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Expected skewness and momentum

Author

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  • Jacobs, Heiko
  • Regele, Tobias
  • Weber, Martin

Abstract

Motivated by the time-series insights of Daniel and Moskowitz (2016), we investigate the link between expected skewness and momentum in the cross-section. The alpha of skewness-enhanced (-weakened) momentum is about twice (half) as large as the traditional alpha. These findings are driven by the short leg. Portfolio sorts, Fama-MacBeth regressions, and the market reaction to earnings announcements suggest that expected skewness is an important determinant of momentum. Due to the simplicity of the approach, its economic magnitude, its existence among large stocks, and the success of risk management, the results are difficult to reconcile with the efficient market hypothesis.

Suggested Citation

  • Jacobs, Heiko & Regele, Tobias & Weber, Martin, 2016. "Expected skewness and momentum," CEPR Discussion Papers 11455, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11455
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    as
    1. Fama, Eugene F & French, Kenneth R, 1992. " The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    3. X. Frank Zhang, 2006. "Information Uncertainty and Stock Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 105-137, February.
    4. Novy-Marx, Robert, 2013. "The other side of value: The gross profitability premium," Journal of Financial Economics, Elsevier, vol. 108(1), pages 1-28.
    5. Jacobs, Heiko, 2015. "What explains the dynamics of 100 anomalies?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 65-85.
    6. Bates, David S., 2008. "The market for crash risk," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2291-2321, July.
    7. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    8. 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.
    9. Jennifer Conrad & Robert F. Dittmar & Eric Ghysels, 2013. "Ex Ante Skewness and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 68(1), pages 85-124, February.
    10. Zhi Da & Umit G. Gurun & Mitch Warachka, 2014. "Frog in the Pan: Continuous Information and Momentum," Review of Financial Studies, Society for Financial Studies, vol. 27(7), pages 2171-2218.
    11. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2001. "Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices," Journal of Financial Economics, Elsevier, vol. 61(3), pages 345-381, September.
    12. 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.
    13. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    14. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    15. Jegadeesh, Narasimhan, 1990. " Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    16. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    17. Grinblatt, Mark & Han, Bing, 2005. "Prospect theory, mental accounting, and momentum," Journal of Financial Economics, Elsevier, vol. 78(2), pages 311-339, November.
    18. 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.
    19. Doron Avramov & Tarun Chordia & Gergana Jostova & Alexander Philipov, 2007. "Momentum and Credit Rating," Journal of Finance, American Finance Association, vol. 62(5), pages 2503-2520, October.
    20. Almazan, Andres & Brown, Keith C. & Carlson, Murray & Chapman, David A., 2004. "Why constrain your mutual fund manager?," Journal of Financial Economics, Elsevier, vol. 73(2), pages 289-321, August.
    21. Anne-Marie Anderson & Edward A. Dyl, 2005. "Market Structure And Trading Volume," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(1), pages 115-131.
    22. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    23. Markus K. Brunnermeier & Jonathan A. Parker & Christian Gollier, 2007. "Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns," American Economic Review, American Economic Association, vol. 97(2), pages 159-165, May.
    24. Charles M.C. Lee & Bhaskaran Swaminathan, 2000. "Price Momentum and Trading Volume," Journal of Finance, American Finance Association, vol. 55(5), pages 2017-2069, October.
    25. Conrad, Jennifer & Kapadia, Nishad & Xing, Yuhang, 2014. "Death and jackpot: Why do individual investors hold overpriced stocks?," Journal of Financial Economics, Elsevier, vol. 113(3), pages 455-475.
    26. Hongwei Chuang & Hwai-Chung Ho, 2014. "Implied Price Risk and Momentum Strategy," Review of Finance, European Finance Association, vol. 18(2), pages 591-622.
    27. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    28. Grinblatt, Mark & Moskowitz, Tobias J., 2004. "Predicting stock price movements from past returns: the role of consistency and tax-loss selling," Journal of Financial Economics, Elsevier, vol. 71(3), pages 541-579, March.
    29. John M. Griffin & Nicholas H. Hirschey & Patrick J. Kelly, 2011. "How Important Is the Financial Media in Global Markets?," Review of Financial Studies, Society for Financial Studies, vol. 24(12), pages 3941-3992.
    30. Pavel Bandarchuk & Jens Hilscher, 2013. "Sources of Momentum Profits: Evidence on the Irrelevance of Characteristics," Review of Finance, European Finance Association, vol. 17(2), pages 809-845.
    31. Thomas J. George & Chuan-Yang Hwang, 2004. "The 52-Week High and Momentum Investing," Journal of Finance, American Finance Association, vol. 59(5), pages 2145-2176, October.
    32. repec:hrv:faseco:30747159 is not listed on IDEAS
    33. Chordia, Tarun & Subrahmanyam, Avanidhar & Tong, Qing, 2014. "Have capital market anomalies attenuated in the recent era of high liquidity and trading activity?," Journal of Accounting and Economics, Elsevier, vol. 58(1), pages 41-58.
    34. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    35. Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
    36. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Momentum has its moments," Journal of Financial Economics, Elsevier, vol. 116(1), pages 111-120.
    37. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
    38. John M. Griffin & Patrick J. Kelly & Federico Nardari, 2010. "Do Market Efficiency Measures Yield Correct Inferences? A Comparison of Developed and Emerging Markets," Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 3225-3277, August.
    39. Clifford S. Asness & Tobias J. Moskowitz & Lasse Heje Pedersen, 2013. "Value and Momentum Everywhere," Journal of Finance, American Finance Association, vol. 68(3), pages 929-985, June.
    40. Matteo P. Arena & K. Stephen Haggard & Xuemin (Sterling) Yan, 2008. "Price Momentum and Idiosyncratic Volatility," The Financial Review, Eastern Finance Association, vol. 43(2), pages 159-190, May.
    41. Ozgur S. Ince & R. Burt Porter, 2006. "INDIVIDUAL EQUITY RETURN DATA FROM THOMSON DATASTREAM: HANDLE WITH CARE!," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(4), pages 463-479.
    42. 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.
    43. 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.
    44. Narasimhan Jegadeesh, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
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    Cited by:

    1. Friedrich-Carl Franz & Tobias Regele, 2016. "Beating the DAX, MDAX, and SDAX: investment strategies in Germany," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(2), pages 161-204, May.

    More about this item

    Keywords

    behavioral finance; Market Efficiency; Momentum; return predictability; Skewness;

    JEL classification:

    • 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

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