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Dependency Structures in Cryptocurrency Market from High to Low Frequency

We investigate logarithmic price returns cross-correlations at different time horizons for a set of 25 liquid cryptocurrencies traded on the FTX digital currency exchange. We study how the structure of the Minimum Spanning Tree (MST) and the Triangulated Maximally Filtered Graph (TMFG) evolve from h...

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Detalles Bibliográficos
Autores principales: Briola, Antonio, Aste, Tomaso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689460/
https://www.ncbi.nlm.nih.gov/pubmed/36359637
http://dx.doi.org/10.3390/e24111548
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author Briola, Antonio
Aste, Tomaso
author_facet Briola, Antonio
Aste, Tomaso
author_sort Briola, Antonio
collection PubMed
description We investigate logarithmic price returns cross-correlations at different time horizons for a set of 25 liquid cryptocurrencies traded on the FTX digital currency exchange. We study how the structure of the Minimum Spanning Tree (MST) and the Triangulated Maximally Filtered Graph (TMFG) evolve from high (15 s) to low (1 day) frequency time resolutions. For each horizon, we test the stability, statistical significance and economic meaningfulness of the networks. Results give a deep insight into the evolutionary process of the time dependent hierarchical organization of the system under analysis. A decrease in correlation between pairs of cryptocurrencies is observed for finer time sampling resolutions. A growing structure emerges for coarser ones, highlighting multiple changes in the hierarchical reference role played by mainstream cryptocurrencies. This effect is studied both in its pairwise realizations and intra-sector ones.
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spelling pubmed-96894602022-11-25 Dependency Structures in Cryptocurrency Market from High to Low Frequency Briola, Antonio Aste, Tomaso Entropy (Basel) Article We investigate logarithmic price returns cross-correlations at different time horizons for a set of 25 liquid cryptocurrencies traded on the FTX digital currency exchange. We study how the structure of the Minimum Spanning Tree (MST) and the Triangulated Maximally Filtered Graph (TMFG) evolve from high (15 s) to low (1 day) frequency time resolutions. For each horizon, we test the stability, statistical significance and economic meaningfulness of the networks. Results give a deep insight into the evolutionary process of the time dependent hierarchical organization of the system under analysis. A decrease in correlation between pairs of cryptocurrencies is observed for finer time sampling resolutions. A growing structure emerges for coarser ones, highlighting multiple changes in the hierarchical reference role played by mainstream cryptocurrencies. This effect is studied both in its pairwise realizations and intra-sector ones. MDPI 2022-10-28 /pmc/articles/PMC9689460/ /pubmed/36359637 http://dx.doi.org/10.3390/e24111548 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Briola, Antonio
Aste, Tomaso
Dependency Structures in Cryptocurrency Market from High to Low Frequency
title Dependency Structures in Cryptocurrency Market from High to Low Frequency
title_full Dependency Structures in Cryptocurrency Market from High to Low Frequency
title_fullStr Dependency Structures in Cryptocurrency Market from High to Low Frequency
title_full_unstemmed Dependency Structures in Cryptocurrency Market from High to Low Frequency
title_short Dependency Structures in Cryptocurrency Market from High to Low Frequency
title_sort dependency structures in cryptocurrency market from high to low frequency
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689460/
https://www.ncbi.nlm.nih.gov/pubmed/36359637
http://dx.doi.org/10.3390/e24111548
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