Expected Idiosyncratic Volatility Measures and Expected Returns

Authors

  • Jason D. Fink,

  • Kristin E. Fink,

  • Hui He

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    • Jason D. Fink is the Chandler/Universal Professor of Banking at James Madison University in Harrisonburg, VA. Kristin E. Fink is a Professor at James Madison University in Harrisonburg, VA. Hui He is an Assistant Professor at James Madison University in Harrisonburg, VA.


  • The authors would like to thank Geert Bekaert, Pamela Drake, and Qianqiu Liu for helpful discussions and/or correspondence, and John Battipaglia for excellent research assistance. We especially thank Maria Schutte and James Weston for important conversations that significantly strengthened this paper. The suggestions of two anonymous referees and Marc Lipson (Editor) led to significant improvements in this paper. All volatility data is provided at http://people.jmu.edu/hehx/index.html.

Abstract

We find that idiosyncratic volatility forecasts using information available to traders at the time of the forecast are not related to expected returns. The positive relation documented in a number of other papers only exists when forward-looking information is incorporated into the volatility estimate. That positive relation is driven by the realized idiosyncratic volatility component that cannot be forecasted by investors. Our findings are robust to several different empirical tests, volatility forecasting models and time periods.

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