Briola, Antonio;
Aste, Tomaso;
(2022)
Dependency Structures in Cryptocurrency Market from High to Low Frequency.
Entropy
, 24
(11)
, Article 1548. 10.3390/e24111548.
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Abstract
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.
Type: | Article |
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Title: | Dependency Structures in Cryptocurrency Market from High to Low Frequency |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.3390/e24111548 |
Publisher version: | https://doi.org/10.3390/e24111548 |
Language: | English |
Additional information: | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | complex systems; network science; econophysics; economics; financial markets; cryptocurrencies |
UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
URI: | https://discovery.ucl.ac.uk/id/eprint/10158658 |
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