Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F22%3A63553978" target="_blank" >RIV/70883521:28120/22:63553978 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1057521922001004" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1057521922001004</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.irfa.2022.102132" target="_blank" >10.1016/j.irfa.2022.102132</a>
Alternative languages
Result language
angličtina
Original language name
Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19
Original language description
In this paper, we study the long memory behavior of Bitcoin, Litecoin, Ethereum, Ripple, Monero, and Dash with a focus on the COVID-19 period. Initially, we apply a time-varying Lifting method to estimate the Hurst exponent for each cryptocurrency. Then we test for a change in persistence over time. To model the multivariate con-nectivity, the wavelet-based multivariate long memory approach proposed by Achard and Gannaz (2016) is implemented. Our results indicate a change in the long-range dependence for the majority of cryptocurrencies, with a noticeable downward trend in persistence after the 2017 bubble and then a dramatic drop after the outbreak of COVID-19. The drop in persistence after COVID-19 is further illustrated by the Fractal connectivity matrix obtained from the Wavelet long-memory model. Our findings provide important implications regarding the evolution of market efficiency in the cryptocurrency market and the associated fractal structure and dy-namics of the crypto prices over time.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Review of Financial Analysis
ISSN
1057-5219
e-ISSN
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Volume of the periodical
82
Issue of the periodical within the volume
Neuveden
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
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UT code for WoS article
000806724700003
EID of the result in the Scopus database
2-s2.0-85128278696