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Estimation of skill of Russian mutual fund managers

Author

Listed:
  • Parshakov, Petr

    () (Higher School of Economics (Perm), Russia)

Abstract

Our work is focused on Russian mutual funds managers’ skills versus luck estimating. Using bootstrap procedure we build Jensen’s alpha density for each fund. We find that only 5% of Russian equity mutual funds do have skills (in contrast to luck) to outperform the benchmark.

Suggested Citation

  • Parshakov, Petr, 2015. "Estimation of skill of Russian mutual fund managers," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 37(1), pages 57-66.
  • Handle: RePEc:ris:apltrx:0257
    as

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    File URL: http://pe.cemi.rssi.ru/pe_2015_1_57-66.pdf
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    References listed on IDEAS

    as
    1. Michael C. Jensen, 1968. "The Performance Of Mutual Funds In The Period 1945–1964," Journal of Finance, American Finance Association, vol. 23(2), pages 389-416, May.
    2. L. M. Doncel & P. Grau & J. Otamendi & J. Sainz, 2011. "The truth about mutual funds across Europe," Applied Economics Letters, Taylor & Francis Journals, vol. 18(7), pages 687-692.
    3. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    4. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    5. Nicolas P. B. Bollen, 2005. "Short-Term Persistence in Mutual Fund Performance," Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 569-597.
    6. Kliger, Doron & Levy, Ori & Sonsino, Doron, 2003. "On absolute and relative performance and the demand for mutual funds--experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 52(3), pages 341-363, November.
    7. Marcin Kacperczyk & Stijn Van Nieuwerburgh & Laura Veldkamp, 2014. "Time-Varying Fund Manager Skill," Journal of Finance, American Finance Association, vol. 69(4), pages 1455-1484, August.
    8. Chen, Yong & Liang, Bing, 2007. "Do Market Timing Hedge Funds Time the Market?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(04), pages 827-856, December.
    9. Ayadi, Mohamed A. & Kryzanowski, Lawrence, 2011. "Fixed-income fund performance: Role of luck and ability in tail membership," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 379-392, June.
    10. Nuttall, John, 2007. "Flaw in the fund skill/luck test method of Cuthbertson et al," MPRA Paper 1584, University Library of Munich, Germany.
    11. Robert Kosowski & Allan Timmermann & Russ Wermers & Hal White, 2006. "Can Mutual Fund "Stars" Really Pick Stocks? New Evidence from a Bootstrap Analysis," Journal of Finance, American Finance Association, vol. 61(6), pages 2551-2595, December.
    12. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2008. "UK mutual fund performance: Skill or luck?," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 613-634, September.
    13. Kosowski, Robert & Naik, Narayan Y. & Teo, Melvyn, 2007. "Do hedge funds deliver alpha? A Bayesian and bootstrap analysis," Journal of Financial Economics, Elsevier, vol. 84(1), pages 229-264, April.
    14. Stanislav Anatolyev, 2007. "The basics of bootstrapping (in Russian)," Quantile, Quantile, issue 3, pages 1-12, September.
    15. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross-Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    picking; skill; mutual fund;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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