IDEAS home Printed from
   My bibliography  Save this paper

Do Realized Skewness and Kurtosis Predict the Cross-Section of Equity Returns?


  • Diego Amaya

    () (HEC Montreal - Department of Management Sciences)

  • Peter Christoffersen

    () (University of Toronto - Rotman School of Management and CREATES)

  • Kris Jacobs

    () (University of Houston - C.T. Bauer College of Business)

  • Aurelio Vasquez

    () (Instituto Tecnológico Autónomo de México (ITAM) - Department of Business Administration)


Yes. We use intraday data to compute weekly realized variance, skewness and kurtosis for individual equities and assess whether this week?s realized moments predict next week?s stock returns in the cross-section. We sort stocks each week according to their past realized moments, form decile portfolios and analyze subsequent weekly returns. We ?nd a very strong negative relationship between realized skewness and next week?s stock returns, and a positive relationship between realized kurtosis and next week?s stock returns. We do not ?nd a strong relationship between realized volatility and stock returns. A trading strategy that buys stocks in the lowest realized skewness decile and sells stocks in the highest realized skewness decile generates an average weekly return of 43 basis points with a t-statistic of 8:91. A similar strategy that buys stocks with high realized kurtosis and sells stocks with low realized kurtosis produces a weekly return of 16 basis points with a t-statistic of 2:98. Our results are robust across sample periods, portfolio weightings, and proxies for ?rm characteristics, and they are not captured by the Fama-French and Carhart factors.

Suggested Citation

  • Diego Amaya & Peter Christoffersen & Kris Jacobs & Aurelio Vasquez, 2011. "Do Realized Skewness and Kurtosis Predict the Cross-Section of Equity Returns?," CREATES Research Papers 2011-44, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2011-44

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Jia Li & Andrew J. Patton, 2013. "Asymptotic Inference about Predictive Accuracy Using High Frequency Data," Working Papers 13-27, Duke University, Department of Economics.
    2. Campbell R. Harvey & Yan Liu & Heqing Zhu, 2014. ". . . and the Cross-Section of Expected Returns," NBER Working Papers 20592, National Bureau of Economic Research, Inc.

    More about this item


    Realized volatility; skewness; kurtosis; equity markets; return prediction.;

    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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aah:create:2011-44. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.