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Volatility and mutual fund manager skill

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  • Jordan, Bradford D.
  • Riley, Timothy B.

Abstract

In a standard four-factor framework, mutual fund return volatility is a reliable, persistent, and powerful predictor of future abnormal returns. However, the abnormal returns are eliminated by the addition of a “vol” anomaly factor contrasting returns on portfolios of low and high volatility stocks. Consistent with Novy-Marx (2014) and Fama and French (2014), the Fama and French (2015) profitability and investment factors are equally effective at eliminating the abnormal returns. Failure to account for the vol anomaly, either directly or indirectly, can lead to substantial mismeasurement of fund manager skill.

Suggested Citation

  • Jordan, Bradford D. & Riley, Timothy B., 2015. "Volatility and mutual fund manager skill," Journal of Financial Economics, Elsevier, vol. 118(2), pages 289-298.
  • Handle: RePEc:eee:jfinec:v:118:y:2015:i:2:p:289-298
    DOI: 10.1016/j.jfineco.2015.06.012
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    References listed on IDEAS

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    1. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    2. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
    3. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    4. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    5. 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.
    6. Richard B. Evans, 2010. "Mutual Fund Incubation," Journal of Finance, American Finance Association, vol. 65(4), pages 1581-1611, August.
    7. Haugen, Robert A. & Heins, A. James, 1975. "Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 10(5), pages 775-784, December.
    8. 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.
    9. Robert Novy-Marx, 2014. "Understanding Defensive Equity," NBER Working Papers 20591, National Bureau of Economic Research, Inc.
    10. Yufeng Han & David Lesmond, 2011. "Liquidity Biases and the Pricing of Cross-sectional Idiosyncratic Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1590-1629.
    11. 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.
    12. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    13. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    14. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    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.
    16. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    17. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    18. Itamar Drechsler & Qingyi Freda Drechsler, 2014. "The Shorting Premium and Asset Pricing Anomalies," NBER Working Papers 20282, National Bureau of Economic Research, Inc.
    19. Joseph Chen & Harrison Hong & Ming Huang & Jeffrey D. Kubik, 2004. "Does Fund Size Erode Mutual Fund Performance? The Role of Liquidity and Organization," American Economic Review, American Economic Association, vol. 94(5), pages 1276-1302, December.
    20. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    21. Blitz, D.C. & van Vliet, P., 2007. "The Volatility Effect: Lower Risk without Lower Return," ERIM Report Series Research in Management ERS-2007-044-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    More about this item

    Keywords

    Mutual funds; Skill; Volatility; Market efficiency; Anomaly;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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