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.
We used Chang et 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.
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.
Our results are also helpful for the policy makers in designing stricter regulations to provide safe investment environment to the investors.
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.
Kumar, A. (2021), "Empirical investigation of herding in cryptocurrency market under different market regimes", Review of Behavioral Finance, Vol. 13 No. 3, pp. 297-308. https://doi.org/10.1108/RBF-01-2020-0014
Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited