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Review of Finance Vol. 28 No. 1 2024

Do Anomalies Really Predict Market Returns? New Data and New Evidence

Nusret Cakici1; Christian Fieberg2,3,4; Daniel Metko5; Adam Zaremba6,7,8

1 Gabelli School of Business, Fordham University , New York, NY, · 2 School of International Business, City University of Applied Sciences , Bremen, · 3 Department of Economics and Management, University of Luxembourg , Luxembourg, · 4 Department of Finance, Concordia University , Montreal, · 5 Faculty of Business Studies and Economics, University of Bremen , Bremen, · 6 Montpellier Business School , Montpellier, · 7 Department of Investment and Financial Markets, Institute of Finance, Poznan University of Economics and Business , Poznań, · 8 Department of Finance and Tax, Faculty of Commerce, University of Cape Town ,

open access

Abstract

Using new data from US and global markets, we revisit market risk premium predictability by equity anomalies. We apply a repertoire of machine-learning methods to forty-two countries to reach a simple conclusion: anomalies, as such, cannot predict aggregate market returns. Any ostensible evidence from the USA lacks external validity in two ways: it cannot be extended internationally and does not hold for alternative anomaly sets—regardless of the selection and design of factor strategies. The predictability—if any—originates from a handful of specific anomalies and depends heavily on seemingly minor methodological choices. Overall, our results challenge the view that anomalies as a group contain helpful information for forecasting market risk premia.

DOI
10.1093/rof/rfad025
Volume
28
Issue
1
Pages
1-44
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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