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How active is your (nominally) actively managed quantitative fund?
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We study the Active Share (AS) of quantitative actively managed US equity funds (quants). Our results suggest that closet indexing is a common practice among these funds, with 50 % of the assets in quants managed by closet indexers by the end of 2019. This fraction significantly exceeds that observed among human–managed funds (non–quants). Our analysis indicates that AS is associated with lower performance for quants, in contrast to the positive relationship observed for non–quants. We incorporate Tracking Error (TE) alongside AS to further categorize funds based on their level of active management. We find that, after fees, quants tend to underperform their benchmarks across all categories. This result is particularly pronounced among stock pickers, with quants notably trailing non–quants, and for factor bets, which emerge as the poorest performing category. Our findings also challenge the common belief that quants charge lower fees. Although this is generally true for strategies characterized by low AS, it does not hold for those with high AS. Overall, our work documents the prevalence of closet indexing among quants and suggests that significant progress is needed before algorithms can effectively substitute human expertise in strategies that require extensive discretionary decision–making.
Descrição
Publisher Copyright: © 2025 The Authors Funding Information: We thank Miguel Ferreira, Helena Isidro, Aneel Keswani, Mara Madaleno, Pedro Pires, Florinda Silva, and Sevgi Tuzcu for comments. We also thank Samuel Vigne (Editor) and an anonymous referee for their constructive comments. Financial support from Fundação para a Ciência e Tecnologia - Grant UIDB/00315/2020 (DOI: 10.54499/UIDB/00315/2020) - is greatly acknowledged. This work used infrastructure and resources funded by Fundação para a Ciência e a Tecnologia (UID/ECO/00124/2013, UID/ECO/00124/2019 and Social Sciences DataLab, Project 22209), POR Lisboa (LISBOA-01-0145-FEDER-007722 and Social Sciences DataLab, Project 22209) and POR Norte (Social Sciences DataLab, Project 22209).
Palavras-chave
Active share Fees Mutual fund industry Performance Portfolio selection Quantitative analysis Finance Economics and Econometrics