Scientific journal paper Q1
Do machines beat humans? Evidence from mutual fund performance persistence
António Miguel (Miguel, A. F.); Yihao Chen (Chen, Y.);
Journal Title
International Review of Financial Analysis
Year (definitive publication)
2021
Language
English
Country
United States of America
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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.
Acknowledgements
We thank Miguel Ferreira, Helena Isidro, Aneel Keswani, Pedro Pires, and Sevgi Tuzcu for comments. We also thank Brian Lucey (Editor), and two anonymous referees for their constructive comments. Financial support from Fundação para a Ciência e Tecnologia
Keywords
Quantitative analysis,Mutual fund persistence,Management skill,Mutual fund industry
  • Economics and Business - Social Sciences
Funding Records
Funding Reference Funding Entity
PTDC/IIM–FIN/1500/2014 Fundação para a Ciência e a Tecnologia
UIDB/00315/2020 Fundação para a Ciência e a Tecnologia

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