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Mutual Funds Performance Assessment Techniques: Comparative Analysis

Author

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  • Anna E. Olkova

    (Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow 119571, Russia)

Abstract

The article examines existing approaches to assessing mutual funds portfolio performance. The author considers major advantages and drawbacks of diverse upside potential and risk measures, as well as the most commonly used portfolio efficiency metrics. Empirical evidence of 12 most popular performance measures on a base of 255 Russian mutual funds sample is provided. Moreover, the author demonstrates that semi-variance and alpha-based metrics yield rankings that differ essentially from those provided by volatility-based, VaR-based and other metrics. Finally, the article discusses the rationale for different performance measures use.

Suggested Citation

  • Anna E. Olkova, 2017. "Mutual Funds Performance Assessment Techniques: Comparative Analysis," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 85-95, June.
  • Handle: RePEc:fru:finjrn:170307:p:85-95
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    References listed on IDEAS

    as
    1. Jensen, Michael C, 1969. "Risk, The Pricing of Capital Assets, and the Evaluation of Investment Portfolios," The Journal of Business, University of Chicago Press, vol. 42(2), pages 167-247, April.
    2. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    3. Carlo Acerbi, 2007. "Coherent measures of risk in everyday market practice," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 359-364.
    4. Yitzhaki, Shlomo, 1982. "Stochastic Dominance, Mean Variance, and Gini's Mean Difference," American Economic Review, American Economic Association, vol. 72(1), pages 178-185, March.
    5. Farinelli, Simone & Tibiletti, Luisa, 2008. "Sharpe thinking in asset ranking with one-sided measures," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1542-1547, March.
    6. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
    7. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    8. Darolles, Serge & Gourieroux, Christian & Jasiak, Joann, 2009. "L-performance with an application to hedge funds," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 671-685, September.
    9. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    10. Ang, James S. & Chua, Jess H., 1979. "Composite Measures for the Evaluation of Investment Performance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 14(2), pages 361-384, June.
    11. Antonio E. Bernardo & Olivier Ledoit, 2000. "Gain, Loss, and Asset Pricing," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 144-172, February.
    12. Eling, Martin & Schuhmacher, Frank, 2007. "Does the choice of performance measure influence the evaluation of hedge funds?," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2632-2647, September.
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    More about this item

    Keywords

    mutual funds; portfolio management; performance measurement; risk measurement; Sharpe ratio; Sortino ratio; downside risk measures;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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