论文标题
COVID-19对加密货币的影响：基于小波的Hurst指数的证据
Covid-19 impact on cryptocurrencies: evidence from a wavelet-based Hurst exponent
论文作者
论文摘要
加密货币历史始于2008年，是一种付款建议。但是，加密货币演变为复杂的高产投机资产。与传统的金融工具相反，它们不是（主要）在有组织的，守法的场所进行交易，而是在匿名统治的在线平台上。本文使用11个重要硬币的高频时间序列研究了回报和波动性的长期记忆。我们的研究涵盖了前旋转前和随后的大麻时期。我们使用基于小波变换的最近开发的方法，该方法提供了赫斯特指数的更强大的估计器。我们检测到，在Covid-19-19大流行的峰值（2020年3月左右）期间，回报的长期记忆仅受到轻微影响。但是，波动率在其远距离相关结构中暂时影响。我们的结果可能对学者和从业人员感兴趣。
Cryptocurrency history begins in 2008 as a means of payment proposal. However, cryptocurrencies evolved into complex, high yield speculative assets. Contrary to traditional financial instruments, they are not (mostly) traded in organized, law-abiding venues, but on online platforms, where anonymity reigns. This paper examines the long term memory in return and volatility, using high frequency time series of eleven important coins. Our study covers the pre-Covid-19 and the subsequent pandemia period. We use a recently developed method, based on the wavelet transform, which provides more robust estimators of the Hurst exponent. We detect that, during the peak of Covid-19 pandemic (around March 2020), the long memory of returns was only mildly affected. However, volatility suffered a temporary impact in its long range correlation structure. Our results could be of interest for both academics and practitioners.
