We develop a multi-period learning model to examine the relation between analysts’ forecasting behavior and their performance. In a competitive market for banking services, the surplus and the analyst's payoff, which is determined through bargaining, are convex in her reputation. The convexity of her payoff structure and the presence of employment risk lead to a U-shaped relation between the analyst's forecast boldness and prior performance and a positive relation between forecast boldness and experience. We find support for these predictions in our empirical analysis. Significant underperformers (outperformers) face higher (lower) employment risk and are more likely to issue bolder forecasts.

We use India's unique regulatory design to test sentiment-based models of IPO initial returns. Using a sample of 362 Indian offerings from 2003 to 2014, we find that the traditional measure of IPO underpricing averages 23%. We decompose the traditional underpricing measure into two components: one related to voluntary underpricing by the underwriter and the other component related to the IPO's first-day trading activity. We find minimal levels of voluntary underpricing. However, initial returns on the first day average 14% and are primarily driven by the unmet demand of non-institutional investor groups. Overall, our results support sentiment-based models of IPO initial returns.

We demonstrate that time stamps reported in I/B/E/S for analysts’ recommendations released during trading hours are systematically delayed. Using newswire‐reported time stamps, we find 30‐minute returns of 1.83% (−2.10%) for upgrades (downgrades), but for this subset of recommendations we find corresponding returns of −0.07% (−0.09%) using I/B/E/S‐reported time stamps. We also examine the information content of recommendations relative to management guidance and earnings announcements. Our evidence suggests that analysts’ recommendations are the most important information disclosure channel examined.