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Identifying systemically important financial institutions in complex network: A case study of Chinese stock market

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  • Chen, Wei
  • Hou, Xiaoli
  • Jiang, Manrui
  • Jiang, Cheng

Abstract

In this paper, we identify the dynamic influence of financial institutions based on a complex network modelling method. We first construct a financial network based on stock comprehensive evaluation (SCE), which is obtained by the technique for order preference by similarity to an ideal solution (TOPSIS). Then, the dynamic influence of financial institutions is identified by iterating the static influence of each network. The results indicate that (i) the dynamic influence of financial institutions is greater than their static influence in analysing the evolution of influence and (ii) banks and securities institutions play an important role in the financial system.

Suggested Citation

  • Chen, Wei & Hou, Xiaoli & Jiang, Manrui & Jiang, Cheng, 2022. "Identifying systemically important financial institutions in complex network: A case study of Chinese stock market," Emerging Markets Review, Elsevier, vol. 50(C).
  • Handle: RePEc:eee:ememar:v:50:y:2022:i:c:s1566014121000443
    DOI: 10.1016/j.ememar.2021.100836
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    as
    1. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    2. Banulescu, Georgiana-Denisa & Dumitrescu, Elena-Ivona, 2015. "Which are the SIFIs? A Component Expected Shortfall approach to systemic risk," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 575-588.
    3. Chang, Carolyn W. & Li, Xiaodan & Lin, Edward M.H. & Yu, Min-Teh, 2018. "Systemic risk, interconnectedness, and non-core activities in Taiwan insurance industry," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 273-284.
    4. 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.
    5. Chen Zhou, 2010. "Are Banks Too Big to Fail? Measuring Systemic Importance of Financial Institutions," International Journal of Central Banking, International Journal of Central Banking, vol. 6(34), pages 205-250, December.
    6. Zhao, Longfeng & Wang, Gang-Jin & Wang, Mingang & Bao, Weiqi & Li, Wei & Stanley, H. Eugene, 2018. "Stock market as temporal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1104-1112.
    7. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    8. Gang-Jin Wang & Chi Xie & Shou Chen, 2017. "Multiscale correlation networks analysis of the US stock market: a wavelet analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 561-594, October.
    9. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2019. "Financial systemic risk measurement based on causal network connectedness analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 290-307.
    10. Tumminello, Michele & Lillo, Fabrizio & Mantegna, Rosario N., 2010. "Correlation, hierarchies, and networks in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 75(1), pages 40-58, July.
    11. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    12. Drakos, Anastassios A. & Kouretas, Georgios P., 2015. "Bank ownership, financial segments and the measurement of systemic risk: An application of CoVaR," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 127-140.
    13. 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.
    14. 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.
    15. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    16. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
    17. Mo, Hongming & Deng, Yong, 2019. "Identifying node importance based on evidence theory in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 529(C).
    18. Li, Chao & Wang, Li & Sun, Shiwen & Xia, Chengyi, 2018. "Identification of influential spreaders based on classified neighbors in real-world complex networks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 512-523.
    19. Fei, Liguo & Zhang, Qi & Deng, Yong, 2018. "Identifying influential nodes in complex networks based on the inverse-square law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1044-1059.
    20. Bentian Li & Dechang Pi, 2018. "Analysis of global stock index data during crisis period via complex network approach," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-16, July.
    21. Marco Bardoscia & Stefano Battiston & Fabio Caccioli & Guido Caldarelli, 2015. "DebtRank: A Microscopic Foundation for Shock Propagation," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-13, June.
    22. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, vol. 102(3), pages 59-64, May.
    23. Daniele Petrone & Vito Latora, 2016. "A dynamic approach merging network theory and credit risk techniques to assess systemic risk in financial networks," Papers 1610.00795, arXiv.org, revised Apr 2018.
    24. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    25. Hamed Amini & Rama Cont & Andreea Minca, 2016. "Resilience To Contagion In Financial Networks," Mathematical Finance, Wiley Blackwell, vol. 26(2), pages 329-365, April.
    26. Namaki, A. & Shirazi, A.H. & Raei, R. & Jafari, G.R., 2011. "Network analysis of a financial market based on genuine correlation and threshold method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3835-3841.
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