I examine three composite analyst forecast of earnings per share as proxies for expected earnings. The most current forecast weakly dominates the mean and median forecasts in accuracy. This is evidence that forecast dates are more relevant for determining accuracy than individual error. Consistent with previous research, I find analysts more accurate than time-series models. However prior knowledge of forecast errors from a quarterly autoregressive model predicts excess stock returns better than prior knowledge of analysts' errors. This is inconsistent with previous research, and is anomalous given analysts' greater accuracy.

Using hand-collected data on analyst locations, we study how geographic proximity affects analyst coverage decisions for U.S. firms that went public during 1996–2009, along with the impact of local coverage on firm visibility. Analysts are 80% more likely to cover local firms than non-local ones, and nearby non-underwriter analysts initiate coverage one to three weeks earlier than distant ones. Proximity matters most for smaller, less visible firms, for firms with less complex operations and for lower status analysts. Less visible firms may use local analyst coverage as a stepping-stone to increase visibility with other analysts and institutional investors.