Accounting Data, Market Values, and the Cross Section of Expected Returns World

by Charles C.Y. Wang

Overview — Over the past 30 years, the central question in asset pricing is understanding what drives the variation in expected returns. Despite its importance, empirical research in this area has remained problematic because the key variable, expected returns, is not observable. This paper promotes an accounting-fundamentals-based approach to estimating expected returns. It contributes to the stream of empirical studies devoted to developing the estimation of, and understanding the behavior of, expected returns. It also provides a practical tool that can be used to analyze investment choices in international equity contexts.

Author Abstract

Under fairly general assumptions, expected stock returns are a linear combination of two firm fundamentals-book-to-market ratio and return on equity. This parsimonious relation is pervasive, producing expected return proxies (ERP) that predict the cross section of out-of-sample returns in 26 of 29 international equity markets. The average slope coefficient on the ERP is a highly significant 1.05. In contrast, factor-model-based proxies fail to exhibit predictive power worldwide. Integrating the model with a dynamic information structure, we show analytically, and verify empirically, that the importance of return on equity in forecasting future stock returns depends on the quality of the accounting information. This extension also reconciles our model with alternative characteristic-based forecasters. These findings suggest that a tractable accounting-based valuation model provides a unifying framework for obtaining reliable proxies of expected returns worldwide.