Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...

This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are...

This paper studies the factor structure of the cross-section of delta-hedged equity option returns. We find that a four-factor model explains the cross-section and time-series of equity option returns. Out of the four factors, three are characteristic based factors from the long-short option...

This paper studies the effects of default risk on equity option returns. We show that there is a cross-sectional and a time-series relation between default risk and option returns. In the cross-section, expected delta-hedged equity option returns have a negative relation with default risk...

The Black-Scholes framework implies a constant volatility across term and strike, and a lognormal distribution for underlying asset prices. However, it is known that empirical data violates this assumption. In this report we describe, motivate and apply a model-independent,...

This paper evaluates the underperformance of individual equity options relative to their replicating portfolios. Considering a high-dimensional set of variables, we use a machine learning approach to identify the characteristics of options and their underlying stocks that provide incremental...

We propose a non-parametric method based on a model-free formula to evaluate the tails of a risk-neutral distribution using the full cross-section of option prices at a fixed horizon. The method leads to the joint estimation of risk-neutral tail probabilities and tail expectations beyond the...