Flows and Performance with Optimal Money Management Contracts

Abstract

Previous literature documents that mutual funds flows increase more than linearly with realized performance. I show this convex flow-performance relationship is consistent with a dynamic contracting model in which investors learn about the fund manager s skill. My model predicts that flows become more sensitive to current performance after a history of good past performance. It also predicts that the effect of past performance on the current flow-performance relationship is weaker for managers with longer tenure. I consider an optimal incentive contract for money managers, and I provide an explanation for common compensation practices in the industry, such as convex pay-for-performance schemes and deferred compensation. In the optimal contract, flows become more sensitive to performance when the manager faces stronger incentives from the compensation contract. With learning, the manager s incentives become stronger after good performance, so that a manager exerts more effort when his assessed skill is higher. However, the relation between past performance and incentives becomes weaker over the manager s tenure. Using mutual fund data, I test the predictions of the model on the dynamic behavior of the flow-performance relationship, and I find empirical support for the theory.