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Risk-neutral skewness and stock market returns: A time-series analysis

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  • Li, Xiaowei
  • Wu, Zhengyu
  • Zhang, Hao
  • Zhang, Lu

Abstract

This paper investigates whether the change of average risk-neutral skewness (RNS), which is the average of monthly risk-neutral skewness across firms, can predict subsequent aggregate stock returns. We find that average RNS positively and significantly predicts future aggregate stock returns, consistent with the firm-level evidence. Our findings are robust after controlling for other well-documented financial and economic stock return predictors. Moreover, we document that the robustness of predictability still holds in out-of-sample settings. Finally, we show that the forecasting ability of average RNS stems from its better performances during the economic recession rather than economic expansion and its pronounced predictability among stocks that are more speculative and difficult to arbitrage.

Suggested Citation

  • Li, Xiaowei & Wu, Zhengyu & Zhang, Hao & Zhang, Lu, 2024. "Risk-neutral skewness and stock market returns: A time-series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:ecofin:v:70:y:2024:i:c:s1062940823001638
    DOI: 10.1016/j.najef.2023.102040
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    More about this item

    Keywords

    Risk-neutral skewness; Return predictability; Out-of-sample prediction; Arbitrage constraints;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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