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Unintentional herd behavior via the Google search volume index in international equity markets

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  • Wanidwaranan, Phasin
  • Padungsaksawasdi, Chaiyuth

Abstract

We find that retail investor attention measured by the Google Search Volume Index helps promote herd behavior in 21 international equity markets. The proposed methodology with only one dummy variable in the herd detection model is more appropriate than prior models which include multiple dummy variables, yielding better interpretation, reliability, and validation. As the Google searches are informative and free, investors utilize the information and unknowingly make similar trading patterns, supporting unintentional herd behavior. Interestingly, the effect of retail investor attention seems to disappear in downward markets. We attribute this finding to the ostrich effect, in which investors are less attentive during downward markets because of their psychological discomfort. The robustness of our results is consistent with the main findings.

Suggested Citation

  • Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2022. "Unintentional herd behavior via the Google search volume index in international equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:intfin:v:77:y:2022:i:c:s1042443121002067
    DOI: 10.1016/j.intfin.2021.101503
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    Cited by:

    1. Ozdamar, Melisa & Sensoy, Ahmet & Akdeniz, Levent, 2022. "Retail vs institutional investor attention in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    2. Shahid Raza & Sun Baiqing & Pwint Kay-Khine & Muhammad Ali Kemal, 2023. "Uncovering the Effect of News Signals on Daily Stock Market Performance: An Econometric Analysis," IJFS, MDPI, vol. 11(3), pages 1-25, August.
    3. Shifen Zhou & Xiaojun Liu, 2022. "Internet postings and investor herd behavior: evidence from China’s open-end fund market," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    4. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    5. Huisheng Wang & H. Vicky Zhao, 2024. "Optimal Investment with Herd Behaviour Using Rational Decision Decomposition," Papers 2401.07183, arXiv.org, revised Jul 2024.
    6. Lu, Shuai & Li, Shouwei, 2023. "Is institutional herding efficient? Evidence from an investment efficiency and informational network perspective," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    7. Shi, Guiqiang & Shen, Dehua & Zhu, Zhaobo, 2024. "Herding towards carbon neutrality: The role of investor attention," International Review of Financial Analysis, Elsevier, vol. 91(C).

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    More about this item

    Keywords

    Investor attention; Herd behavior; Google Search Volume Index; Behavioral finance; Ostrich effect;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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