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Efficiency tests for mutual fund portfolios


  • Jati Sengupta


A set of nonparametric tests which includes the convex hull method and the stochastic dominance criteria is developed here for evaluating the performance of mutual fund portfolios. The empirical results support the hypothesis that some groups of funds based on new technology tend to outperform the others and in most cases the investor shows a preference for skewness, thus emphasizing an asymmetry in the mean variance relationship. Technology funds tend to exhibit second order stochastic dominance over the income and growth funds. This shows some new features of the mean variance efficiency frontier.

Suggested Citation

  • Jati Sengupta, 2003. "Efficiency tests for mutual fund portfolios," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 869-876.
  • Handle: RePEc:taf:apfiec:v:13:y:2003:i:12:p:869-876 DOI: 10.1080/09603100210161992

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    References listed on IDEAS

    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Liesenfeld, Roman, 1998. "Dynamic Bivariate Mixture Models: Modeling the Behavior of Prices and Trading Volume," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 101-109, January.
    3. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    4. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    5. Richardson, Matthew & Smith, Tom, 1994. "A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(01), pages 101-116, March.
    6. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665 National Bureau of Economic Research, Inc.
    7. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
    8. Lamoureux, Christopher G & Lastrapes, William D, 1994. "Endogenous Trading Volume and Momentum in Stock-Return Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 253-260, April.
    9. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    10. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(02), pages 127-141, June.
    11. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    12. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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    Cited by:

    1. Mohammad Reza TAVAKOLI BAGHDADABAD & Afsaneh NOORI HOUSHYAR, 2014. "Productivity and Efficiency Evaluation of US Mutual Funds," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 120-143, March.
    2. Amporn SOONGSWANG & Yosawee SANOHDONTREE, 2011. "Equity Mutual Fund: Performances, Persistence and Fund Rankings," Journal of Knowledge Management, Economics and Information Technology,, vol. 1(6), pages 1-27, October.
    3. Lamb, John D. & Tee, Kai-Hong, 2012. "Data envelopment analysis models of investment funds," European Journal of Operational Research, Elsevier, vol. 216(3), pages 687-696.
    4. Babalos, Vassilios & Mamatzakis, Emmanuel C. & Matousek, Roman, 2015. "The performance of US equity mutual funds," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 217-229.
    5. Huyen Nguyen-Thi-Thanh, 2006. "Quantitative selection of hedge funds using data envelopment analysis," Post-Print halshs-00067742, HAL.
    6. Babalos, Vassilios & Caporale, Guglielmo Maria & Philippas, Nikolaos, 2012. "Efficiency evaluation of Greek equity funds," Research in International Business and Finance, Elsevier, vol. 26(2), pages 317-333.
    7. Agata Sielska, 2010. "Multicriteria rankings of open-end investment funds and their stability," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 1, pages 111-129.
    8. repec:eee:jomega:v:75:y:2018:i:c:p:57-76 is not listed on IDEAS
    9. Huyen Nguyen-Thi-Thanh, 2006. "On the Use of Data Envelopment Analysis in Hedge Fund Performance Appraisal," Working Papers halshs-00120292, HAL.
    10. Tarnaud, Albane Christine & Leleu, Hervé, 2018. "Portfolio analysis with DEA: Prior to choosing a model," Omega, Elsevier, vol. 75(C), pages 57-76.
    11. Vassilios Babalos & Michael Doumpos & Nikolaos Philippas & Constantin Zopounidis, 2015. "Towards a Holistic Approach for Mutual Fund Performance Appraisal," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 35-53, June.
    12. Babalos, Vassilios & Philippas, Nikolaos & Doumpos, Michael & Zompounidis, Constantin, 2011. "Mutual funds performance appraisal using stochastic multicriteria acceptability analysis," MPRA Paper 37953, University Library of Munich, Germany.

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