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.

我们通过使用独特的交易者交易数据集为有关加密货币市场羊群效应的文献做出贡献。使用流行的指标，我们发现了羊群效应的重要证据，考虑到信息的零星性以及这个市场固有的模糊性和匿名性，羊群效应主要是由个人模仿自己过去的交易驱动的。在看跌时期，羊群效应会更高，因为交易者对负面消息的反应更加相似。我们发现了由于流动性较差的加密货币中的信息级联而故意羊群效应的证据，其中重大的价格变动可能被解释为有价值的信息。拥有较大账户的交易者倾向于模仿自己过去的交易。成熟的交易者由于对风险和实验的容忍度较低，因此进行类似的交易。我们发现交易者之间的羊群差异是由于他们所在的当地金融体系的管理环境而产生的。此外，由于加密货币及其交易个人的模糊性较高，与其他市场报道的情况相比，羊群效应的持续性较低。最后，波动等市场因素对羊群效应有显着影响。我们的结果揭示了交易者特征和市场因素如何影响个人的从众倾向。