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

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.

• Journal Article Type: Article
• Acceptance Date: Nov 17, 2021
• Online Publication Date: Nov 26, 2021
• Publication Date: Jun 30, 2022
• Deposit Date: Nov 20, 2023
• Journal: Finance Research Letters
• Print ISSN: 1544-6123
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 47
• Article Number: 102585
• DOI: https://doi.org/10.1016/j.frl.2021.102585
• Public URL: https://uwe-repository.worktribe.com/output/11456533