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Efficient construction of threshold networks of stock markets

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  • Xin-Jian Xu
  • Kuo Wang
  • Liucun Zhu
  • Li-Jie Zhang

Abstract

Although the threshold network is one of the most used tools to characterize the underlying structure of a stock market, the identification of the optimal threshold to construct a reliable stock network remains challenging. In this paper, the concept of dynamic consistence between the threshold network and the stock market is proposed. The optimal threshold is estimated by maximizing the consistence function. The application of this procedure to stocks belonging to Standard \& Pool's 500 Index from January 2006 to December 2011 yields the threshold value 0.28. In analyzing topological characteristics of the generated network, three globally financial crises can be distinguished well from the evolutionary perspective.

Suggested Citation

  • Xin-Jian Xu & Kuo Wang & Liucun Zhu & Li-Jie Zhang, 2018. "Efficient construction of threshold networks of stock markets," Papers 1803.06223, arXiv.org, revised Aug 2018.
    • Handle: RePEc:arx:papers:1803.06223
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    Cited by:

    1. Su, Qingqing & Tu, Lilan & Wang, Xianjia & Rong, Hang, 2022. "Construction and robustness of directed-weighted financial stock networks via meso-scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    2. Hongxing Yao & Yanyu Lu & Bilal Ahmed Memon, 2019. "Impact of US-China Trade War on the Network Topology Structure of Chinese Stock Market," Journal of Asian Business Strategy, Asian Economic and Social Society, vol. 9(2), pages 235-250, December.
    3. Zhang, Yaozhong & Wu, Junfeng & Zhang, Chao, 2021. "Risk transfer between stock and open-ended equity fund markets in China based on a multi-layer network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    4. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    5. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    6. Ku, Seungmo & Lee, Changju & Chang, Woojin & Wook Song, Jae, 2020. "Fractal structure in the S&P500: A correlation-based threshold network approach," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).

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