Herding behavior in Hong Kong stock market during the COVID-19 period: a systematic detection approach

Conghua Wen, Zixi Yang and Rui Jiang

Journal of Chinese Economic and Business Studies, 2022, vol. 20, issue 2, 159-170

Abstract: The study intends to conduct a systematic mechanism for herding detection in the Hong Kong stock market. We take stocks from three market sectors as samples and investigate the existence of herding in the two periods: before and during the outbreak of COVID-19 in Hong Kong, from August 2019 to July 2020. We adopt CCK model-based OLS and quantile regression to examine herding in each observed period and employ HS model to measure the magnitude of herding during the time. The empirical results indicate the emergence of mild herding from August 2019 to January 2020, and the herding phenomenon is generally weakened between February and July 2020. Our study confirms the implication of the systematic herding detection mechanism that can improve the sensitivity of detection and capture the magnitude and variation of herding.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/14765284.2021.1948320 (text/html)
Access to full text is restricted to subscribers.

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:taf:jocebs:v:20:y:2022:i:2:p:159-170

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCEA20

DOI: 10.1080/14765284.2021.1948320

Access Statistics for this article

Journal of Chinese Economic and Business Studies is currently edited by Professor Xiaming Liu

More articles in Journal of Chinese Economic and Business Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().