A Bayesian approach to diagnosis of asset pricing models

A large literature has arisen which exploits a particular portfolio on the mean-variance frontier, determining a minimum variance bound on the set of stochastic discount factors (state price to probability ratios). This paper proposes a new variational characterization of the closely related set of state price densities, based on minimization of the Kullback-Leibler Information Criterion. In contrast to the variance bound, the resulting information bound automatically satisfies an important positivity constraint. Furthermore, the information bound is determined by a portfolio which maximizes expected CARA utility. Several interpretations of the information bound are given, and empirical uses of it are illustrated.