An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers

Autores
Fernández Bariviera, Aurelio; Zunino, Luciano José; Rosso, Osvaldo Aníbal
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper discusses the dynamics of intraday prices of 12 cryptocurrencies during the past months´ boom and bust. The importance of this study lies in the extended coverage of the cryptoworld, accounting for more than 90% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.
Centro de Investigaciones Ópticas
Materia
Física
Cryptocurrencies
Blockchain technology
High-frequency data
Complexity-entropy causality plane
Informational efficiency
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/97950
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiersFernández Bariviera, AurelioZunino, Luciano JoséRosso, Osvaldo AníbalFísicaCryptocurrenciesBlockchain technologyHigh-frequency dataComplexity-entropy causality planeInformational efficiencyThis paper discusses the dynamics of intraday prices of 12 cryptocurrencies during the past months´ boom and bust. The importance of this study lies in the extended coverage of the cryptoworld, accounting for more than 90% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.Centro de Investigaciones Ópticas2018-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/97950enginfo:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/89539info:eu-repo/semantics/altIdentifier/url/https://aip.scitation.org/doi/10.1063/1.5027153info:eu-repo/semantics/altIdentifier/issn/1054-1500info:eu-repo/semantics/altIdentifier/doi/10.1063/1.5027153info:eu-repo/semantics/altIdentifier/hdl/11336/89539info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T17:01:25Zoai:sedici.unlp.edu.ar:10915/97950Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 17:01:25.645SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
title An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
spellingShingle An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
Fernández Bariviera, Aurelio
Física
Cryptocurrencies
Blockchain technology
High-frequency data
Complexity-entropy causality plane
Informational efficiency
title_short An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
title_full An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
title_fullStr An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
title_full_unstemmed An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
title_sort An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers
dc.creator.none.fl_str_mv Fernández Bariviera, Aurelio
Zunino, Luciano José
Rosso, Osvaldo Aníbal
author Fernández Bariviera, Aurelio
author_facet Fernández Bariviera, Aurelio
Zunino, Luciano José
Rosso, Osvaldo Aníbal
author_role author
author2 Zunino, Luciano José
Rosso, Osvaldo Aníbal
author2_role author
author
dc.subject.none.fl_str_mv Física
Cryptocurrencies
Blockchain technology
High-frequency data
Complexity-entropy causality plane
Informational efficiency
topic Física
Cryptocurrencies
Blockchain technology
High-frequency data
Complexity-entropy causality plane
Informational efficiency
dc.description.none.fl_txt_mv This paper discusses the dynamics of intraday prices of 12 cryptocurrencies during the past months´ boom and bust. The importance of this study lies in the extended coverage of the cryptoworld, accounting for more than 90% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.
Centro de Investigaciones Ópticas
description This paper discusses the dynamics of intraday prices of 12 cryptocurrencies during the past months´ boom and bust. The importance of this study lies in the extended coverage of the cryptoworld, accounting for more than 90% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.
publishDate 2018
dc.date.none.fl_str_mv 2018-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/97950
url http://sedici.unlp.edu.ar/handle/10915/97950
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/89539
info:eu-repo/semantics/altIdentifier/url/https://aip.scitation.org/doi/10.1063/1.5027153
info:eu-repo/semantics/altIdentifier/issn/1054-1500
info:eu-repo/semantics/altIdentifier/doi/10.1063/1.5027153
info:eu-repo/semantics/altIdentifier/hdl/11336/89539
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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