Your browser doesn't support javascript.
loading
Network Dynamics of a Financial Ecosystem.
Somin, Shahar; Altshuler, Yaniv; Gordon, Goren; Pentland, Alex 'Sandy'; Shmueli, Erez.
Afiliação
  • Somin S; Industrial Engineering Department, Tel Aviv University, Tel Aviv, Israel. shaharso@media.mit.edu.
  • Altshuler Y; MIT Media Lab, Cambridge, MA, USA. shaharso@media.mit.edu.
  • Gordon G; MIT Media Lab, Cambridge, MA, USA.
  • Pentland A'; Endor Ltd., Tel Aviv, Israel.
  • Shmueli E; Industrial Engineering Department, Tel Aviv University, Tel Aviv, Israel.
Sci Rep ; 10(1): 4587, 2020 03 12.
Article em En | MEDLINE | ID: mdl-32165674
ABSTRACT
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.

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article