We adopt a family of nonparametric Cressie-Read estimators to price options based on relative pricing using the underlying asset returns. We use option models with stochastic volatility and jumps to investigate the ability of each member in this family to price options with different moneynesses...

We characterize a set of risk-neutral measures associated with a comprehensive class of risk averse investors. From this set, we show how to construct option price bounds and recover the implied gamma: a parameter uniquely identifying the marginal investor pricing a given option. Empirically, we...

We show that net demand in the S&P 500 option market is fundamental to explain empirical puzzles related to the pricing kernel. When public investors (non-market makers) are exposed to variance risk by net-selling out-of-the-money (OTM) options, the pricing kernel is U-shaped, expected option...

We develop a new approach to evaluate asset pricing models (APMs) based on Minimum Discrepancy (MD) projections that generalize the Hansen-Jagannathan (HJ, 1997) distance to account for an arbitrary number of moments of asset returns. The Minimum Discrepancy projections correct APMs to become...

We develop a new approach to identify model misspecifications based on Minimum Discrepancy (MD) projections that correct asset pricing models with the use of nonlinear functions of basis assets returns. These nonlinear corrections make our method more effective than the Hansen and Jagannathan...

We study the relation between a comprehensive set of firm characteristics and the entire universe of individual equity option prices. We find that 42 out of 86 characteristics are priced in the option market, in the sense that they significantly explain differences in the implied volatility...