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.

We document significant time-series and cross-sectional momentum in 28 equity option factors. Factor momentum is distinct from a static factor portfolio, and prominent option factor models cannot fully explain its returns. Despite high autocorrelation, factor momentum profits are mainly driven by high and persistently different mean factor returns in the case of longer formation periods. Option factor momentum fully subsumes option momentum, but not vice versa. Our findings are robust over time, across various market states, and for alternative momentum strategy constructions.