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

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  • Arouxet, M. Belén
  • Bariviera, Aurelio F.
  • Pastor, Verónica E.
  • Vampa, Victoria

Abstract

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.

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  • Arouxet, M. Belén & Bariviera, Aurelio F. & Pastor, Verónica E. & Vampa, Victoria, 2022. "Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    • Handle: RePEc:eee:phsmap:v:596:y:2022:i:c:s0378437122001765
    DOI: 10.1016/j.physa.2022.127170
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    7. Majid Mirzaee Ghazani & Ali Akbar Momeni Malekshah & Reza Khosravi, 2024. "Analyzing time–frequency connectedness between cryptocurrencies, stock indices, and benchmark crude oils during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-28, December.
    8. Bejaoui, Azza & Mgadmi, Nidhal & Moussa, Wajdi, 2022. "On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis," Resources Policy, Elsevier, vol. 77(C).
    9. Kai Meng & Khalid Khan, 2024. "Is cryptocurrency Efficient? A High-Frequency Asymmetric Multifractality Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2225-2246, June.
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