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Higher moments matter! Cross‐sectional (higher) moments and the predictability of stock returns

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  • Sebastian Stöckl
  • Lars Kaiser

Abstract

In this paper, we investigate the predictive power of signals imputed from the cross‐section of stock returns—namely cross‐sectional volatility, skewness, and kurtosis—to forecast the time series. Adding to the existing literature, which documents cross‐sectional volatility to forecast a decline in the equity premium with high in‐ and out‐of‐sample predictive power, we highlight the additional role of cross‐sectional skewness and cross‐sectional kurtosis. Applying a principal component approach, we show that cross‐sectional higher moments add statistically and economically significant to the predictive quality of cross‐sectional volatility by stabilizing its predictive performance and yielding a positive trend in in‐sample and out‐of‐sample predictive quality for the equity premium. Additionally, we show that cross‐sectional skewness and cross‐sectional kurtosis span the predictive power of cross‐sectional volatility for disaggregated returns with respect to size and value.

Suggested Citation

  • Sebastian Stöckl & Lars Kaiser, 2021. "Higher moments matter! Cross‐sectional (higher) moments and the predictability of stock returns," Review of Financial Economics, John Wiley & Sons, vol. 39(4), pages 455-481, October.
    • Handle: RePEc:wly:revfec:v:39:y:2021:i:4:p:455-481
    DOI: 10.1002/rfe.1121
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    as
    1. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    2. Xiaoquan Jiang, 2010. "Return dispersion and expected returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(2), pages 107-135, June.
    3. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    4. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
    5. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
    6. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    7. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    8. Kent D. Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 2001. "Overconfidence, Arbitrage, and Equilibrium Asset Pricing," Journal of Finance, American Finance Association, vol. 56(3), pages 921-965, June.
    9. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    10. Pollet, Joshua M. & Wilson, Mungo, 2010. "Average correlation and stock market returns," Journal of Financial Economics, Elsevier, vol. 96(3), pages 364-380, June.
    11. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    12. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    13. Brian H. Boyer & Keith Vorkink, 2014. "Stock Options as Lotteries," Journal of Finance, American Finance Association, vol. 69(4), pages 1485-1527, August.
    14. Lisa Borland, 2012. "Statistical signatures in times of panic: markets as a self-organizing system," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1367-1379, October.
    15. Geert Bekaert & Campbell R. Harvey, 2000. "Foreign Speculators and Emerging Equity Markets," Journal of Finance, American Finance Association, vol. 55(2), pages 565-613, April.
    16. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    17. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    18. Guo, Hui & Kassa, Haimanot & Ferguson, Michael F., 2014. "On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(1), pages 271-296, February.
    19. 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.
    20. Stivers, Christopher T., 2003. "Firm-level return dispersion and the future volatility of aggregate stock market returns," Journal of Financial Markets, Elsevier, vol. 6(3), pages 389-411, May.
    21. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short‐Run and Long‐Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    22. Harrison Hong & José Scheinkman & Wei Xiong, 2006. "Asset Float and Speculative Bubbles," Journal of Finance, American Finance Association, vol. 61(3), pages 1073-1117, June.
    23. Angelidis, Timotheos & Sakkas, Athanasios & Tessaromatis, Nikolaos, 2015. "Stock market dispersion, the business cycle and expected factor returns," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 265-279.
    24. Riccardo Colacito & Eric Ghysels & Jinghan Meng & Wasin Siwasarit, 2016. "Skewness in Expected Macro Fundamentals and the Predictability of Equity Returns: Evidence and Theory," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2069-2109.
    25. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    26. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
    27. Xing, Yuhang & Zhang, Xiaoyan & Zhao, Rui, 2010. "What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(3), pages 641-662, June.
    28. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    29. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    30. Loungani, Prakash & Rush, Mark & Tave, William, 1990. "Stock market dispersion and unemployment," Journal of Monetary Economics, Elsevier, vol. 25(3), pages 367-388, June.
    31. Robert Connolly & Chris Stivers, 2003. "Momentum and Reversals in Equity‐Index Returns During Periods of Abnormal Turnover and Return Dispersion," Journal of Finance, American Finance Association, vol. 58(4), pages 1521-1556, August.
    32. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    33. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    34. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    35. Jinpeng Ma & Yuming Wang, 2015. "Technical Analysis, Business Cycle, and Stock Market Returns," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 5(2), pages 1-3.
    36. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    37. Eric Jondeau & Xuewu Wang & Zhipeng Yan & Qunzi Zhang, 2020. "Skewness and index futures return," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1648-1664, November.
    38. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    39. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    40. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    41. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    42. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
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    1. Ian Dew-Becker, 2024. "Real-time forward-looking skewness over the business cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 54, October.

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