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Financial risk propagation between Chinese and American stock markets based on multilayer networks

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  • Huang, Qi-An
  • Zhao, Jun-Chan
  • Wu, Xiao-Qun

Abstract

Stock networks, which are constructed from stock price time series, are useful tools for analyzing complex behaviors in stock markets. Following former researches, the epidemic model has been usually used to detect dynamic characteristics in a stock price complex systems. Recently, multilayer networks have been demonstrated well when working on heterogeneous nodes rather than integrated networks. In this paper, we proposed a two-layer SIR propagation model with an infective medium to analyze the spread of financial shocks. In consideration of strict financial regulation in the A shares, the model assumed that capital cannot flow directly between layers but through the Hong Kong stock market. By applying the model to constituent stocks included in three prominent indices, Standard & Poor 500, Shanghai and Shenzhen 300, and Hang Seng(medium), we established a two-layer Granger networks. Betweenness showed that the Hong Kong stock market had a promoting transition function of financial shocks between the US stock markets and the mainland China stock markets. In addition, with a big basic reproduction number, stock markets system appeared to be vulnerable during extreme financial shock such as the outbreak of COVID-19 epidemic and the meltdown of stock markets. Furthermore, sensitivity analysis and the spreading simulation indicated that the US stock markets were much more robust to financial shocks than the mainland China stock markets.

Suggested Citation

  • Huang, Qi-An & Zhao, Jun-Chan & Wu, Xiao-Qun, 2022. "Financial risk propagation between Chinese and American stock markets based on multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
  • Handle: RePEc:eee:phsmap:v:586:y:2022:i:c:s0378437121007184
    DOI: 10.1016/j.physa.2021.126445
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    References listed on IDEAS

    as
    1. David Hartman & Jaroslav Hlinka, 2018. "Nonlinearity in stock networks," Papers 1804.10264, arXiv.org, revised Jun 2018.
    2. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
    3. Corsi, Fulvio & Lillo, Fabrizio & Pirino, Davide & Trapin, Luca, 2018. "Measuring the propagation of financial distress with Granger-causality tail risk networks," Journal of Financial Stability, Elsevier, vol. 38(C), pages 18-36.
    4. Dastkhan, Hossein & Gharneh, Naser Shams, 2018. "How the ownership structures cause epidemics in financial markets: A network-based simulation model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 324-342.
    5. Bai, Ye & Chow, Darien Yan Pang, 2017. "Shanghai-Hong Kong Stock Connect: An analysis of Chinese partial stock market liberalization impact on the local and foreign markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 182-203.
    6. An, Feng & Gao, Xiangyun & Guan, Jianhe & Huang, Shupei & Liu, Qian, 2017. "Modeling the interdependent network based on two-mode networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 57-67.
    7. Jin Qin & Yuxin He & Linglin Ni, 2014. "Quantitative Efficiency Evaluation Method for Transportation Networks," Sustainability, MDPI, vol. 6(12), pages 1-15, November.
    8. Yuanyuan Ma & Lingxuan Li, 2018. "Crisis Spreading Model of the Shareholding Networks of Listed Companies and Their Main Holders and Their Controllability," Complexity, Hindawi, vol. 2018, pages 1-17, December.
    9. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2017. "Informative Contagion Dynamics in a Multilayer Network Model of Financial Markets," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 343-366, November.
    10. Marina Dolfin & Damian Knopoff & Michele Limosani & Maria Gabriella Xibilia, 2019. "Credit Risk Contagion and Systemic Risk on Networks," Mathematics, MDPI, vol. 7(8), pages 1-16, August.
    11. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    12. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    13. 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.
    14. Zheng, Muhua & Wang, Wei & Tang, Ming & Zhou, Jie & Boccaletti, S. & Liu, Zonghua, 2018. "Multiple peaks patterns of epidemic spreading in multi-layer networks," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 135-142.
    15. Antonia Godoy-Lorite & Roger Guimerà & Marta Sales-Pardo, 2016. "Long-Term Evolution of Email Networks: Statistical Regularities, Predictability and Stability of Social Behaviors," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-11, January.
    16. Wen-Jie Xie & Ming-Xia Li & Hai-Chuan Xu & Wei Chen & Wei-Xing Zhou & H. E. Stanley, 2016. "Quantifying immediate price impact of trades based on the $k$-shell decomposition of stock trading networks," Papers 1611.06666, arXiv.org, revised Dec 2016.
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    1. Jin, Qichao & Sun, Lei & Chen, Yanyu & Hu, Zhao-Long, 2024. "Financial risk contagion based on dynamic multi-layer network between banks and firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).

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