Differential Information and Security Market Equilibrium

TLDR

The paper proposes a simple equilibrium asset pricing model that incorporates differential information across securities and provides theoretical support for empirically testing three proxies of relative information: listing period, number of return observations, and analyst opinion divergence. The authors develop a straightforward equilibrium asset pricing framework that models how varying amounts of information used to infer return parameters affect asset pricing. They find that estimation risk alters market equilibrium, causing securities with limited information to exhibit higher systematic risk, and that the model remains robust when key assumptions are relaxed.

Abstract

We propose a simple model of equilibrium asset pricing in which there are differences in the amounts of information available for developing inferences about the returns parameters of alternative securities. In contrast with earlier work, we show that parameter uncertainty, or estimation risk, can have an effect upon market equilibrium. Under reasonable conditions, securities for which there is relatively little information are shown to have relatively higher systematic risk when that risk is properly measured, ceteris paribus. The initially very limited model is shown to be robust with respect to relaxation of a number of its principal assumptions. We provide theoretical support for the empirical examination of at least three proxies for relative information: period of listing, number of security returns observations available, and divergence of analyst opinion.