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Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework

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  • Hai-Chuan Xu

    (College of Management and Economics - TJU - Tianjin University, China Center for Social Computing and Analytics - TJU - Tianjin University)

  • Fredj Jawadi

    (LUMEN - Lille University Management Lab - ULR 4999 - Université de Lille)

  • Jie Zhou

    (IFM - Department of Physics, Chemistry and Biology [Linköping] - LIU - Linköping University)

  • Wei-Xing Zhou

Abstract

Financial risk is spread and amplified through the interconnectedness among financial institutions. We apply a time-varying parameter vector autoregression model to analyze the dynamic spillover effects in the Chinese financial system. We find that the 2017 house price control policies have significantly increased the risk of China’s financial system. Before 2017, with the prosperity of the real estate market, the interconnectedness of the Chinese financial system continued to decline, while after 2017, with the slowdown of house price growth and the downturn of the real estate market, the interconnectedness turned to increase. For different sectors, the trends and the magnitudes of the spillover effects are diverse, and any sector can contribute to systemic risk in a dynamic way. Finally, we rank 20 systemically important financial institutions according to two centrality measures. The stable institution ranking provides less noisy information for regulators to formulate a policy and intervene in the market effectively.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2022. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Post-Print hal-04478741, HAL.
    • Handle: RePEc:hal:journl:hal-04478741
    DOI: 10.1007/s00181-022-02338-x
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    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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