When Mutual Fund Names Misinform

Abstract

Mutual funds often inform directly about their strategy in their name. This paper studies the accuracy of mutual fund names. Constructing a fund name history data set based on SEC filings and applying unsupervised machine learning techniques, we document that a significant fraction of mutual funds features an inaccurate name, i.e. a name which is not aligned with their actual investment style. Funds that provide an inaccurate name experienced lower fund inflows before the inaccuracy, under-performed in the year before, and charged higher expenses. Strikingly, after featuring an inaccurate name, funds see a worse risk-return trade-off due to an increased idiosyncratic risk. Finally, we document that investors experience difficulties in responding to this misleading information while at the same time, they do not profit from this deviating behavior of the funds. Thus, our results highlight the importance of regulatory intervention in the name dimension.