The literature on accounting anomalies and fundamental analysis provides important insights into the behavior of stock prices and the relation between accounting numbers and firm value. My review discusses five key topics from this literature: (1) discriminating between risk and mispricing explanations for return anomalies; (2) estimating the implied cost of capital; (3) inferring investors’ perceptions of the earnings process; (4) understanding the importance of trading costs and firm size; and (5) improving the construction of characteristic-based trading strategies. My discussion highlights important challenges facing the literature and offers suggestions for improving empirical tests.

It has become standard practice in the cross-sectional asset pricing literature to evaluate models based on how well they explain average returns on size-B/M portfolios, something many models seem to do remarkably well. In this paper, we review and critique the empirical methods used in the literature. We argue that asset pricing tests are often highly misleading, in the sense that apparently strong explanatory power (high cross-sectional R2s and small pricing errors) can provide quite weak support for a model. We offer a number of suggestions for improving empirical tests and evidence that several proposed models do not work as well as originally advertised.