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

Ghulame Rubbaniy, Kienpin Tee, Perihan Iren and Sonia Abdennadher

Finance Research Letters, 2022, vol. 47, issue PA

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.

Keywords: Cryptocurrencies; Herding behavior; Happiness index; Investors’ mood; Quantile-on-quantile regression (search for similar items in EconPapers)
JEL-codes: F3 G1 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612321005353
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321005353

DOI: 10.1016/j.frl.2021.102585

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().