Empirical investigation of herding in cryptocurrency market under different market regimes
Ashish Kumar
Review of Behavioral Finance, 2020, vol. 13, issue 3, 297-308
Abstract:
Purpose - Our study focuses on analyzing the trading behaviour of the investors who invest in these currencies to review their trading patterns which may help us to understand the price formation of cryptocurrencies in this market. Design/methodology/approach - We used Changet al.(2000) measure to calculate herding that is based on cross-section absolute dispersion of stock returns (CSAD). We further analyse the nature of the same in different market regimes, that is up market, down market, high volatile market, low volatile market etc. Findings - Applying different methodologies both static and time varying, we find that herding is pronounced when the market is either passing through stress or has become highly volatile. Anti-herding is found in a less volatile market or in a bullish market. Practical implications - Our results are also helpful for the policy makers in designing stricter regulations to provide safe investment environment to the investors. Originality/value - Our study in an extension of the literature in same direction and contribute in numerous ways. As the number of digital currencies is growing day by day and we have around 2,200 digital currencies trading across the world, we increased our sample size up to 100 most traded currencies. While majority of the studies cover the period 2015–2018, our study comprises the largest sample size starting from August 2013 to April 2019. We use the static model to find herding and simultaneously try to detect herding under different market regimes: up market and down market.
Keywords: Herding; CSAD; Time varying herding; Cryptocurrency (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
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:eme:rbfpps:rbf-01-2020-0014
DOI: 10.1108/RBF-01-2020-0014
Access Statistics for this article
Review of Behavioral Finance is currently edited by Professor Gulnur Muradoglu
More articles in Review of Behavioral Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().