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Herding and Google search queries in the Brazilian stock market

Jeferson Carvalho (Department of Finance, Unigranrio, Rio de Janeiro, Brazil)
Paulo Vitor Jordão da Gama Silva (Department of Finance, Unigranrio, Rio de Janeiro, Brazil)
Marcelo Cabus Klotzle (Department of Finance, Pontificia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil)

Review of Behavioral Finance

ISSN: 1940-5979

Article publication date: 7 September 2023

Issue publication date: 5 March 2024

85

Abstract

Purpose

This study investigates the presence of herding in the Brazilian stock market between 2012 and 2020 and associates it with the volume of searches on the Google platform.

Design/methodology/approach

Following methodologies are used to investigate the presence of herding: the Cross-Sectional Standard Deviation of Returns (CSSD), the Cross-Sectional Absolute Deviation (CSAD) and the Cross-Sectional Deviation of Asset Betas to the Market.

Findings

Most of the models detected herding. In addition, there was a causal relationship between peaks in Google search volumes and the incidence of herding across the whole period, especially in 2015 and 2019.

Originality/value

This study suggests that confirmation bias influences investors' decisions to buy or sell assets.

Keywords

Acknowledgements

This work was carried out with the support of Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brazilian National Council for Scientific and Technological Development - CNPq), grant number 303693/2022-3, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (Carlos Chagas Filho Foundation for Research Support in the State of Rio de Janeiro - FAPERJ), grant number E-26/201.015/2022 and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Coordination for the Improvement of Higher Education Personel - Brasil/ CAPES), Finance Code 001.

Citation

Carvalho, J., Jordão da Gama Silva, P.V. and Klotzle, M.C. (2024), "Herding and Google search queries in the Brazilian stock market", Review of Behavioral Finance, Vol. 16 No. 2, pp. 341-359. https://doi.org/10.1108/RBF-12-2022-0296

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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