modest, D.M., “Mutual Fund Performance Evaluation.”Journal of Finance 42, 233–265, (1987).Google Scholar
  28. Schmidt, F.L. and Hunter, J.E., “Development of a General Solution to the Problem of Validity Generalization.”Journal of Applied Psychology 62, 529–540, (1977).CrossRefGoogle Scholar
  29. Thorndike, R.L.,Applied Psychometrics, Boston, MA: Houghton Mifflin, 1982.Google Scholar
  30. Treynor, J.L. and Mazuy, K., “Can Mutual Funds Outguess the Market?”Harvard Business Review. 44 131–136 (1966).Google Scholar
  31. Trotman, K.T. and Wood, R., “A Meta-Analysis of Studies on Internal Control Judgments.”Journal of Accounting Research 29, 180–192 (1991).Google Scholar

Copyright information

© Kluwer Academic Publishers 1993

Authors and Affiliations

  • T. Daniel Coggin
    • 1
  • John E. Hunter
    • 2
  1. 1.Virginia Retirement SystemRichmond
  2. 2.Department of PsychologyMichigan State UniversityEast Lansing

Personalised recommendations