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Do machines beat humans? Evidence from mutual fund performance persistence

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  • Miguel, António F.
  • Chen, Yihao

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.

Suggested Citation

  • Miguel, António F. & Chen, Yihao, 2021. "Do machines beat humans? Evidence from mutual fund performance persistence," International Review of Financial Analysis, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:finana:v:78:y:2021:i:c:s1057521921002398
    DOI: 10.1016/j.irfa.2021.101913
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    More about this item

    Keywords

    Quantitative analysis; Mutual fund persistence; Management skill; Mutual fund industry;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G40 - Financial Economics - - Behavioral Finance - - - General

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