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Herding behaviour in digital currency markets: An integrated survey and empirical estimation

机译:数字货币市场中的掠夺行为:综合调查和实证估计

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摘要

This paper reviews the empirical literature on the highly popular phenomenon of herding behaviour in the markets of digital currencies. Furthermore, a comparison takes place with outcomes from earlier studies about traditional financial assets. Moreover, we empirically investigate herding behaviour of 240 cryptocurrencies during bull and bear markets. The present survey suggests that empirical findings about whether herding phenomena have made a significant appearance or not in cryptocurrency markets are split. The Cross-sectional absolute deviations (CSAD) and Cross-sectional standard deviations (CSSD) approaches for measuring herding tendencies are found to be the most popular. Different behaviour is detected in bull periods compared to bear markets. Nevertheless, evidence from primary studies indicates that herding is stronger during extreme situations rather than in normal conditions. However, our empirical estimations reveal that herding behaviour is evident only in bull markets. These findings cast light on and provide a roadmap for investment decisions with modern forms of liquidity.
机译:本文评论了数字货币市场中掠夺行为高度流行现象的实证文献。此外,比较从早期研究传统金融资产的结果进行了比较。此外,我们在公牛和熊市期间经验探讨了240个加密货币的掠过行为。目前的调查表明,关于掠过现象是否在加密货币中取得了显着外观的实证发现。发现横断面的绝对偏差(CSAD)和横截面标准偏差(CSSD)测量放牧趋势的方法是最受欢迎的。与熊市相比,在熊时期检测到不同的行为。然而,来自初级研究的证据表明,在极端情况下,放牧比正常情况更强大。然而,我们的实证估计表明,雄牧行为仅在牛市中很明显。这些调查结果投放了光线,并提供了具有现代流动性的投资决策路线图。

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