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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

The structure and resilience of financial market networks

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Author(s):
Dal'Maso Peron, Thomas Kaue [1] ; Costa, Luciano da Fontoura [1] ; Rodrigues, Francisco A. [2]
Total Authors: 3
Affiliation:
[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
Total Affiliations: 2
Document type: Journal article
Source: Chaos; v. 22, n. 1 MAR 2012.
Web of Science Citations: 39
Abstract

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)

FAPESP's process: 10/19440-2 - Characterization, analysis, simulation and classification of complex networks
Grantee:Francisco Aparecido Rodrigues
Support type: Regular Research Grants
FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants