Testing Asymmetric-Information Asset Pricing Models

Abstract

We provide evidence for the importance of information asymmetry in asset pricing by using three natural experiments. Consistent with rational expectations models with multiple assets and multiple signals, we find that prices and uninformed demand fall as asymmetry increases. These falls are larger when more investors are uninformed, turnover is larger and more variable, payoffs are more uncertain, and the lost signal is more precise. Prices fall partly because expected returns become more sensitive to liquidity risk. Our results confirm that information asymmetry is priced and imply that a primary channel that links asymmetry to prices is liquidity. (JEL G12, G14, G17, G24) Theoretical asset pricing models routinely assume that investors have heterogeneous information. The goal of this article is to establish the empirical relevance of this assumption for equilibrium asset prices and investor demands. To do so, we exploit a novel identification strategy that allows us to infer changes in the distribution of information among investors and hence to quantify the effect of information asymmetry on prices and demands. Our results suggest that information asymmetry has a substantial effect on prices and demands and affects assets through a liquidity channel. Asymmetric-information asset pricing models typically rely on a noisy rational expectations equilibrium (REE) in which prices, due to randomness in the risky asset’s supply, only partially reveal the better-informed investors’ information. Random supply might reflect the presence of “noise traders” whose demands are independent of information. Prominent examples of such models include Grossman and Stiglitz (1980), Hellwig (1980), Admati (1985), Wang (1993), and Easley and O’Hara (2004).