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Community Structure Detection of Shanghai Stock Market Based on Complex Networks

In: Liss 2014

Author

Listed:
  • Sen Wu

    (University of Science and Technology Beijing)

  • Mengjiao Tuo

    (University of Science and Technology Beijing)

  • Deying Xiong

    (University of Science and Technology Beijing)

Abstract

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.

Suggested Citation

  • Sen Wu & Mengjiao Tuo & Deying Xiong, 2015. "Community Structure Detection of Shanghai Stock Market Based on Complex Networks," Springer Books, in: Zhenji Zhang & Zuojun Max Shen & Juliang Zhang & Runtong Zhang (ed.), Liss 2014, edition 127, pages 1661-1666, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-43871-8_239
    DOI: 10.1007/978-3-662-43871-8_239
    as

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