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Projecting XRP price burst by correlation tensor spectra of transaction networks
Cryptoassets are becoming essential in the digital economy era. XRP is one of the large market cap cryptoassets. Here, we develop a novel method of correlation tensor spectra for the dynamical XRP networks, which can provide an early indication for XRP price. A weighed directed weekly transaction ne...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033910/ https://www.ncbi.nlm.nih.gov/pubmed/36949100 http://dx.doi.org/10.1038/s41598-023-31881-5 |
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author | Chakraborty, Abhijit Hatsuda, Tetsuo Ikeda, Yuichi |
author_facet | Chakraborty, Abhijit Hatsuda, Tetsuo Ikeda, Yuichi |
author_sort | Chakraborty, Abhijit |
collection | PubMed |
description | Cryptoassets are becoming essential in the digital economy era. XRP is one of the large market cap cryptoassets. Here, we develop a novel method of correlation tensor spectra for the dynamical XRP networks, which can provide an early indication for XRP price. A weighed directed weekly transaction network among XRP wallets is constructed by aggregating all transactions for a week. A vector for each node is then obtained by embedding the weekly network in continuous vector space. From a set of weekly snapshots of node vectors, we construct a correlation tensor. A double singular value decomposition of the correlation tensors gives its singular values. The significance of the singular values is shown by comparing with its randomize counterpart. The evolution of singular values shows a distinctive behavior. The largest singular value shows a significant negative correlation with XRP/USD price. We observe the minimum of the largest singular values at the XRP/USD price peak during the first week of January 2018. The minimum of the largest singular value during January 2018 is explained by decomposing the correlation tensor in the signal and noise components and also by evolution of community structure. |
format | Online Article Text |
id | pubmed-10033910 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100339102023-03-24 Projecting XRP price burst by correlation tensor spectra of transaction networks Chakraborty, Abhijit Hatsuda, Tetsuo Ikeda, Yuichi Sci Rep Article Cryptoassets are becoming essential in the digital economy era. XRP is one of the large market cap cryptoassets. Here, we develop a novel method of correlation tensor spectra for the dynamical XRP networks, which can provide an early indication for XRP price. A weighed directed weekly transaction network among XRP wallets is constructed by aggregating all transactions for a week. A vector for each node is then obtained by embedding the weekly network in continuous vector space. From a set of weekly snapshots of node vectors, we construct a correlation tensor. A double singular value decomposition of the correlation tensors gives its singular values. The significance of the singular values is shown by comparing with its randomize counterpart. The evolution of singular values shows a distinctive behavior. The largest singular value shows a significant negative correlation with XRP/USD price. We observe the minimum of the largest singular values at the XRP/USD price peak during the first week of January 2018. The minimum of the largest singular value during January 2018 is explained by decomposing the correlation tensor in the signal and noise components and also by evolution of community structure. Nature Publishing Group UK 2023-03-22 /pmc/articles/PMC10033910/ /pubmed/36949100 http://dx.doi.org/10.1038/s41598-023-31881-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chakraborty, Abhijit Hatsuda, Tetsuo Ikeda, Yuichi Projecting XRP price burst by correlation tensor spectra of transaction networks |
title | Projecting XRP price burst by correlation tensor spectra of transaction networks |
title_full | Projecting XRP price burst by correlation tensor spectra of transaction networks |
title_fullStr | Projecting XRP price burst by correlation tensor spectra of transaction networks |
title_full_unstemmed | Projecting XRP price burst by correlation tensor spectra of transaction networks |
title_short | Projecting XRP price burst by correlation tensor spectra of transaction networks |
title_sort | projecting xrp price burst by correlation tensor spectra of transaction networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033910/ https://www.ncbi.nlm.nih.gov/pubmed/36949100 http://dx.doi.org/10.1038/s41598-023-31881-5 |
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