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Network Dynamics of a Financial Ecosystem
Global financial crises have led to the understanding that classical econometric models are limited in comprehending financial markets in extreme conditions, partially since they disregarded complex interactions within the system. Consequently, in recent years research efforts have been directed tow...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067835/ https://www.ncbi.nlm.nih.gov/pubmed/32165674 http://dx.doi.org/10.1038/s41598-020-61346-y |
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author | Somin, Shahar Altshuler, Yaniv Gordon, Goren Pentland, Alex ’Sandy’ Shmueli, Erez |
author_facet | Somin, Shahar Altshuler, Yaniv Gordon, Goren Pentland, Alex ’Sandy’ Shmueli, Erez |
author_sort | Somin, Shahar |
collection | PubMed |
description | Global financial crises have led to the understanding that classical econometric models are limited in comprehending financial markets in extreme conditions, partially since they disregarded complex interactions within the system. Consequently, in recent years research efforts have been directed towards modeling the structure and dynamics of the underlying networks of financial ecosystems. However, difficulties in acquiring fine-grained empirical financial data, due to regulatory limitations, intellectual property and privacy control, still hinder the application of network analysis to financial markets. In this paper we study the trading of cryptocurrency tokens on top of the Ethereum Blockchain, which is the largest publicly available financial data source that has a granularity of individual trades and users, and which provides a rare opportunity to analyze and model financial behavior in an evolving market from its inception. This quickly developing economy is comprised of tens of thousands of different financial assets with an aggregated valuation of more than 500 Billion USD and typical daily volume of 30 Billion USD, and manifests highly volatile dynamics when viewed using classic market measures. However, by applying network theory methods we demonstrate clear structural properties and converging dynamics, indicating that this ecosystem functions as a single coherent financial market. These results suggest that a better understanding of traditional markets could become possible through the analysis of fine-grained, abundant and publicly available data of cryptomarkets. |
format | Online Article Text |
id | pubmed-7067835 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70678352020-03-19 Network Dynamics of a Financial Ecosystem Somin, Shahar Altshuler, Yaniv Gordon, Goren Pentland, Alex ’Sandy’ Shmueli, Erez Sci Rep Article Global financial crises have led to the understanding that classical econometric models are limited in comprehending financial markets in extreme conditions, partially since they disregarded complex interactions within the system. Consequently, in recent years research efforts have been directed towards modeling the structure and dynamics of the underlying networks of financial ecosystems. However, difficulties in acquiring fine-grained empirical financial data, due to regulatory limitations, intellectual property and privacy control, still hinder the application of network analysis to financial markets. In this paper we study the trading of cryptocurrency tokens on top of the Ethereum Blockchain, which is the largest publicly available financial data source that has a granularity of individual trades and users, and which provides a rare opportunity to analyze and model financial behavior in an evolving market from its inception. This quickly developing economy is comprised of tens of thousands of different financial assets with an aggregated valuation of more than 500 Billion USD and typical daily volume of 30 Billion USD, and manifests highly volatile dynamics when viewed using classic market measures. However, by applying network theory methods we demonstrate clear structural properties and converging dynamics, indicating that this ecosystem functions as a single coherent financial market. These results suggest that a better understanding of traditional markets could become possible through the analysis of fine-grained, abundant and publicly available data of cryptomarkets. Nature Publishing Group UK 2020-03-12 /pmc/articles/PMC7067835/ /pubmed/32165674 http://dx.doi.org/10.1038/s41598-020-61346-y Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Somin, Shahar Altshuler, Yaniv Gordon, Goren Pentland, Alex ’Sandy’ Shmueli, Erez Network Dynamics of a Financial Ecosystem |
title | Network Dynamics of a Financial Ecosystem |
title_full | Network Dynamics of a Financial Ecosystem |
title_fullStr | Network Dynamics of a Financial Ecosystem |
title_full_unstemmed | Network Dynamics of a Financial Ecosystem |
title_short | Network Dynamics of a Financial Ecosystem |
title_sort | network dynamics of a financial ecosystem |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067835/ https://www.ncbi.nlm.nih.gov/pubmed/32165674 http://dx.doi.org/10.1038/s41598-020-61346-y |
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