Stocks network of coal and power sectors in China stock markets

Abstract

To explore the interaction among stocks and improve the ability to build portfolios, a Stocks Network of Coal and Power Sectors (SNCPS) was modeled in China stock markets, in which nodes were stocks, and edges were correlation coefficients of stocks logarithm returns from 1991 to 2009. The study calculated nodes degree and cluster coefficient of SNCPS, analyzed its centrality by social network way and community by k-plex, particularly advanced Backbone Network (BN) conception, developed Algorithm of the Largest Eigenvalue of Weight Matrix to detect BN. Results show that SNCPS is scale-free, negative exponent of node-degree distribution less than 1, the average cluster coefficient 0.68 for unweighted networks and 0.41 for weighted networks, node 000723, 601898, and 601918 with high betweenness, SNCPS with two partitions, the BN with 10 nodes which influences entire network greatly. © Springer-Verlag 2010.