Utility-Based Performance Measures for Regression Models

Abstract

We measure regression model performance (as perceived by a conservative investor betting on a complete market) via the out-of-sample expected utility for the allocation that maximizes expected utility under a most adverse modelconsistent measure. This robust allocation is optimal under the minimum generalized relative entropy (MGRE) measure. We analyze our performance measure in the (practical) case of an investor whose utility function is a member of a three-parameter logarithmic family with a wide range of possible risk aversions. Here, our performance measure is independent of the market prices, and the MGRE measure minimizes the Kullback-Leibler relative entropy.

Keywords: regression models, model performance measures, relative entropy, expected utility, horse race

JEL Classification: C10