Title

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

Document Type

Article

Source of Publication

Finance Research Letters

Publication Date

11-1-2021

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.

ISSN

1544-6123

Publisher

Elsevier

Disciplines

Business

Keywords

Cryptocurrencies, Herding behavior, Happiness index, Investors’ mood, Quantile-on-quantile regression

Indexed in Scopus

no

Open Access

no

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