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Systematic stress tests on public data

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  • Breuer, Thomas
  • Summer, Martin

Abstract

For a given set of banks, how big can losses in bad economic or financial scenarios possibly get, and what are these bad scenarios? These are the two central questions of stress tests for banks and the banking system. Current stress tests select stress scenarios in a way which might leave aside many dangerous scenarios and thus create an illusion of safety; and which might consider highly implausible scenarios and thus trigger a false alarm. We show how to select scenarios systematically for a banking system in a context of multiple credit exposures. We demonstrate the application of our method in an example on the Spanish and Italian residential real estate exposures of European banks. Compared to the EBA 2016 stress test our method produces scenarios which are equally plausible as the EBA stress scenario but yield considerably worse system wide losses.

Suggested Citation

  • Breuer, Thomas & Summer, Martin, 2020. "Systematic stress tests on public data," Journal of Banking & Finance, Elsevier, vol. 118(C).
  • Handle: RePEc:eee:jbfina:v:118:y:2020:i:c:s0378426620301527
    DOI: 10.1016/j.jbankfin.2020.105886
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    References listed on IDEAS

    as
    1. Breuer, Thomas & Csiszár, Imre, 2013. "Systematic stress tests with entropic plausibility constraints," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1552-1559.
    2. Paul Glasserman & Chulmin Kang & Wanmo Kang, 2015. "Stress scenario selection by empirical likelihood," Quantitative Finance, Taylor & Francis Journals, vol. 15(1), pages 25-41, January.
    3. Thomas Breuer & Imre Csiszár, 2016. "Measuring Distribution Model Risk," Mathematical Finance, Wiley Blackwell, vol. 26(2), pages 395-411, April.
    4. Mark D. Flood & George G. Korenko, 2015. "Systematic scenario selection: stress testing and the nature of uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 15(1), pages 43-59, January.
    5. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
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    Cited by:

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    2. Bonucchi, Manuel & Catalano, Michele, 2022. "How severe are the EBA macroeconomic scenarios for the Italian Economy? A joint probability approach," Journal of International Money and Finance, Elsevier, vol. 129(C).
    3. Zachary Feinstein, 2022. "Continuity and sensitivity analysis of parameterized Nash games," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 10(2), pages 233-249, October.

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    More about this item

    Keywords

    Stress testing; Risk measures; Scenario analysis; Systemic risk;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • M48 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Government Policy and Regulation

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