Learning from Prospectuses

Abstract

We analyze fund managers' incentives to disclose qualitative information about their strategies, and investors’ ability to learn from these disclosures. We propose a mechanism whereby investors make fewer errors in distinguishing active returns from passive factor exposures when they have access to more detailed strategy descriptions. In a formal model, we show that investor attribution errors are, on balance, more costly for managers with more specialized strategies, leading them to write more detailed descriptions. In the data, we find evidence for this prediction and support for the model’s core learning mechanism, as well as new insights into the flow-performance relationship.

Keywords: mutual funds, fund prospectus, information disclosure, fund benchmarks, machine learning

JEL Classification: G23, G11, D83