An Empirical Implementation of the Ross Recovery Theorem as a Prediction Device

Abstract Building on the method of Ludwig (2015) to construct robust state price density surfaces from snapshots of option prices, we develop a nonparametric estimation strategy based on the recovery theorem of Ross (2015). Using options on the S&P 500, we then investigate whether or not recovery yields predictive information beyond what can be gleaned from risk-neutral densities. Over the 13 year period from 2000 to 2012, we find that market timing strategies based on recovered moments outperform those based on risk-neutral moments.