dc.contributor.author |
Danylchuk, Hanna |
|
dc.contributor.author |
Kibalnyk, Liubov |
|
dc.contributor.author |
Kovtun, Oksana |
|
dc.contributor.author |
Ків, Арнольд Юхимович |
|
dc.contributor.author |
Pursky, Oleg |
|
dc.contributor.author |
Berezhna, Galina |
|
dc.date.accessioned |
2021-09-07T17:25:54Z |
|
dc.date.available |
2021-09-07T17:25:54Z |
|
dc.date.issued |
2020-10-26 |
|
dc.identifier.citation |
Danylchuk H. Modelling of cryptocurrency market using fractal and entropy analysis in COVID-19 / Hanna Danylchuk, Liubov Kibalnyk, Oksana Kovtun, Arnold Kiv, Oleg Pursky, Galina Berezhna // CEUR Workshop Proceedings. - Vol. 2713. - P. 352-371. |
uk |
dc.identifier.issn |
1613-0073 |
|
dc.identifier.uri |
http://ceur-ws.org/Vol-2713/paper40.pdf |
|
dc.identifier.uri |
http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/4477 |
|
dc.identifier.uri |
https://doi.org/10.31812/123456789/4477 |
|
dc.description.abstract |
In this article, we present the results of simulation for cryptocurrency
market based on fractal and entropy analysis using six cryptocurrencies in the
first 20 of the capitalization rating. The application of the selected research
methods is based on an analysis of existing methodologies and tools of economic
and mathematical modeling of financial markets. It has been shown that
individual methods are not relevant because they do not provide an adequate
assessment of the given market, so an integrated approach is the most appropriate.
Daily values of cryptocurrency pairs from August 2016 to August 2020 selected
by the monitoring and modelling database. The application of fractal analysis led
to the conclusion that the time series of selected cryptocurrencies were persistent.
And the use of the window procedure for calculating the local Hurst coefficient
allowed to detail and isolate the persistant and antipersistant gaps.
Interdisciplinary methods, namely Tsallis entropy and wavelet entropy, are
proposed to complement the results. The results of the research show that Tsallis
entropy reveals special (crisis) conditions in the cryptocurrency market, despite
the nature of the crises’ origin. Wavelet entropy is a warning indicator of crisis
phenomena. It provides additional information on a small scale. |
uk |
dc.language.iso |
en |
uk |
dc.publisher |
CEUR Workshop Proceedings |
uk |
dc.subject |
cryptocurrency market |
uk |
dc.subject |
fractal analysis |
uk |
dc.subject |
wavelet entropy |
uk |
dc.subject |
Tsallis entropy |
uk |
dc.subject |
crisis |
uk |
dc.subject |
COVID-19 |
uk |
dc.title |
Modelling of cryptocurrency market using fractal and entropy analysis in COVID-19 |
uk |
dc.type |
Article |
uk |