MULTIFRACTAL BEHAVIOR OF CRYPTOCURRENCIES BEFORE AND DURING COVID-19

Ying-Hui Shao, Han Xu, Ying-Lin Liu and Hai-Chuan Xu
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Ying-Hui Shao: School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai 201620, P. R. China
Han Xu: School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai 201620, P. R. China
Ying-Lin Liu: ��School of Finance, Shanghai University of Finance and Economics, Shanghai 200433, P. R. China
Hai-Chuan Xu: ��School of Business, East China University of Science and Technology, Shanghai 200237, P. R. China

FRACTALS (fractals), 2021, vol. 29, issue 06, 1-10

Abstract: Based on high-frequency data, we study the difference in cryptocurrency market before and during the COVID-19. We analyze the multifractality of three major cryptocurrencies via the multifractal detrended fluctuation analysis (MFDFA). To investigate the source of multifractality, we construct shuffled, surrogated and truncate data. The results show that market efficiency of cryptocurrency has decreased during COVID-19. The cryptocurrency multifractal characteristics mainly come from non-Gaussian distribution. Additionally, the components of multifractal nature have changed during the pandemic. The results provide evidence for the impact of COVID-19 on cryptocurrency market.

Keywords: Cryptocurrency; MFDFA; COVID-19; Multifractality; Generalized Hurst Exponent; High-Frequency Data (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:29:y:2021:i:06:n:s0218348x21501322

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DOI: 10.1142/S0218348X21501322

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