Empirical Likelihood Estimators for Stochastic Discount Factors
37 Pages Posted: 6 Mar 2008
Date Written: March 4, 2008
Hansen and Jagannathan (HJ, 1991) provided bounds on the volatility of Stochastic Discount Factors (SDF) that proved extremely useful to diagnose and test asset pricing models. This nonparametric bound reflects a duality between the mean-standard deviation frontier for SDFs and the mean-variance frontier for portfolios of asset returns. We extend this fundamental contribution by proposing information bounds that reflect a duality with finding the optimal portfolio of asset returns with a general HARA utility function. The maximum utility portfolio implies SDF estimators that are based on implied probabilities associated with the class of Generalized Empirical Likelihood estimators. We analyze the implications of these information bounds for the pricing of size portfolios and the performance evaluation of hedge funds.
Keywords: Stochastic Discount Factor, Information-Theoretic Bounds,Generalized Minimum Contrast Estimators, Implicit Utility Maximizing Weights
JEL Classification: C1, C5, G1
Suggested Citation: Suggested Citation