Assessing Asset Pricing Models Using Revealed Preference

Abstract

We propose a new method of testing asset pricing models that relies on using quantities rather than simply prices or returns. We use the capital flows into and out of mutual funds to infer which risk model investors use. We derive a simple test statistic that allows us to infer, from a set of candidate models, the model that is closest to the model that investors use in making their capital allocation decisions. Using our method, we assess the performance of the most commonly used asset pricing models in the literature.