Analyst Rankings and Forecast Informativeness

Abstract

Does competition for a higher reputational ranking induce analysts to reveal more information? Two analysts make simultaneous forecasts about a company's future value to achieve a higher reputation relative to their peers, and are paid a tournament-style compensation. I show that the effect of reputational rankings on the information content of analysts' forecasts depends on the convexity of their payoffs and the correlation between their private signals. Competition diminishes forecast informativeness under a convex payoff structure when their signals are positively correlated and the market uncertainty is high. Under a convex payoff, analysts expecting a positive signal correlation tend to differentiate from each other by forecasting against their own signals, revealing less information in equilibrium. For a concave payoff, competition improves forecast informativeness. Forecasts by more reputable analysts may not be more informative under a convex payoff structure. These results have important implications for Regulation Fair Disclosure.