We develop a new family of estimators of the covariance matrix that relies solely on forwardlooking information. It uses only current prices of plain-vanilla options. In an out-of-sample study we show that a minimum-variance strategy based on these fully-implied estimators outperforms several...

In this paper we develop the first estimator of the covariance matrix that relies solely on forward-looking information. This estimator only uses price information from a cross-section of plain-vanilla options. In an out-of-sample study for US blue-chip stocks we show that a minimum-variance...

Option-implied moments, like implied volatility, contain useful information about an underlying asset's return distribution, but are derived under the risk-neutral probability measure. This paper shows how to convert risk-neutral moments into the corresponding physical ones. The main theoretical...

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...