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...

We propose a long-run risk model with stochastic volatility, a time-varying mean reversion level of volatility, and jumps in the state variables. The special feature of our model is that the jump intensity is not affine in the conditional variance but driven by a separate process. We show that...

We provide the first comprehensive analysis of option information for pricing the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that certain option measures have significant...

Conventional financial theory considers ex-ante that risk, generally measured by the volatility, has to be appropriately rewarded by expected returns. In modern financial markets, there are countless quantitative and systematic strategies which may test and eventually lead to excess returns when...

When analyzing options returns, most papers tend to focus on the expected and realized return from strategies where the investors are long on those financial instruments. We conduct a test searching for excess returns on passive options investment strategies resorting to a four factor model,...