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Area of Science:

  • Financial economics
  • Network theory
  • Risk management

Background:

  • Financial stability relies on strengthening large or interconnected banks.
  • Clustering among homogeneous banks can also lead to financial fragility, a less studied area.
  • Systemic risk is a major concern in modern financial systems.

Purpose of the Study:

  • To explore policy improvements for preventing systemic risk by analyzing the clustering patterns of systemically important banks (SIBs).
  • To understand the relationship between SIB clustering and systemic risk contagion.
  • To propose network-based tools for optimizing bank networks and reducing systemic risk.

Main Methods:

  • Utilizing a network optimization model to analyze SIB clustering patterns.
  • Examining the impact of network structure on systemic risk contagion.
  • Developing and evaluating policy tools such as inter-SIBs exposure limits and pairwise capital requirements.

Main Results:

  • The clustering pattern of SIBs is significantly related to systemic risk contagion.
  • Networks with fewer connections among SIBs (disassortative networks) exhibit lower systemic risk.
  • Systemic vulnerability of smaller banks is reduced in disassortative networks.

Conclusions:

  • Optimizing network structures by reducing SIB clustering is crucial for mitigating systemic risk.
  • Inter-SIBs exposure limits and pairwise capital requirements are effective network-based tools.
  • Combining existing capital surcharges with proposed network-based tools enhances financial stability more effectively than current policies.