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Efficient scholars: academic attention and the disappearance of anomalies

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  • Savva Shanaev
  • Binam Ghimire

Abstract

This study examines the dynamics of ten most notable stock market anomalies through 1926–2018 and assesses the joint impact of academic attention, post-publication decay, data-snooping bias, institutional trading, and time trend on their disappearance. It proposes new and simple measures of academic attention attracted by stock market anomalies using the number of articles published on the relevant topic available via Google Scholar or respective citation counts. The study finds that academic attention is the most dominant factor explaining the diminishing abnormal returns of anomaly-exploiting strategies. The approach developed by this study can also be useful in determining whether a stock return regularity is a behavioural anomaly or a systematic risk factor.

Suggested Citation

  • Savva Shanaev & Binam Ghimire, 2021. "Efficient scholars: academic attention and the disappearance of anomalies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(3), pages 278-304, February.
    • Handle: RePEc:taf:eurjfi:v:27:y:2021:i:3:p:278-304
    DOI: 10.1080/1351847X.2020.1812684
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    Cited by:

    1. Reveley Callum & Shanaev Savva & Bin Yu & Panta Humnath & Ghimire Binam, 2023. "Analyst herding—whether, why, and when? Two new tests for herding detection in target forecast prices," Economics and Business Review, Sciendo, vol. 9(4), pages 25-55, December.
    2. Hutchinson, Mark C. & Kyziropoulos, Panagiotis E. & O’Brien, John & O’Reilly, Philip & Sharma, Tripti, 2022. "Technical trading rule profitability in currencies: It’s all about momentum," Research in International Business and Finance, Elsevier, vol. 63(C).
    3. Shanaev, Savva & Ghimire, Binam, 2022. "A generalised seasonality test and applications for cryptocurrency and stock market seasonality," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 172-185.
    4. Shanaev, Savva & Shuraeva, Arina & Fedorova, Svetlana, 2022. "The Groundhog Day stock market anomaly," Finance Research Letters, Elsevier, vol. 47(PA).

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