Hedge funds trading strategies and leverage

Abstract

We introduce learning into the hedge fund managers’ risk choice problem with imperfect information. We find that with a constant but unobserved expected return on investment, learning induces managers to take more risks and increases manager compensation. When the return is stochastic, learning increases manager compensation and induces an aggressive leverage choice when funds perform poorly or managers’ belief about fund returns is low. When funds are close to the high-water mark or the return belief is high, the learning effect reverses. This situation generates a flatter leverage ratio, which helps explain the cross-sectional dispersion of hedge fund strategies’ market betas. Finally, comparative statistics for transition intensity show that procyclicality in the hedge fund industry declines.