 Do machines beat humans? Evidence from mutual fund performance persistenceAntónio F. Miguel and Yihao Chen International Review of Financial Analysis, 2021, vol. 78, issue C Abstract: We study the performance persistence of quantitative actively managed US equity funds. We show that the persistence of quantitative funds originates from poor performers and that there are reversals at the top of the performance scale, which is no different from the widely accepted evidence in the mutual fund literature. When testing for differences in performance persistence between quantitative and non–quantitative funds, we find no differences for poorly performing funds, but we observe significantly more reversals for quantitative funds at the top of the performance distribution. We also find that the differences in performance persistence are not explained by differences in flow–induced incentives to generate alpha, as there is no heterogeneity in investors preferences when allocating capital to these funds. Overall our results are consistent with machines having less skill than their human counterparts. Keywords: Quantitative analysis; Mutual fund persistence; Management skill; Mutual fund industry (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:78:y:2021:i:c:s1057521921002398 DOI: 10.1016/j.irfa.2021.101913 Access Statistics for this article International Review of Financial Analysis is currently edited by B.M. Lucey More articles in International Review of Financial Analysis from Elsevier |
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