Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

A better understanding of financial contagion and systemically important financial institutions (SIFIs) is essential for the prevention and control of systemic financial risk. Considering the ripple effect of financial contagion, we integrate the relevant spatiotemporal information that affects fina...

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Main Authors: Beibei Zhang, Xuemei Xie, Xi Zhou
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2024/5316162
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author Beibei Zhang
Xuemei Xie
Xi Zhou
author_facet Beibei Zhang
Xuemei Xie
Xi Zhou
author_sort Beibei Zhang
collection DOAJ
description A better understanding of financial contagion and systemically important financial institutions (SIFIs) is essential for the prevention and control of systemic financial risk. Considering the ripple effect of financial contagion, we integrate the relevant spatiotemporal information that affects financial contagion and propose to use the ripple-spreading network to simulate the dynamic process of risk contagion in China’s financial system. In addition, we introduce the smooth-transition vector autoregression (STVAR) model to identify “high” and “low” systemic risk regimes and set the relevant parameters of the ripple-spreading network on this basis. The results show that risk ripples spread much faster in high than in low systemic risk regimes. However, systemic shocks can also trigger large-scale risk contagion in the financial system even in a low systemic risk regime as the risk ripple continues. In addition, whether the financial system is in a high or low systemic risk regime, the risk ripples from a contagion source (i.e., a real estate company) spread first to the real estate sector and the banking sector. The network centrality results of the heterogeneous ripple-spreading network indicate that most securities and banks and some real estate companies have the highest systemic importance, followed by the insurance, and finally the diversified financial institutions. Our study provides a new perspective on the regulatory practice of systemic financial risk and reminds regulators to focus not only on large institutions but also on institutions with strong ripple capacity.
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institution Kabale University
issn 1099-0526
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spelling doaj-art-5ce8023cdd224889ab324fb1a589bc292025-02-03T06:14:54ZengWileyComplexity1099-05262024-01-01202410.1155/2024/5316162Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching ModelBeibei Zhang0Xuemei Xie1Xi Zhou2School of Economics and ManagementSchool of Economics and ManagementJiyang College of Zhejiang A&F UniversityA better understanding of financial contagion and systemically important financial institutions (SIFIs) is essential for the prevention and control of systemic financial risk. Considering the ripple effect of financial contagion, we integrate the relevant spatiotemporal information that affects financial contagion and propose to use the ripple-spreading network to simulate the dynamic process of risk contagion in China’s financial system. In addition, we introduce the smooth-transition vector autoregression (STVAR) model to identify “high” and “low” systemic risk regimes and set the relevant parameters of the ripple-spreading network on this basis. The results show that risk ripples spread much faster in high than in low systemic risk regimes. However, systemic shocks can also trigger large-scale risk contagion in the financial system even in a low systemic risk regime as the risk ripple continues. In addition, whether the financial system is in a high or low systemic risk regime, the risk ripples from a contagion source (i.e., a real estate company) spread first to the real estate sector and the banking sector. The network centrality results of the heterogeneous ripple-spreading network indicate that most securities and banks and some real estate companies have the highest systemic importance, followed by the insurance, and finally the diversified financial institutions. Our study provides a new perspective on the regulatory practice of systemic financial risk and reminds regulators to focus not only on large institutions but also on institutions with strong ripple capacity.http://dx.doi.org/10.1155/2024/5316162
spellingShingle Beibei Zhang
Xuemei Xie
Xi Zhou
Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model
Complexity
title Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model
title_full Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model
title_fullStr Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model
title_full_unstemmed Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model
title_short Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model
title_sort ripple spreading network of china s systemic financial risk contagion new evidence from the regime switching model
url http://dx.doi.org/10.1155/2024/5316162
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AT xuemeixie ripplespreadingnetworkofchinassystemicfinancialriskcontagionnewevidencefromtheregimeswitchingmodel
AT xizhou ripplespreadingnetworkofchinassystemicfinancialriskcontagionnewevidencefromtheregimeswitchingmodel