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Expected Idiosyncratic Skewness

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  • Brian Boyer
  • Todd Mitton
  • Keith Vorkink
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    Abstract

    We test the prediction of recent theories that stocks with high idiosyncratic skewness should have low expected returns. Because lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Consistent with recent theories, we find that expected idiosyncratic skewness and returns are negatively correlated. Specifically, the Fama-French alpha of a low-expected-skewness quintile exceeds the alpha of a high-expected-skewness quintile by 1.00% per month. Furthermore, the coefficients on expected skewness in Fama-MacBeth cross-sectional regressions are negative and significant. In addition, we find that expected skewness helps explain the phenomenon that stocks with high idiosyncratic volatility have low expected returns. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

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    Bibliographic Info

    Article provided by Society for Financial Studies in its journal The Review of Financial Studies.

    Volume (Year): 23 (2010)
    Issue (Month): 1 (January)
    Pages: 169-202

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    Handle: RePEc:oup:rfinst:v:23:y:2010:i:1:p:169-202

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    Cited by:
    1. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Asset Prices," American Economic Review, American Economic Association, vol. 103(3), pages 623-28, May.
    2. Rui Albuquerque, 2012. "Skewness in Stock Returns: Reconciling the Evidence on Firm Versus Aggregate Returns," Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1630-1673.
    3. Jiang, Danling, 2013. "The second moment matters! Cross-sectional dispersion of firm valuations and expected returns," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3974-3992.
    4. Cao, Jie & Han, Bing, 2013. "Cross section of option returns and idiosyncratic stock volatility," Journal of Financial Economics, Elsevier, vol. 108(1), pages 231-249.
    5. Ruenzi, Stefan & Weigert, Florian, 2011. "Crash Sensitivity and the Cross-Section of Expected Stock Returns," Working Papers on Finance 1324, University of St. Gallen, School of Finance, revised Mar 2013.
    6. Peter Christoffersen & Vihang Errunza & Kris Jacobs & Hugues Langlois, 2012. "Is the Potential for International Diversi?cation Disappearing? A Dynamic Copula Approach," CREATES Research Papers 2012-48, School of Economics and Management, University of Aarhus.
    7. Li, Yan & Yang, Liyan, 2013. "Prospect theory, the disposition effect, and asset prices," Journal of Financial Economics, Elsevier, vol. 107(3), pages 715-739.
    8. FJohn A. Doukas & Wenjia Zhang, 2013. "Managerial gambling attitudes: evidence from bank acquisitions," Review of Behavioral Finance, Emerald Group Publishing, vol. 5(1), pages 4-34, February.
    9. Robert F. Stambaugh & Jianfeng Yu & Yu Yuan, 2012. "Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle," NBER Working Papers 18560, National Bureau of Economic Research, Inc.
    10. Annaert, Jan & De Ceuster, Marc & Verstegen, Kurt, 2013. "Are extreme returns priced in the stock market? European evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3401-3411.
    11. Chang, Eric C. & Cheng, Joseph W. & Pinegar, J. Michael & Yu, Yinghui, 2012. "Short-sale constraints: Reductions in costs of capital or overvaluation? Evidence from Hong Kong," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 506-520.
    12. Helga Fehr-Duda & Thomas Epper, 2012. "Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk Preferences," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 567-593, 07.
    13. 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.
    14. 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.
    15. Giuseppe arbia, 2014. "Least quartic Regression Criterion with Application to Finance," Papers 1403.4171, arXiv.org.
    16. Huang, Wei & Liu, Qianqiu & Ghon Rhee, S. & Wu, Feng, 2012. "Extreme downside risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1492-1502.

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