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Analysis of the impact of Sino-US trade friction on China’s stock market based on complex networks

Author

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  • Li, Yanshuang
  • Zhuang, Xintian
  • Wang, Jian
  • Zhang, Weiping

Abstract

This paper analyzes the impact of the Sino-US trade friction incident in 2018 on China's stock market by using the complex network methods. Firstly, we divide the Sino-US trade friction incident in 2018 into four research periods. Based on the GARCH-BEKK model and the Planar Maximum Filter Graph (PMFG) algorithm, the volatility spillover network between China's stock market sectors and the stock price correlation network of China's stock market corresponding to the above four research periods are constructed. Next, from the perspective of sectors in stock market, we use various network centrality indicators to build a systematic importance comprehensive evaluation index of industry sectors in the stock market through the principal component analysis method, to explore the impact of the Sino-US trade friction incident on the risk spillover effects of sectors in China's stock market. From the perspective of the overall stock market, we analyze the impact of Sino-US trade friction incident on the overall stability of the stock market through calculating the network topology indicators and conducting simulation experiments. Finally, the main factors affecting the stability mechanism of China's stock market are studied through the probit model. The results show that: (1) The risk spillover effect of various sectors in China's stock market changes significantly in different periods of Sino-US trade friction, and there are obvious cyclical rotation effects among various sectors (2) When some weighted stocks in the stock market abnormally fluctuate or suffer targeted shocks, the China's stock market's ability to maintain stability is weak, and the Sino-US trade friction will reduce the stability of China's stock market, and the higher the intensity of trade friction incident is, the more obvious the impact of the incident is. (3) The important factors that affect the abnormal fluctuations in China's stock market include four types of indicators: the stock market network structure, the fluctuation of important international stock indexes, the fluctuation of commodity prices in the international market, and the domestic macroeconomic indicators. This study provides a reference for China's financial regulatory authorities to conduct macro-prudential management, control systemic risks, and maintain the stability of financial market.

Suggested Citation

  • Li, Yanshuang & Zhuang, Xintian & Wang, Jian & Zhang, Weiping, 2020. "Analysis of the impact of Sino-US trade friction on China’s stock market based on complex networks," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
  • Handle: RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940820300826
    DOI: 10.1016/j.najef.2020.101185
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    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Silva, Thiago Christiano & de Souza, Sergio Rubens Stancato & Tabak, Benjamin Miranda, 2016. "Network structure analysis of the Brazilian interbank market," Emerging Markets Review, Elsevier, vol. 26(C), pages 130-152.
    3. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    4. Nishimura, Yusaku & Sun, Bianxia, 2018. "The intraday volatility spillover index approach and an application in the Brexit vote," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 241-253.
    5. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency Crashes in Emerging Markets: Empirical Indicators," Center for International and Development Economics Research (CIDER) Working Papers 233424, University of California-Berkeley, Department of Economics.
    6. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    7. M. Tumminello & T. Di Matteo & T. Aste & R. N. Mantegna, 2007. "Correlation based networks of equity returns sampled at different time horizons," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 209-217, January.
    8. Pollard, Stephen K. & Sapra, Sunil K. & Canarella, Giorgio, 2007. "Asymmetry and Spillover Effects in the North American Equity Markets," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-52.
    9. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    10. Lundgren, Amanda Ivarsson & Milicevic, Adriana & Uddin, Gazi Salah & Kang, Sang Hoon, 2018. "Connectedness network and dependence structure mechanism in green investments," Energy Economics, Elsevier, vol. 72(C), pages 145-153.
    11. Fang Chen & Xuanjuan Chen & Zhenzhen Sun & Tong Yu & Ming Zhong, 2013. "Systemic Risk, Financial Crisis, and Credit Risk Insurance," The Financial Review, Eastern Finance Association, vol. 48(3), pages 417-442, August.
    12. Laeven, Luc & Ratnovski, Lev & Tong, Hui, 2016. "Bank size, capital, and systemic risk: Some international evidence," Journal of Banking & Finance, Elsevier, vol. 69(S1), pages 25-34.
    13. 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.
    14. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    15. Yanan Li & David E. Giles, 2015. "Modelling Volatility Spillover Effects Between Developed Stock Markets and Asian Emerging Stock Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 155-177, March.
    16. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2015. "Intra-daily volatility spillovers in international stock markets," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 95-114.
    17. I�aki Aldasoro & Ignazio Angeloni, 2015. "Input-output-based measures of systemic importance," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 589-606, April.
    18. Rochet, Jean-Charles & Tirole, Jean, 1996. "Interbank Lending and Systemic Risk," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(4), pages 733-762, November.
    19. Varotto, Simone & Zhao, Lei, 2018. "Systemic risk and bank size," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 45-70.
    20. Michael D. Bordo & Michael J. Dueker & David C. Wheelock, 2002. "Aggregate Price Shocks and Financial Instability: A Historical Analysis," Economic Inquiry, Western Economic Association International, vol. 40(4), pages 521-538, October.
    21. Nishimura, Yusaku & Tsutsui, Yoshiro & Hirayama, Kenjiro, 2015. "Intraday return and volatility spillover mechanism from Chinese to Japanese stock market," Journal of the Japanese and International Economies, Elsevier, vol. 35(C), pages 23-42.
    22. Samuel G. Hanson & Anil K. Kashyap & Jeremy C. Stein, 2011. "A Macroprudential Approach to Financial Regulation," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 3-28, Winter.
    23. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    24. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency crashes in emerging markets: An empirical treatment," Journal of International Economics, Elsevier, vol. 41(3-4), pages 351-366, November.
    25. Christian Brownlees & Robert F. Engle, 2017. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
    26. Alotaibi, Abdullah R. & Mishra, Anil V., 2015. "Global and regional volatility spillovers to GCC stock markets," Economic Modelling, Elsevier, vol. 45(C), pages 38-49.
    27. Zihui Yang & Yinggang Zhou, 2017. "Quantitative Easing and Volatility Spillovers Across Countries and Asset Classes," Management Science, INFORMS, vol. 63(2), pages 333-354, February.
    28. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    29. Soramäki, Kimmo & Cook, Samantha, 2013. "SinkRank: An algorithm for identifying systemically important banks in payment systems," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-27.
    30. Huang, Wei-Qiang & Wang, Dan, 2018. "Systemic importance analysis of chinese financial institutions based on volatility spillover network," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 19-30.
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    4. Saifullah Khan & Adnan Shoaib, 2024. "Firm value adjustment speed through financial friction in the presence of earnings management and productivity growth: evidence from emerging economies," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
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    More about this item

    Keywords

    Complex network; Volatility spillover effect; Planar Maximum Filter Graph; Sino-US trade friction; Stock market stability;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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