Risk sharing framework and systemic tolerance in Indian banks: Double layer network approach

被引:0
|
作者
Banerjee, Ameet Kumar [1 ]
Rahman, Molla Ramizur [2 ]
Misra, Arun Kumar [3 ]
Sensoy, Ahmet [4 ]
机构
[1] Xavier Sch Management, XLRI, Jamshedpur, Jharkhand, India
[2] IIM Bodh Gaya, Turi Khurd, Bihar, India
[3] Indian Inst Technol Kharagpur, Kharagpur, India
[4] Bilkent Univ, Fac Business Adm, Ankara, Turkiye
关键词
Systemic tolerance; Systemic risk; Duplex network; Threshold distance; CAPITAL SHORTFALL;
D O I
10.1016/j.ribaf.2024.102636
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Interconnectedness spreads systemic risk and is critical in enhancing banks' systemic tolerance through interbank liquidity and lines of credit. Literature on systemic risk has not considered the importance of interconnectedness in providing liquidity to improve banks' systemic tolerance. As a bank's resistivity towards systemic disruption depends on its tolerance, the current article develops a model to measure the systemic tolerance of individual banks in a two-layer interbank network using Delta CoVaR. It estimates systemic tolerance distance through a risk-sharing framework and analyzes the significance of macroeconomic and bank-specific factors in explaining systemic tolerance. The results support that systemic tolerance values are higher during the downcycle than the up-cycle, signaling the importance of interconnectedness in protecting against systemic crises. The empirics further substantiate that risk-sharing distance is lower, and structure is complex with clusters during economic down-cycle. This highlights that banks couple with each other during stressful environments and empirically validate the importance of interbank and lines of credit in enhancing systemic tolerance and, therefore, possess the regulator to develop a robust interbank market through regulatory guidelines.
引用
收藏
页数:13
相关论文
共 38 条
  • [21] Systemic risk in the Angolan interbank payment system - a network approach
    Borges, Maria Rosa
    Ulica, Lauriano
    Gubareva, Mariya
    APPLIED ECONOMICS, 2020, 52 (45) : 4900 - 4912
  • [22] 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
  • [23] Reducing systemic risk in a multi-layer network using reinforcement learning
    Le, Richard
    Ku, Hyejin
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 605
  • [24] The framework of systemic risk related to contagion, recovery rate and capital requirement in an interbank network
    Ren, Xuemin
    Yuan, George X.
    Jiang, Lishang
    INTERNATIONAL JOURNAL OF FINANCIAL ENGINEERING, 2014, 1 (01)
  • [25] Systemic risk of multi-layer financial network system under macroeconomic fluctuations
    Gao, Qianqian
    Lv, Dayong
    Jin, Xiaomei
    FRONTIERS IN PHYSICS, 2022, 10
  • [26] Systemic risk of China's commercial banks during financial turmoils in 2010-2020: A MIDAS-QR based CoVaR approach
    Liu, Shuting
    Xu, Qifa
    Jiang, Cuixia
    APPLIED ECONOMICS LETTERS, 2021, 28 (18) : 1600 - 1609
  • [27] Systemic risk in the Chinese financial system: A copula-based network approach
    Zhang, Zhiwei
    Zhang, Dayong
    Wu, Fei
    Ji, Qiang
    INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, 2021, 26 (02) : 2044 - 2063
  • [28] Measuring network systemic risk contributions: A leave-one-out approach
    Hue, Sullivan
    Lucotte, Yannick
    Tokpavi, Sessi
    JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2019, 100 : 86 - 114
  • [29] Systemic risk measurement: A Quantile Long Short-Term Memory network approach
    Aprea, Imma Lory
    Scognamiglio, Salvatore
    Zanetti, Paolo
    APPLIED SOFT COMPUTING, 2024, 152
  • [30] Concentrated commonalities and systemic risk in China's banking system: A contagion network approach
    Shi, Qing
    Sun, Xiaoqi
    Jiang, Yile
    INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 2022, 83