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When Anomalies Are Publicized Broadly, Do Institutions Trade Accordingly?

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  • Paul Calluzzo

    (Smith School of Business, Queen’s University, Kingston, Ontario K7L 3N6, Canada)

  • Fabio Moneta

    (Smith School of Business, Queen’s University, Kingston, Ontario K7L 3N6, Canada)

  • Selim Topaloglu

    (Smith School of Business, Queen’s University, Kingston, Ontario K7L 3N6, Canada)

Abstract

This paper studies whether institutional investors trade on 14 well documented stock market anomalies. We show that there is an increase in anomaly-based trading when information about the anomalies is readily available through academic publications and the release of necessary accounting data. This finding is more pronounced among hedge funds and institutions with high turnover, that is, the subset of investors who likely have the abilities and incentives to act on the anomalies. We directly relate the increase in trading to the observed decay in post-publication anomaly returns. Our results support the role of institutional investors in the arbitrage process and in improving market efficiency.

Suggested Citation

  • Paul Calluzzo & Fabio Moneta & Selim Topaloglu, 2019. "When Anomalies Are Publicized Broadly, Do Institutions Trade Accordingly?," Management Science, INFORMS, vol. 65(10), pages 4555-4574, October.
    • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:10:p:4555-4574
    DOI: 10.1287/mnsc.2018.3066
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    5. Bartram, Söhnke & Djuranovik, Leslie & Garratt, Anthony, 2021. "Currency Anomalies," CEPR Discussion Papers 15653, C.E.P.R. Discussion Papers.
    6. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    7. Jacobs, Heiko & Müller, Sebastian, 2020. "Anomalies across the globe: Once public, no longer existent?," Journal of Financial Economics, Elsevier, vol. 135(1), pages 213-230.
    8. Andrew Y. Chen & Alejandro Lopez-Lira & Tom Zimmermann, 2022. "Does Peer-Reviewed Research Help Predict Stock Returns?," Papers 2212.10317, arXiv.org, revised Jun 2024.
    9. Charoenwong, Ben & Nettayanun, Sampan & Saengchote, Kanis, 2021. "Digesting anomalies: A q-factor approach for the Thai market," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
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    11. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.
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    16. Ilan Cooper & Liang Ma & Paulo Maio, 2022. "What Does the Cross‐Section Tell About Itself? Explaining Equity Risk Premia with Stock Return Moments," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(1), pages 73-118, February.
    17. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    18. Chen, Haosi (Chelsea) & Puckett, Andy, 2023. "Do Hedge Funds Value Sell-Side Analysts Differently?," Journal of Banking & Finance, Elsevier, vol. 154(C).
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    21. Martineau, Charles, 2021. "Rest in Peace Post-Earnings Announcement Drift," SocArXiv z7k3p, Center for Open Science.

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