We contribute to the literature on herding in the cryptocurrency market by using a unique data set of trader transactions. Using popular metrics, we find significant evidence of herding, which is primarily driven by individuals mimicking their own past trades, given the sporadic nature of information as well as the ambiguity and anonymity inherent in this market. Herding is higher during bearish periods as traders react more similarly to negative news. We find evidence of intentional herding due to informational cascades in less liquid cryptocurrencies, where significant price movements may be interpreted as valuable information. Traders with larger accounts tend to mimic their own past trades. Mature traders trade similarly due to their lower tolerance for risk and experimentation. We find herding differentials among traders that arise due to the environment governing the local financial system in which they are located. Moreover, persistence in herding is lower compared to what has been reported in other markets due to the higher degree of ambiguity of cryptocurrencies and the individuals trading them. Finally, market factors such as volatility, have a significant effect on herding. Our results shed light on how trader characteristics and market factors impact an individual’s propensity to herd.
|Journal of International Financial Markets, Institutions and Money
|Early online date
|8 Jan 2024
|E-pub ahead of print - 8 Jan 2024
Bibliographical notePublisher Copyright:
© 2023 Elsevier B.V.
- Behavioural finance
- Retail traders