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The Nexus Between Systemic Risk and Sovereign Crises

Author

Listed:
  • Tomas Klinger

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague)

  • Petr Teply

    (Faculty of Finance and Accounting, University of Economics in Prague)

Abstract

This paper focuses on the relationship between the financial system and sovereign debt crises by analyzing sovereign support to banks and banks’ resulting exposure to the bonds issued by weak sovereigns. We construct an agent-based network model of an artificial financial system allowing us to analyze the effects of state support on systemic stability and the feedback loops of risk transfer back into the financial system. The model is tested with various parameter settings in Monte Carlo simulations. Our analyses yield the following key results: first, in the short term, all the support measures improve systemic stability. Second, in the longer run, there are settings which mitigate the systemic crisis and settings which contribute to systemic breakdown. Finally, there are differences among the effects of the different types of support measures. While bailouts and recapitalization are the most efficient types of support type and execution of guarantees is still a viable solution, the results of liqu idity measures such as asset relief or provision of funding liquidity are significantly worse.

Suggested Citation

  • Tomas Klinger & Petr Teply, 2016. "The Nexus Between Systemic Risk and Sovereign Crises," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(1), pages 50-69, February.
    • Handle: RePEc:fau:fauart:v:66:y:2016:i:1:p:50-69
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    Citations

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    Cited by:

    1. Jan Brůha & Evžen Kočenda, 2018. "Bankovní sektor a státní riziko v Evropské unii [Banking Sector and Sovereign Risk in Euroepan Union]," Politická ekonomie, Prague University of Economics and Business, vol. 2018(3), pages 366-383.
    2. Janda, Karel & Kravtsov, Oleg, 2016. "Interdependencies between Leverage and Capital Ratios in the Banking Sector of the Czech Republic," MPRA Paper 74457, University Library of Munich, Germany.
    3. Karel Janda & Oleg Kravtsov, 2018. "Basel III Leverage and Capital Ratio over the Economic Cycle in the Czech Republic and its Comparison with the CEE Region," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2018(4), pages 5-23.
    4. Brůha, Jan & Kočenda, Evžen, 2018. "Financial stability in Europe: Banking and sovereign risk," Journal of Financial Stability, Elsevier, vol. 36(C), pages 305-321.
    5. Tomas Klinger & Petr Teply, 2017. "Agent-Based Risk Assessment Model of the European Banking Network," CERGE-EI Working Papers wp602, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    6. Janda, Karel & Kravtsov, Oleg, 2016. "Interdependencies between Leverage and Capital Ratios in the Central and Eastern European Banks," MPRA Paper 74560, University Library of Munich, Germany.
    7. 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.
    8. Jovan Njegic & Milica Stankovic & Dejan Živkov, 2019. "What Wavelet-Based Quantiles Can Suggest about the Stocks-Bond Interaction in the Emerging East Asian Economies?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(1), pages 95-119, February.
    9. Gomez-Puig, Marta & Singh, Manish K. & Sosvilla-Rivero, Simon, 2019. "The sovereign-bank nexus in peripheral euro area: Further evidence from contingent claims analysis," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 1-26.
    10. Teply, Petr & Kvapilikova, Ivana, 2017. "Measuring systemic risk of the US banking sector in time-frequency domain," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 461-472.

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    More about this item

    Keywords

    agent-based models; bailout; contagion; financial stability; network models; state support; 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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