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.

The returns and stock holdings of institutional investors from 1980 to 2007 provide little evidence of stock-picking skill. Institutions as a whole closely mimic the market portfolio, with pre-cost returns that have nearly perfect correlation with the value-weighted index and an insignificant CAPM alpha of 0.08% quarterly. Institutions also show little tendency to bet on any of the main characteristics known to predict stock returns, such as book-to-market, momentum, or accruals. While particular groups of institutions have modest stock-picking skill relative to the CAPM, their performance is almost entirely explained by the book-to-market and momentum effects in returns. Further, no group holds a portfolio that deviates efficiently from the market portfolio.

This article studies whether financial ratios like dividend yield can predict aggregate stock returns. Predictive regressions are subject to small-sample biases, but the correction used by prior studies can substantially understate forecasting power. I show that dividend yield predicts market returns during the period 1946–2000, as well as in various subsamples. Book-to-market and the earnings-price ratio predict returns during the shorter sample 1963–2000. The evidence remains strong despite the unusual price run-up in recent years.

This article studies momentum in stock returns, focusing on the role of industry, size, and book-to-market (B/M) factors. Size and B/M portfolios exhibit momentum as strong as that in individual stocks and industries. The size and B/M portfolios are well diversified, so momentum cannot be attributed to firm- or industry-specific returns. Further, industry, size, and B/M portfolios are negatively autocorrelated and cross-serially correlated over intermediate horizons. The evidence suggests that stocks covary “too strongly” with each other. I argue that excess covariance, not underreaction, explains momentum in the portfolios.

Higher accruals are associated with lower subsequent earnings. We show this phenomenon can be explained by the way sales, profits, and working capital respond to changes in a firm's product markets. Empirically, high accruals predict high subsequent sales growth but a long-lasting drop in both profits and profitability. Accruals also predict an increase in future competition, suggesting that accruals are correlated with abnormally high—and, in equilibrium, transitory—true profitability that attracts new entrants to the industry. Overall, the predictive power of accruals is better explained by product-market effects than by measurement error in accruals or diminishing returns from investment.

ABSTRACT This paper studies institutional investors’ incentives to be engaged shareholders. In 2017, the average institution gains an extra $129,000 in annual management fees if a stockholding increases 1% in value, considering both the direct effect on assets under management and the indirect effect on subsequent fund flows. The estimates range from $19,600 for investments in small firms to $307,600 for investments in large firms. Institutional shareholders in one firm often gain when the firm's competitors do well, by virtue of institutions’ holdings in those firms, but the impact of common ownership is modest in the most concentrated industries.

We study the stock market's reaction to aggregate earnings news. Prior research shows that, for individual firms, stock prices react positively to earnings news but require several quarters to fully reflect the information in earnings. We find a substantially different pattern in aggregate data. First, returns are unrelated to past earnings, suggesting that prices neither underreact nor overreact to aggregate earnings news. Second, aggregate returns correlate negatively with concurrent earnings; over the last 30 years, for example, stock prices increased 5.7% in quarters with negative earnings growth and only 2.1% otherwise. This finding suggests that earnings and discount rates move together over time and provides new evidence that discount-rate shocks explain a significant fraction of aggregate stock returns.

ABSTRACT This paper studies the asset‐pricing implications of parameter uncertainty. We show that, when investors must learn about expected cash flows, empirical tests can find patterns in the data that differ from those perceived by rational investors. Returns might appear predictable to an econometrician, or appear to deviate from the Capital Asset Pricing Model, but investors can neither perceive nor exploit this predictability. Returns may also appear excessively volatile even though prices react efficiently to cash‐flow news. We conclude that parameter uncertainty can be important for characterizing and testing market efficiency.

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.