HIERARCHICAL ORGANIZATION AND DISASSORTATIVE MIXING OF CORRELATION-BASED WEIGHTED FINANCIAL NETWORKS
Shi-Min Cai (),
Tao Zhou and
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Shi-Min Cai: Department of Electronic Science and Technology, University of Science and Technology of China, Hefei Anhui 230026, P. R. China;
Yan-Bo Zhou: Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700 Fribourg, Switzerland
Tao Zhou: Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700 Fribourg, Switzerland;
Pei-Ling Zhou: Department of Electronic Science and Technology, University of Science and Technology of China, Hefei Anhui 230026, P. R. China
International Journal of Modern Physics C (IJMPC), 2010, vol. 21, issue 03, 433-441
Correlation-based weighted financial networks are analyzed to present cumulative distribution of strength with a power-law tail, which suggests that a small number of hub-like stocks have greater influence on the whole fluctuation of financial market than others. The relationship between clustering and connectivity of vertices emphasizes hierarchical organization, which has been depicted by minimal span tree in previous work. These results urge us to further study the mixing patter of financial network to understand the tendency for vertices to be connected to vertices that are like (or unlike) them in some way. The measurement of average nearest-neighbor degree running over classes of vertices with degreekshows a descending trend whenkincreases. This interesting result is first uncovered in our work, and suggests the disassortative mixing of financial network which refers to a bias in favor of connections between dissimilar vertices. All the results in weighted complex network aspect may provide some insights to deeper understand the underlying mechanism of financial market and model the evolution of financial market.
Keywords: Weighted financial networks; correlation matrix; power-law; hierarchical structure; disassortative mixing; 89.65.-s; 89.75.-k; 89.90.+n (search for similar items in EconPapers)
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