论文信息 - Community Structure Detection of Shanghai Stock Market Based on Complex Networks

Community Structure Detection of Shanghai Stock Market Based on Complex Networks

To investigate community structure of the component stocks of SSE 180-index, a stock correlation network is built taking the stocks as vertices and the correlation coefficient of logarithm returns of stock price as edges. It is built as undirected weighted at first. GN algorithm is chosen to detect community structure after transferring it into un-weighted based on different thresholds. The result shows that the stock market researched in this paper has obvious industrial characteristics.

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