The Ambiguous Effects of Rankings: Strategically Biased Forecasting by Advisers

We present a model of investors acquiring forecasts from a group of advisers (analysts), some of which are better informed than others. Investors may pick an adviser based on his past performance. In the literature it is typically assumed that agentsã rewards depend solely on the type they are perceived to be, which leads to typical herding results. In contrast here, advisersã rewards not only depend on their own reputation but also on the number of advisers with a similar reputation. There exist two interesting types of equilibria: in the first type it is optimal for investors to ignore advisersã past performance, even though advisers make predictions according to their best knowledge. In a second type investors do use past performance to select advisers. However this induces advisers to predict strategically, i.e. some advisers knowingly make wrong predictions.