This paper studies the relation between stock returns and aggregate earnings surprises. An extensive literature investigates the stock market reaction to individual companies’ earnings announcements (e.g., Ball and Brown, 1968; Watts, 1978; Bernard and Thomas, 1989). At the firm level, stock prices react positively to earnings news but require several quarters to fully reflect the information in earnings. Our goal is to test whether post-earnings announcement drift extends to aggregate data, and more broadly, to understand the connection between stock returns and aggregate earnings surprises.

The motivation for our study is two-fold. First, we test for post-announcement drift in market returns as a simple ‘out-of-sample’ test of recent behavioral models. At the firm level, Fama (1998, p. 304) describes post-earnings announcement drift as an ‘anomaly above suspicion.’ Bernard and Thomas (1990), Barberis, Shleifer, and Vishny (1998), and Daniel, Hirshleifer, and Subrahmanyam (1998) all cite it as a prime example of market inefficiency, helping to motivate their behavioral theories. Our reading of the theories suggests that, although they are motivated by firm level evidence, the biases they describe should also affect aggregate stock returns. As discussed further below, we do not view our study as a strict test of the models, but our investigation is in the spirit of testing whether the theories can ‘explain the big picture’ (Fama 1998, p. 291). More generally, comparing how the stock market reacts to firm and aggregate earnings should help theorists refine models of price behavior.