Reporting System, Investor Learning, and Stock Return Regularities

Abstract

We propose a simple framework for understanding accounting-based stock return regularities. A firm's accounting reports provide noisy information about hidden economic states that evolve according to a Markov process. In response to the accounting reports, a representative Bayesian investor forms beliefs about the underlying state and hence the value of the firm. For a population of such firms, the model provides predictions consistent with two sets of well-documented regularities: (i) the market reaction to an earnings announcement that ends a string of consecutive earnings increases and (ii) the return predictabilities based on accruals and book-tax differences. The model also yields novel cross-sectional predictions about the distinct roles of economic persistence and earnings informativeness. We confirm these predictions through empirical tests.