Assistant Professor of Finance
Huaizhi Chen is an Assistant Professor of Finance at the University of Notre Dame. Professor Chen earned his PhD in Finance at the London School of Economics and spent two years at Harvard Business School as a Post-Doc Fellow with the Behavioral Finance and Financial Stability Initiative. Professor Chen's research focuses on investments and assets pricing and has been published in the Review of Financial Studies and the Journal of Financial Economics. He teaches security analysis at the University of Notre Dame.
“Don’t Take Their Word For It: The Misclassification of Bond Mutual Funds,” Working Paper 2019.
We provide evidence that mutual fund managers misclassify their holdings, and that these misclassifications have a real and significant impact on investor capital flows. In particular, we provide the first systematic study of bond funds’ reported asset profiles to Morningstar against their actual portfolios. Many funds report more investment grade assets than are actually held in their portfolios, making these funds appear significantly less risky. This results in pervasive misclassifications across the universe of US fixed income mutual funds by Morningstar, who relies on these reported holdings. The problem is widespread- resulting in about 30% of funds being misclassified with safer profiles, when compared against their actual, publicly reported holdings. “Misclassified funds” – i.e., those that hold risky bonds, but claim to hold safer bonds– outperform the actual low-risk funds in their peer groups. “Misclassified funds” therefore receive higher Morningstar Ratings (significantly more Morningstar Stars) and higher investor flows due to this perceived outperformance. However, when we correctly classify them based on their actual risk, these funds are mediocre performers. Misreporting is stronger following several quarters of large negative returns, and it is strong at the fund family level. We report those families that have the highest percentage of misreported funds in the sample.