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Network-based risk measurements for interbank systems.

Yongli Li1, Guanghe Liu1,2, Paolo Pin3

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This study introduces new measurements for systemic risk in interbank networks, demonstrating their ability to assess default risk and inform strategies for risk reduction in financial systems.

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Area of Science:

  • Financial economics
  • Network theory
  • Risk management

Background:

  • Interbank networks are crucial for financial stability.
  • Evaluating systemic risk is complex due to interconnectedness.
  • Existing metrics may not fully capture network-specific risks.

Purpose of the Study:

  • To propose novel measurements for systemic risk in interbank networks.
  • To formally prove the properties of these measurements.
  • To provide insights into mitigating systemic risk.

Main Methods:

  • Development of risk distance, risk degree, and m-order risk degree metrics.
  • Formal mathematical proofs of measurement properties.
  • Analysis of the relationship between proposed metrics and financial contagion.

Main Results:

  • The proposed measurements effectively capture the impact of bank size, liability structure, and discount factors on default risk.
  • These metrics reflect risks at both individual bank and system-wide levels.
  • The rationality of the measurements is supported by their properties and link to financial contagion.

Conclusions:

  • The new measurements offer a robust framework for assessing systemic risk in interbank systems.
  • Findings provide a basis for developing targeted interventions to enhance financial stability.
  • The study contributes to a deeper understanding of financial contagion dynamics.