The structure and resilience of financial market networks.

Clicks: 346
ID: 70093
2012
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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.
Reference Key
peron2012thechaos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Peron, Thomas Kaue Dal'Maso;Costa, Luciano da Fontoura;Rodrigues, Francisco A;
Journal chaos (woodbury, ny)
Year 2012
DOI
10.1063/1.3683467
URL
Keywords
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