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Connectivity, centralisation and ‘robustness-yet-fragility’ of interbank networks

Author

Listed:
  • Mario Eboli

    (Universitá “G. d’Annunzio” Chieti Pescara)

  • Bulent Ozel

    (Lucidminds B.V.)

  • Andrea Teglio

    (University Ca’ Foscari of Venice)

  • Andrea Toto

    (Universitá “G. d’Annunzio” Chieti Pescara
    Budapest University of Technology and Economics)

Abstract

This paper studies the effects that connectivity and centralisation have on the response of interbank networks to external shocks that generate phenomena of default contagion. We run numerical simulations of contagion processes on randomly generated networks, characterised by different degrees of density and centralisation. Our main findings show that the degree of robustness-yet-fragility of a network grows progressively with both its degree of density or centralisation, although at different paces. We also find that sparse and decentralised interbank networks are generally resilient to small shocks, contrary to what so far believed. The degree of robustness-yet-fragility of an interbank network determines its propensity to generate a too-many-to-fail problem. We argue that medium levels of density and high levels of centralisation prevent the emergence of a too-many-to-fail issue for small and medium shocks whilst drastically creating the problem in the case of large shocks. Finally, our results shed some light on the actual robustness-yet-fragility of the observed core-periphery national interbank networks, highlighting the existing risk of systemic crises.

Suggested Citation

  • Mario Eboli & Bulent Ozel & Andrea Teglio & Andrea Toto, 2023. "Connectivity, centralisation and ‘robustness-yet-fragility’ of interbank networks," Annals of Finance, Springer, vol. 19(2), pages 169-200, June.
  • Handle: RePEc:kap:annfin:v:19:y:2023:i:2:d:10.1007_s10436-022-00416-9
    DOI: 10.1007/s10436-022-00416-9
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    More about this item

    Keywords

    Systemic risk; Financial contagion; Interbank networks;
    All these keywords.

    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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