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Research on Stock Market Risk Contagion of Major Debt Crises Based on Complex Network Models—The Case of Evergrande in China

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Listed:
  • Kaihao Liang

    (Department of Mathematics, Zhongkai University of Agriculture and Engineering, No. 501, Zhongkai Road, Haizhu District, Guangzhou 510225, China)

  • Shuliang Li

    (College of Economy and Trade, Zhongkai University of Agriculture and Engineering, No. 501, Zhongkai Road, Haizhu District, Guangzhou 510225, China)

  • Wenfeng Zhang

    (College of Economy and Trade, Zhongkai University of Agriculture and Engineering, No. 501, Zhongkai Road, Haizhu District, Guangzhou 510225, China)

  • Chaolong Zhang

    (Department of Mathematics, Zhongkai University of Agriculture and Engineering, No. 501, Zhongkai Road, Haizhu District, Guangzhou 510225, China)

Abstract

After a major debt crisis occurs in a listed company, the stock prices of related enterprises may also fluctuate sharply, resulting in the spread of debt risk to more enterprises. Taking the stocks of listed companies as network nodes, we constructed a complex stock market network over three periods of time through the logarithmic return rate of stocks for the three periods of prophase, metaphase, and anaphase of the debt crisis. We studied the topological characteristics of the network and destructiveness over the three periods. Finally, the minimum spanning tree was used to construct a network and the community structure of the network. The empirical analysis took the debt crisis of the China Evergrande Company as an example to analyze the impact of its major debt crisis on the Chinese stock market. The research findings were as follows: First, the debt crisis increased the inter-industry connections within the network, that is, the correlations between enterprises in different industries was enhanced. Second, the closeness of the cross-industry connections increased the connectivity efficiency of the network, but compared with the other two periods, the debt crisis in the metaphase was less stable. Third, community research showed that in the metaphase of the debt crisis, the enterprises became the core nodes of the network.

Suggested Citation

  • Kaihao Liang & Shuliang Li & Wenfeng Zhang & Chaolong Zhang, 2024. "Research on Stock Market Risk Contagion of Major Debt Crises Based on Complex Network Models—The Case of Evergrande in China," Mathematics, MDPI, vol. 12(11), pages 1-13, May.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:11:p:1675-:d:1403333
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    References listed on IDEAS

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    1. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    2. Ouyang, Zisheng & Zhou, Xuewei & Lai, Yongzeng, 2023. "Global stock markets risk contagion: Evidence from multilayer connectedness networks in the frequency domain," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    3. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    4. Jae Woo Lee & Ashadun Nobi, 2018. "State and Network Structures of Stock Markets Around the Global Financial Crisis," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 195-210, February.
    5. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    6. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
    7. García, Javier Sánchez & Rambaud, Salvador Cruz, 2023. "Macrofinancial determinants of volatility transmission in a network of European sovereign debt markets," Finance Research Letters, Elsevier, vol. 53(C).
    8. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    9. Hu, Sunyang & Gu, Zongyuan & Wang, Yifeng & Zhang, Xiaolei, 2019. "An analysis of the clustering effect of a jump risk complex network in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 622-630.
    10. Jae Woo Lee & Ashadun Nobi, 2018. "State and Network Structures of Stock Markets around the Global Financial Crisis," Papers 1806.04363, arXiv.org.
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