What Should Investors Care About? Mutual Fund Ratings by Analysts vs. Machine Learning Technique

We examine two forward-looking mutual fund ratings: the analyst rating produced by human analysts and the quantitative rating generated by a machine learning technique. The analyst rating identifies outperforming funds, while the quantitative rating does not—this difference derives mostly from the selection of analyst coverage. Moreover, the tone of the analyst report contains incremental soft information predicting fund performance. Finally, retail investors do not follow analyst recommendations; instead, they chase the quantitative rating. Our results highlight the importance of mutual fund analysts in information production and imply a capital misallocation problem in mutual fund investment.

Keywords: Analyst Rating, Quantitative Rating, Mutual Funds, Information Provision, Fund Flows, Machine Learning

JEL Classification: G11, G23

Suggested Citation: Suggested Citation

Cheng, Si and Lu, Ruichang and Zhang, Xiaojun, What Should Investors Care About? Mutual Fund Ratings by Analysts vs. Machine Learning Technique (March 7, 2022). ADB-IGF Special Working Paper Series “Fintech to Enable Development, Investment, Financial Inclusion, and Sustainability”, Available at SSRN: https://ssrn.com/abstract=3702749 or http://dx.doi.org/10.2139/ssrn.3702749