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Systemic risk in centralised interbank networks

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  • Eboli, Mario

Abstract

In this paper, I investigate the relationship between centralisation and systemic resilience in two-tiered interbank networks. Using flow network theory, I characterise the systemic contagion thresholds of stylised Core–Periphery (CP) and Star-Core–Periphery (SCP) networks, focusing on two fundamental contagion channels: common exposures and direct balance-sheet default contagion. Both network typologies are benchmarked against the maximally centralised star networks. The results demonstrate that centralisation when embedded within a modular two-tiered structure, enhances systemic resilience against shocks by reducing aggregate interbank exposures and constraining the spread of contagion across regions of the network. However, this stability comes at a cost. The obtained results highlight a fundamental trade-off between efficiency and risk concentration posed by the centralisation of interbank networks. While the centralisation of interbank exposures facilitates more efficient liquidity reallocations among banks and attenuates the spread of decentralised shocks, it simultaneously amplifies the vulnerability of the network to distress at the hub nodes. Indeed, the two-tiered modular structure of CP and SCP appears particularly exposed to the risk of systemic crises if all hub nodes, i.e. all banks in the core, suffer an exogenous solvency shock. The consequent policy implications for real-world core–periphery networks underscore the importance of reducing the likelihood of common shocks to core banks penalising them for holding overlapping and correlated portfolios.

Suggested Citation

  • Eboli, Mario, 2025. "Systemic risk in centralised interbank networks," Journal of Financial Stability, Elsevier, vol. 81(C).
  • Handle: RePEc:eee:finsta:v:81:y:2025:i:c:s1572308925001007
    DOI: 10.1016/j.jfs.2025.101471
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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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