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System-wide implications of funding risk

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  • Hałaj, Grzegorz
Abstract
Funding risk has a systemic aspect that is frequently neglected in research and risk management applications. We build a model that focuses on systemic consequences of funding risk and its links with solvency conditions and account for pertinent interactions between market participants in an agent-based modelling fashion. The model is brought to a set of real banking system data of the stress test component of the 2014 Comprehensive Assessment in the EU, covering all the major banking groups in the EU. The potential shock amplification role of asset managers is studied in the theoretical part of the model, with some styled calibration and simulations. We investigate importance of the channels through which the funding shock hitting financial institutions can propagate across the financial system. We find that the drivers of the contagion transmission, related to available liquidity and capital buffers, sensitivities of funding cost to loss absorption capacity and asset prices to fire sales of assets depend on the heterogeneity of the agents in the financial system. Second, liquidity requirements are effective instruments to mitigate contagion risk. Third, the relationship between funding shocks and contagion losses is nonlinear and exhibits cliff effects. Fourth, we find evidence of an active cross-border channel of contagion with losses spreading from one country to another. Finally, behaviours of the agents under adverse funding conditions can influence the structure of the financial market and the topology of the interbank network under stress depends on the stringency of the regulatory requirements.

Suggested Citation

  • Hałaj, Grzegorz, 2018. "System-wide implications of funding risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1151-1181.
    • Handle: RePEc:eee:phsmap:v:503:y:2018:i:c:p:1151-1181
    DOI: 10.1016/j.physa.2018.08.060
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    5. Romain Plassard, 2020. "Making a Breach: The Incorporation of Agent-Based Models into the Bank of England's Toolkit," GREDEG Working Papers 2020-30, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    6. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    7. Calimani, Susanna & Hałaj, Grzegorz & Żochowski, Dawid, 2022. "Simulating fire sales in a system of banks and asset managers," Journal of Banking & Finance, Elsevier, vol. 138(C).
    8. 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.
    9. Bardoscia, Marco & Barucca, Paolo & Codd, Adam Brinley & Hill, John, 2019. "Forward-looking solvency contagion," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).

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    Keywords

    Liquidity; Systemic risk; Agent-based models;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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