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Structure Characteristics of the International Stock Market Complex Network in the Perspective of Whole and Part

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  • Guangxi Cao
  • Yingying Shi
  • Qingchen Li

Abstract

International stock market forms an abstract complex network through the fluctuation correlation of stock price index. Past studies of complex network almost focus on single country’s stock market. Here we investigate the whole and partial characteristics of international stock market network (ISMN) (hereinafter referred to as ISMN). For the analysis on the whole network, we firstly determine the reasonable threshold as the basic of the following study. Robustness is applied to analyze the stability of the network and the result shows that ISMN has robustness against random attack but intentional attack breaks the connection integrity of ISMN rapidly. In the partial network, the sliding window method is used to analyze the dynamic evolution of the relationship between the Chinese (Shanghai) stock market and the international stock market. The connection between the Chinese stock market and foreign stock markets becomes increasingly closer, and the links between them show a significant enhancement especially after China joined the WTO. In general, we suggest that transnational investors pay more attention to some significant event of the stock market with large degree for better risk-circumvention.

Suggested Citation

  • Guangxi Cao & Yingying Shi & Qingchen Li, 2017. "Structure Characteristics of the International Stock Market Complex Network in the Perspective of Whole and Part," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-11, March.
  • Handle: RePEc:hin:jnddns:9731219
    DOI: 10.1155/2017/9731219
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    Cited by:

    1. Wang, Yanli & Li, Huajiao & Guan, Jianhe & Liu, Nairong, 2019. "Similarities between stock price correlation networks and co-main product networks: Threshold scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 66-77.
    2. Cai, Wenxue & Liang, Fenfen & Wan, Yanchun & Zhong, Huiling & Gu, Yimiao, 2021. "An innovative approach for constructing a shipping index based on dynamic weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).

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