Machine-learning the skill of mutual fund managers

Ron Kaniel; Zihan Lin; Markus Pelger; Stijn Van Nieuwerburgh

doi:10.1016/j.jfineco.2023.07.004

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Journal of Financial Economics Vol. 150 No. 1 2023

Machine-learning the skill of mutual fund managers

Ron Kaniel^1,2,3; Zihan Lin⁴; Markus Pelger⁴; Stijn Van Nieuwerburgh

¹ Reichman University · ² Fudan University · ³ University of Rochester · ⁴ Stanford University

open access

Abstract

We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, before and after fees. The outperformance persists for more than three years. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance, while characteristics of the stocks that funds hold are not predictive. Returns of predictive long-short portfolios are higher following a period of high sentiment. Our estimation with neural networks enables us to uncover novel and substantial interaction effects between sentiment and both fund flow and fund momentum.

DOI: 10.1016/j.jfineco.2023.07.004
Volume: 150
Issue: 1
Pages: 94-138
Language: en
Sources: bibtex:phds-export.bib openalex crossref

Machine-learning the skill of mutual fund managers

Abstract

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