Systemic Importance and Risk Characteristics of Banks Based on a Multi-Layer Financial Network Analysis

被引:2
|
作者
Gao, Qianqian [1 ]
Fan, Hong [2 ]
Yu, Chengyang [2 ]
机构
[1] Shanghai Lixin Univ Accounting & Finance, Sch Financial Technol, Shanghai 201209, Peoples R China
[2] Donghua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China
基金
中国国家自然科学基金;
关键词
systemic risk; PageRank algorithm; network; centrality; risk exposure; CONTAGION; TOPOLOGY;
D O I
10.3390/e26050378
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Domestic and international risk shocks have greatly increased the demand for systemic risk management in China. This paper estimates China's multi-layer financial network based on multiple financial relationships among banks, assets, and firms, using China's banking system data in 2021. An improved PageRank algorithm is proposed to identify systemically important banks and other economic sectors, and a stress test is conducted. This study finds that China's multi-layer financial network is sparse, and the distribution of transactions across financial markets is uneven. Regulatory authorities should support economic recovery and adjust the money supply, while banks should differentiate competition and manage risks better. Based on the PageRank index, this paper assesses the systemic importance of large commercial banks from the perspective of network structure, emphasizing the role of banks' transaction behavior and market participation. Different industries and asset classes are also assessed, suggesting that increased attention should be paid to industry risks and regulatory oversight of bank investments. Finally, stress tests confirm that the improved PageRank algorithm is applicable within the multi-layer financial network, reinforcing the need for prudential supervision of the banking system and revealing that the degree of transaction concentration will affect the systemic importance of financial institutions.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Systemic Risk Analysis of Multi-Layer Financial Network System Based on Multiple Interconnections between Banks, Firms, and Assets
    Gao, Qianqian
    ENTROPY, 2022, 24 (09)
  • [2] Systemic risk of multi-layer financial network system under macroeconomic fluctuations
    Gao, Qianqian
    Lv, Dayong
    Jin, Xiaomei
    FRONTIERS IN PHYSICS, 2022, 10
  • [3] Financial risk contagion based on dynamic multi-layer network between banks and firms
    Jin, Qichao
    Sun, Lei
    Chen, Yanyu
    Hu, Zhao-Long
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 638
  • [4] The multi-layer network nature of systemic risk and its implications for the costs of financial crises
    Poledna, Sebastian
    Luis Molina-Borboa, Jose
    Martinez-Jaramillo, Serafin
    van der Leij, Marco
    Thurner, Stefan
    JOURNAL OF FINANCIAL STABILITY, 2015, 20 : 70 - 81
  • [5] Reducing systemic risk in a multi-layer network using reinforcement learning
    Le, Richard
    Ku, Hyejin
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 605
  • [6] Systemic importance analysis of chinese financial institutions based on volatility spillover network
    Huang, Wei-Qiang
    Wang, Dan
    CHAOS SOLITONS & FRACTALS, 2018, 114 : 19 - 30
  • [7] Financial systemic risk measurement based on causal network connectedness analysis
    Gong, Xiao-Li
    Liu, Xi-Hua
    Xiong, Xiong
    Zhang, Wei
    INTERNATIONAL REVIEW OF ECONOMICS & FINANCE, 2019, 64 : 290 - 307
  • [8] Financial penalties and banks' systemic risk
    Koester, Hannes
    Pelster, Matthias
    JOURNAL OF RISK FINANCE, 2018, 19 (02) : 154 - 173
  • [9] Multi-Layer Network Performance and Reliability Analysis
    Oikonomou, Kostas N.
    Sinha, Rakesh K.
    Doverspike, Robert D.
    INTERNATIONAL JOURNAL OF INTERDISCIPLINARY TELECOMMUNICATIONS AND NETWORKING, 2009, 1 (03) : 1 - 30
  • [10] Monetary Policy and Systemic Risk in a Financial Network System Based on Multi-Agent Modeling
    Gao, Qianqian
    Fan, Hong
    Pang, Congyuan
    MATHEMATICS, 2025, 13 (03)