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Investors’ mood and herd investing: A quantile-on-quantile regression explanation from crypto market

Author

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  • Rubbaniy, Ghulame
  • Tee, Kienpin
  • Iren, Perihan
  • Abdennadher, Sonia

Abstract

This study uses daily data of 382 cryptocurrencies and a quantile-on-quantile regression (QQR) framework developed by Sim and Zhou (2015), to establish a link between herding behavior and investors’ mood and provide support for mood-as-information hypothesis in the crypto market. The results of QQR analysis reveal that the effect of investors’ mood on herd investing behavior is asymmetric and regime specific with a (weaker)higher (anti)herding tendency towards sad(happy) quantiles of investors’ mood. The results provide support to the portfolio managers by documenting that investors’ mood can be used as a signal to monitor the possible speculative activities in crypto market.

Suggested Citation

  • Rubbaniy, Ghulame & Tee, Kienpin & Iren, Perihan & Abdennadher, Sonia, 2022. "Investors’ mood and herd investing: A quantile-on-quantile regression explanation from crypto market," Finance Research Letters, Elsevier, vol. 47(PA).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321005353
    DOI: 10.1016/j.frl.2021.102585
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    More about this item

    Keywords

    Cryptocurrencies; Herding behavior; Happiness index; Investors’ mood; Quantile-on-quantile regression;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • F3 - International Economics - - International Finance

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