Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent

• Published in: Physica A 2022-06, Vol.596, p.127170, Article 127170
• Main Authors: Arouxet, M. Belén, Bariviera, Aurelio F., Pastor, Verónica E., Vampa, Victoria
• Format: Article
• Language: English
• Subjects: Covid-19; Cryptocurrencies; Hurst exponent; Wavelet transform
• ISSN: 0378-4371; 1873-2119
• DOI: 10.1016/j.physa.2022.127170

Cryptocurrency history begins in 2008 as a means of payment proposal. However, cryptocurrencies evolved into a complex ecosystem of 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 seven important coins. Our study covers the pre-Covid-19 and the subsequent pandemic 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. •Analysis of high frequency (5 to 20 min data) of seven cryptocurrencies.•Long range memory measured by a new wavelet-based Hurst exponent method.•Covid-19 pandemic slightly affected the long memory of cryptocurrency returns.•Covid-19 pandemic produced a temporary severe impact in the long memory of volatility.•Measures of long-range dependence is similar at different frequencies.