We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the...

This paper proposes a theoretical analysis on the impacts of using a suboptimal information set on the three main components used in asset pricing, namely the risk physical and neutral measures and the relative pricing kernel.The analysis is carried out by means of a portfolio optimization...