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Distress and default contagion in financial networks

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  • Veraart, Luitgard A. M.

Abstract

We develop a new model for solvency contagion that can be used to quantify systemic risk in stress tests of financial networks. In contrast to many existing models it allows for the spread of contagion already before the point of default and hence can account for contagion due to distress and mark-to-market losses. We derive general ordering results for outcome measures of stress tests that enable us to compare different contagion mechanisms. We use these results to study the sensitivity of the new contagion mechanism with respect to its model parameters and to compare it to existing models in the literature. When applying the new model to data from the European Banking Authority we find that the risk from distress contagion is strongly dependent on the anticipated recovery rate. For low recovery rates the high additional losses caused by bankruptcy dominate the overall stress test results. For high recovery rates, however, we observe a strong sensitivity of the stress test outcomes with respect to the model parameters determining the magnitude of distress contagion.

Suggested Citation

  • Veraart, Luitgard A. M., 2020. "Distress and default contagion in financial networks," LSE Research Online Documents on Economics 101905, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:101905
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    References listed on IDEAS

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    Cited by:

    1. Paolo Barucca & Marco Bardoscia & Fabio Caccioli & Marco D'Errico & Gabriele Visentin & Guido Caldarelli & Stefano Battiston, 2020. "Network valuation in financial systems," Mathematical Finance, Wiley Blackwell, vol. 30(4), pages 1181-1204, October.
    2. Gandy, Axel & Veraart, Luitgard A. M., 2021. "Compound poisson models for weighted networks with applications in finance," LSE Research Online Documents on Economics 104185, London School of Economics and Political Science, LSE Library.
    3. Chen, Yu & Jin, Shuyue & Wang, Xiasi, 2021. "Solvency contagion risk in the Chinese commercial banks’ network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    4. Sonin, Konstantin & Sonin, Isaac, 2020. "A Continuous-Time Model of Financial Clearing," CEPR Discussion Papers 15117, C.E.P.R. Discussion Papers.
    5. Li, Jiaqi, 2023. "Predicting the demand for central bank digital currency: A structural analysis with survey data," Journal of Monetary Economics, Elsevier, vol. 134(C), pages 73-85.

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    More about this item

    Keywords

    systemic risk; contagion; financial networks; stress testing; mark-to-market losses;
    All these keywords.

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • 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
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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