Unmapped Holdings and the Performance Measurement of U.S. Equity Mutual Funds

Abstract

This paper investigates a dataset that provides information about assets held by U.S. equity mutual funds, but are not U.S. equities (`unmapped holdings'). I show the widespread presence of these assets and investigate how they are used within mutual fund portfolios. I find that their effects are statistically significant upon both portfolio risk and return. They can either hedge or complement mapped asset returns. I show that predictability of mutual fund returns are reduced when unmapped holdings returns are controlled. Since unmapped holdings returns are not observable, I define an econometric technique that in chapter two that can control for their effect. This technique uses an average return (an `endogenous benchmark') to control for common but immeasurable or unobservable characteristics in a group of funds. I find that an `endogenous benchmark' alone produces estimates nearly as good as those using common risk factor regression models. By combining an endoge- nous bechmark with other risk factors in regression models, I find that estimates are improved.