Empirical Likelihood Estimators for Stochastic Discount Factors

37 Pages Posted: 6 Mar 2008

See all articles by Caio Almeida

Caio Almeida

Princeton University

René Garcia

Université de Montréal - CIREQ - Département de sciences économiques; University of Montreal

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

Almeida, Caio and Garcia, René, Empirical Likelihood Estimators for Stochastic Discount Factors (March 4, 2008). EFA 2008 Athens Meetings Paper, Available at SSRN: https://ssrn.com/abstract=1102396 or http://dx.doi.org/10.2139/ssrn.1102396

Caio Almeida

Princeton University ( email )

26 Prospect Avenue
Princeton, NJ 08540
United States

René Garcia (Contact Author)

Université de Montréal - CIREQ - Département de sciences économiques ( email )

C.P. 6128, succursale Centre-Ville
3150, rue Jean-Brillant, bureau C-6027
Montreal, Quebec H3C 3J7
514-985-4014 (Phone)

University of Montreal ( email )

United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics