Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19

Nick James, Max Menzies and Jennifer Chan

Physica A: Statistical Mechanics and its Applications, 2021, vol. 565, issue C

Abstract: This paper introduces new methods for analysing the extreme and erratic behaviour of time series to evaluate the impact of COVID-19 on cryptocurrency market dynamics. Across 51 cryptocurrencies, we examine extreme behaviour through a study of distribution extremities, and erratic behaviour through structural breaks. First, we analyse the structure of the market as a whole and observe a reduction in self-similarity as a result of COVID-19, particularly with respect to structural breaks in variance. Second, we compare and contrast these two behaviours, and identify individual anomalous cryptocurrencies. Tether (USDT) and TrueUSD (TUSD) are consistent outliers with respect to their returns, while Holo (HOT), NEXO (NEXO), Maker (MKR) and NEM (XEM) are frequently observed as anomalous with respect to both behaviours and time. Even among a market known as consistently volatile, this identifies individual cryptocurrencies that behave most irregularly in their extreme and erratic behaviour and shows these were more affected during the COVID-19 market crisis.

Keywords: COVID-19; Cryptocurrencies; Nonlinear dynamics; Time series; Anomaly detection (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:565:y:2021:i:c:s0378437120308797

DOI: 10.1016/j.physa.2020.125581

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