Purpose

With the unprecedented growth of digitalization across the globe, a new asset class, that is cryptocurrency, has emerged to attract investors of all stripe. The novelty of this newly emerged asset class has led researchers to gauge anomalous trade patterns and behavioural fallacies in the crypto market. Therefore, the present study aims to examine the herd behaviour in a newly evolved cryptocurrency market during normal, skewed, Bitcoin bubble and COVID-19 phases. It, then, investigates the significance of Bitcoin in driving herding bias in the market. Finally, the study gauges herding contagion between the crypto market and stock markets.

Design/methodology/approach

The study employs daily closing prices of cryptocurrencies and relevant stocks of S&P 500 (USA), S&P BSE Sensex (Index) and MERVAL (Argentina) indices for a period spanning from June 2015 to May 2020. Quantile regression specifications of Chang et al.’s (2000) absolute deviation method have been used to locate herding bias. Dummy regression models have also been deployed to examine herd activity during skewed, crises and COVID-19 phases.

Findings

The descriptive statistics reveal that the relevant distributions are leptokurtic, justifying the selection of quantile regression to diagnose tails for herding bias. The empirical results provide robust evidence of crypto herd activity during normal, bullish and high volatility periods. Next, the authors find that the assumptions of traditional financial doctrines hold during the Bitcoin bubble. Further, the study reveals that the recent outbreak of COVID-19 subjects the crypto market to herding activity at quantile (t) = 0.60. Finally, no contagion is observed between cryptocurrency and stock market herding.

Practical implications

Drawing on the empirical findings, it is believed that in this age of digitalization and technological escalation, this new asset class can offer diversification benefits to the investors. Also, the crypto market seems quite immune to behavioural idiosyncrasies during turbulence. This may relieve regulators of the possible instability this market may pose to the entire financial system.

Originality/value

The present study appears to be the first attempt to diagnose leptokurtic tails of relevant distribution for crypto herding in the wake of two remarkable events: the crypto asset bubble (2016–2017) and the outbreak of coronavirus (early 2020).

中文翻译：

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加密市场中的羊群效应：严重分布尾巴的诊断

目的

随着全球数字化的空前发展，一种新的资产类别，即加密货币，应运而生，吸引了各行各业的投资者。这种新出现的资产类别的新颖性促使研究人员衡量加密市场中的异常交易模式和行为谬误。因此，本研究旨在检验新发展的加密货币市场在正常、倾斜、比特币泡沫和 COVID-19 阶段的羊群行为。然后，它调查了比特币在推动市场羊群偏见方面的重要性。最后，该研究衡量了加密货币市场和股票市场之间的羊群传染。

设计/方法/途径

该研究采用了 2015 年 6 月至 2020 年 5 月期间加密货币和标准普尔 500 指数（美国）、标准普尔 BSE Sensex（指数）和 MERVAL（阿根廷）指数相关股票的每日收盘价。Chang等人的分位数回归规范。s (2000) 绝对偏差法已被用于定位羊群偏差。还部署了虚拟回归模型来检查倾斜、危机和 COVID-19 阶段的牛群活动。

发现

描述性统计显示相关分布呈尖峰分布，证明选择分位数回归来诊断尾部的羊群偏差是合理的。实证结果为正常、看涨和高波动期间的加密羊群活动提供了有力证据。接下来，作者发现传统金融学说的假设在比特币泡沫期间仍然有效。此外，该研究表明，最近爆发的 COVID-19 使加密货币市场受到分位数 ( t ) = 0.60 的羊群活动的影响。最后，在加密货币和股市羊群之间没有观察到传染。

实际影响

根据实证研究结果，人们相信，在这个数字化和技术升级的时代，这种新资产类别可以为投资者带来多元化收益。此外，加密市场似乎对动荡期间的行为特质完全免疫。这可能会减轻监管机构对这个市场可能对整个金融体系造成的不稳定的影响。

原创性/价值

本研究似乎是在两个显着事件之后诊断加密羊群相关分布的 leptokurtic 尾部的首次尝试：加密资产泡沫（2016-2017 年）和冠状病毒爆发（2020 年初）。