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Explaining the idiosyncratic volatility puzzle using Stochastic Discount Factors

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  • Chabi-Yo, Fousseni

Abstract

I use Stochastic Discount Factors to examine the sources of the idiosyncratic volatility premium. I find that non-zero risk aversion and firms' non-systematic coskewness determine the premium on idiosyncratic volatility risk. The firm's non-systematic coskewness measures the comovement of the asset's volatility with the market return. When I control for the non-systematic coskewness factor, I find no significant relation between idiosyncratic volatility and stock expected returns. My results are robust across different sample periods and firm characteristics.

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  • Chabi-Yo, Fousseni, 2011. "Explaining the idiosyncratic volatility puzzle using Stochastic Discount Factors," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1971-1983, August.
  • Handle: RePEc:eee:jbfina:v:35:y:2011:i:8:p:1971-1983
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    1. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    2. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    3. 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.
    4. Turan G. Bali & Armen Hovakimian, 2009. "Volatility Spreads and Expected Stock Returns," Management Science, INFORMS, vol. 55(11), pages 1797-1812, November.
    5. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    6. Brian Boyer & Todd Mitton & Keith Vorkink, 2010. "Expected Idiosyncratic Skewness," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 169-202, January.
    7. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    8. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    9. Arisoy, Yakup Eser, 2010. "Volatility risk and the value premium: Evidence from the French stock market," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 975-983, May.
    10. Taylor, Stephen J. & Yadav, Pradeep K. & Zhang, Yuanyuan, 2010. "The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 871-881, April.
    11. Matthew Spiegel & Xiaotong Wang, 2005. "Cross-sectional Variation in Stock Returns: Liquidity and Idiosyncratic Risk," Yale School of Management Working Papers amz2540, Yale School of Management, revised 01 Mar 2006.
    12. 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.
    13. 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.
    14. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    15. Gurdip Bakshi & Nikunj Kapadia & Dilip Madan, 2003. "Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options," Review of Financial Studies, Society for Financial Studies, vol. 16(1), pages 101-143.
    16. Todd Mitton & Keith Vorkink, 2007. "Equilibrium Underdiversification and the Preference for Skewness," Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1255-1288.
    17. Jiang, George J. & Tian, Yisong S., 2010. "Misreaction or misspecification? A re-examination of volatility anomalies," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2358-2369, October.
    18. 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.
    19. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    20. Guo, Hui & Savickas, Robert, 2010. "Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1637-1649, July.
    21. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
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    8. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Multi-factor volatility and stock returns," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 132-149.
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