We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian model averaging SDF outperforms reduced-form benchmark models in-sample and out-of-sample in pricing option return anomalies and portfolios. We document that the SDF is dense in characteristics with the implied-realized volatility spread, option return momentum, and jump risk emerging as the most likely included factors. The option SDF exhibits a distinct business cycle pattern and aligns more closely with its counterpart in the stock market than in the bond market.

This article examines whether investors receive compensation for holding crash-sensitive stocks. We capture the crash sensitivity of stocks by their lower-tail dependence (LTD) with the market based on copulas. We find that stocks with strong LTD have higher average future returns than stocks with weak LTD. This effect cannot be explained by traditional risk factors and is different from the impact of beta, downside beta, coskewness, cokurtosis, and Kelly and Jiang’s (2014) tail risk beta. Hence, our findings are consistent with the notion that investors are crash-averse.