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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

The structure and resilience of financial market networks

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Autor(es):
Dal'Maso Peron, Thomas Kaue [1] ; Costa, Luciano da Fontoura [1] ; Rodrigues, Francisco A. [2]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Fis Sao Carlos, BR-13560970 Sao Paulo - Brazil
[2] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Dept Matemat Aplicada & Estat, BR-13560970 Sao Paulo - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: Chaos; v. 22, n. 1 MAR 2012.
Citações Web of Science: 39
Resumo

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. {[}doi:10.1063/1.3683467] (AU)

Processo FAPESP: 05/00587-5 - Modelagem por redes (grafos) e técnicas de reconhecimento de padrões: estrutura, dinâmica e aplicações
Beneficiário:Roberto Marcondes Cesar Junior
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 10/19440-2 - Caracterização, análise, simulação e classificação de redes complexas
Beneficiário:Francisco Aparecido Rodrigues
Linha de fomento: Auxílio à Pesquisa - Regular