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Agent-based modeling of systemic risk in the European banking sector

Author

Listed:
  • Petr Teply

    (University of Economics in Prague)

  • Tomas Klinger

    (University of Economics in Prague)

Abstract

In this paper, we use an agent-based simulation combined with innovative calibration techniques to model the European banking system as accurately as possible. Our novel contribution to the recent literature involves adding bank heterogeneity to the model. To estimate the levels of shock propagation in large-scale events, such as the default of multiple banks, as well as smaller events, such as the defaults of an individual bank, we provide granular modeling of bank behavior. We extend the existing network approach by adding the ability to model banks of various sizes and the detailed connections of 286 individual banks across 9 European countries. Our main results show how the failure of a large Italian bank or of a medium-sized German bank might create a cascade of problems for the entire European banking sector. Our results reveal that Italian banks make a much larger contribution to systemic risk than German or French banks. We believe that computational experiments in this model provide valuable insights into systemic risk within the European banking system for policy makers when estimating the systemic effects of individual bank defaults. From a regulatory perspective, we recommend the introduction of a tighter limit for all types of inter-bank exposures than the recent limit of 25% of Tier 1 capital. Moreover, we propose an increase in the risk-weights for exposures to large banks in Germany, France, Italy, and Spain.

Suggested Citation

  • Petr Teply & Tomas Klinger, 2019. "Agent-based modeling of systemic risk in the European banking sector," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 811-833, December.
  • Handle: RePEc:spr:jeicoo:v:14:y:2019:i:4:d:10.1007_s11403-018-0226-7
    DOI: 10.1007/s11403-018-0226-7
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    2. Morteza Alaeddini & Julie Dugdale & Paul Reaidy & Philippe Madiès, 2023. "Exploring Credit Relationship Dynamics in an Interbank Market Benefiting from Blockchain-based Distributed Trust: Insights from an Agent-based Model," Post-Print hal-04266077, HAL.
    3. Siklos, Pierre L. & Stefan, Martin, 2021. "Exchange rate shocks in multicurrency interbank markets," Journal of Financial Stability, Elsevier, vol. 55(C).
    4. Walter Farkas & Patrick Lucescu, 2024. "Modeling Risk Sharing and Impact on Systemic Risk," Mathematics, MDPI, vol. 12(13), pages 1-19, July.
    5. Valentina Macchiati & Giuseppe Brandi & Tiziana Di Matteo & Daniela Paolotti & Guido Caldarelli & Giulio Cimini, 2022. "Systemic liquidity contagion in the European interbank market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 443-474, April.
    6. Lilit Popoyan & Mauro Napoletano & Andrea Roventini, 2023. "Systemically important banks - emerging risk and policy responses: An agent-based investigation," LEM Papers Series 2023/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Di Xiao & Andreas Krause, 2022. "Bank demand for central bank liquidity and its impact on interbank markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(3), pages 639-679, July.
    8. Afef Bouattour & Maha Kalai & Kamel Helali, 2024. "The non-linear relationship between ESG performance and bank stability in the digital era: new evidence from a regime-switching approach," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.

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    More about this item

    Keywords

    Agent-based models; Bank; Contagion; Network models; Systemic risk;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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