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

Rubbaniyc, 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.

Journal

Finance Research Letters

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Finance Research Letters

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1544-6131

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Elsevier

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DOI

10.1016/j.frl.2021.102585