Topological Properties of Stock Index Futures Based on Network Approach

Abstract

To analyze the topological properties of stock index futures data, we used coarse-graining process to transform stock index futures' price time series from April 19, 2010 to February 22, 2013 into a sequence of modals. Each modal was a 5-symbol string. A complex network of stock index futures was constructed by this modals sequence. The network contained 148 kinds of different nodes. We calculated the dynamical statistics of the degree, degree distribution, average path length, clustering coefficient and betweenness centrality of the network. The degree of the network and the accumulated degree distribution showed a power-law distribution, so did the relationship between the nodes' degree and their ranks. The experiment results reveal that appearance probability of the degree numbers of top 31 nodes is extremely higher than the others. These conclusions may contribute to the forecast of the stock index futures' price.