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Predicting Market Returns Using Covariance Asymmetry Risk Premium

Author

Listed:
  • Zhenxiong Li
  • Xinfeng Ruan
  • Xingzhi Yao

Abstract

Implied covariance asymmetry is a market‐wide measure defined as the average of the absolute difference between the downside and upside pairwise co‐movements of individual stocks, estimated from options data. Its risk premium is linked to improved long‐term economic conditions and significantly forecasts excess market returns from 1 month to 2 years. This predictive power persists at horizons beyond 6 months after controlling for popular financial and economic predictors in in‐sample analyses. It also translates into superior out‐of‐sample forecasts and substantial economic gains for a mean‐variance investor, particularly over medium and long horizons.

Suggested Citation

  • Zhenxiong Li & Xinfeng Ruan & Xingzhi Yao, 2026. "Predicting Market Returns Using Covariance Asymmetry Risk Premium," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 46(2), pages 435-462, February.
  • Handle: RePEc:wly:jfutmk:v:46:y:2026:i:2:p:435-462
    DOI: 10.1002/fut.70065
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    References listed on IDEAS

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    1. Faria, Gonçalo & Kosowski, Robert & Wang, Tianyu, 2022. "The Correlation Risk Premium: International Evidence," Journal of Banking & Finance, Elsevier, vol. 136(C).
    2. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    3. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    4. Amit Goyal & Ivo Welch & Athanasse Zafirov, 2024. "A Comprehensive 2022 Look at the Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 37(11), pages 3490-3557.
    5. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    6. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    7. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    8. Bollerslev, Tim & Todorov, Viktor & Xu, Lai, 2015. "Tail risk premia and return predictability," Journal of Financial Economics, Elsevier, vol. 118(1), pages 113-134.
    9. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    10. Bruno Feunou & Ricardo Lopez Aliouchkin & Roméo Tedongap & Lai Xi, 2017. "Variance Premium, Downside Risk and Expected Stock Returns," Staff Working Papers 17-58, Bank of Canada.
    11. 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.
    12. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    13. Richard D. F. Harris & Xuguang Li & Fang Qiao, 2019. "Option‐implied betas and the cross section of stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 94-108, January.
    14. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    15. 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.
    16. 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.
    17. Bondarenko, Oleg & Bernard, Carole, 2024. "Option-Implied Dependence and Correlation Risk Premium," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 59(7), pages 3139-3189, November.
    18. Gurdip Bakshi & Nikunj Kapadia & Dilip Madan, 2003. "Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options," The Review of Financial Studies, Society for Financial Studies, vol. 16(1), pages 101-143.
    19. Zhenxiong Li & Marwan Izzeldin & Xingzhi Yao, 2020. "Return predictability of variance differences: A fractionally cointegrated approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1072-1089, July.
    20. Bingduo Yang & Wei Long & Liang Peng & Zongwu Cai, 2020. "Testing the Predictability of U.S. Housing Price Index Returns Based on an IVX-AR Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 1598-1619, December.
    21. Alexandros Kostakis & Tassos Magdalinos & Michalis P. Stamatogiannis, 2015. "Robust Econometric Inference for Stock Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 28(5), pages 1506-1553.
    22. Avramov, Doron & Wermers, Russ, 2006. "Investing in mutual funds when returns are predictable," Journal of Financial Economics, Elsevier, vol. 81(2), pages 339-377, August.
    23. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
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