B0831
Title: Efficient estimation of pricing kernels and market-implied densities
Authors: Jeroen Dalderop - University of Notre Dame (United States) [presenting]
Abstract: The nonparametric identification and estimation of projected pricing kernels implicit in European option prices and underlying asset returns are studied using conditional moment restrictions. The proposed series estimator avoids computing ratios of estimated risk-neutral and physical densities. Instead, efficient estimation is considered based on an efficiently weighted minimum distance criterion, which takes into account the informativeness of option prices of varying strike prices beyond observed conditioning variables. In the second step, the implied probabilities are converted into predictive densities by matching the informative part of cross-sections of option prices. Empirically, pricing kernels tend to be U-shaped in the S\&P 500 index return given high levels of the VIX and call and ATM options are more informative about their payoff than put and OTM options.
