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Systematic scenario selection: stress testing and the nature of uncertainty

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  • Mark D. Flood
  • George G. Korenko

Abstract

We present a technique for selecting multidimensional shock scenarios for use in financial stress testing. The methodology systematically enforces internal consistency among the shock dimensions by sampling points of arbitrary severity from a plausible joint probability distribution. The approach involves a grid search of sparse, well distributed, stress-test scenarios, which we regard as a middle ground between traditional stress testing and reverse stress testing. Choosing scenarios in this way reduces the danger of 'blind spots' in stress testing. We suggest extensions to address the issues of non-monotonic loss functions and univariate shocks. We provide tested and commented source code in Matlab-super-®.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:1:p:43-59
    DOI: 10.1080/14697688.2014.926018
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    References listed on IDEAS

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    1. Bookstaber, Rick & Cetina, Jill & Feldberg, Greg & Flood, Mark & Glasserman, Paul, 2013. "Stress tests to promote financial stability: Assessing progress and looking to the future," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 7(1), pages 16-25, December.
    2. Borio, Claudio & Drehmann, Mathias & Tsatsaronis, Kostas, 2014. "Stress-testing macro stress testing: Does it live up to expectations?," Journal of Financial Stability, Elsevier, vol. 12(C), pages 3-15.
    3. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
    4. Mr. Paul Louis Ceriel Hilbers & Mr. Matthew T Jones & Mr. Graham L Slack, 2004. "Stress Testing Financial Systems: What to Do When the Governor Calls," IMF Working Papers 2004/127, International Monetary Fund.
    5. Paul Glasserman & Chulmin Kang & Wanmo Kang, 2013. "Stress Scenario Selection by Empirical Likelihood," Working Papers 13-04, Office of Financial Research, US Department of the Treasury.
    6. Maria Soledad Martinez Peria & Mr. Giovanni Majnoni & Mr. Matthew T Jones & Mr. Winfrid Blaschke, 2001. "Stress Testing of Financial Systems: An Overview of Issues, Methodologies, and FSAP Experiences," IMF Working Papers 2001/088, International Monetary Fund.
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    Cited by:

    1. Daniel Grigat & Fabio Caccioli, 2017. "Reverse stress testing interbank networks," Papers 1702.08744, arXiv.org, revised Mar 2017.
    2. Günter Franke, 2020. "Management nicht-finanzieller Risiken: eine Forschungsagenda [Management of Non-Financial Risks: A Research Agenda]," Schmalenbach Journal of Business Research, Springer, vol. 72(3), pages 279-320, September.
    3. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.
    4. Packham, Natalie & Woebbeking, Fabian, 2021. "Correlation scenarios and correlation stress testing," IRTG 1792 Discussion Papers 2021-012, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. N. Packham & F. Woebbeking, 2021. "Correlation scenarios and correlation stress testing," Papers 2107.06839, arXiv.org, revised Sep 2022.
    7. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean–variance efficient large portfolios: a simple machine learning heuristic technique based on the two-fund separation theorem," Annals of Operations Research, Springer, vol. 334(1), pages 133-155, March.
    8. Breuer, Thomas & Summer, Martin, 2020. "Systematic stress tests on public data," Journal of Banking & Finance, Elsevier, vol. 118(C).
    9. Giuseppe Montesi & Giovanni Papiro & Massimiliano Fazzini & Alessandro Ronga, 2020. "Stochastic Optimization System for Bank Reverse Stress Testing," JRFM, MDPI, vol. 13(8), pages 1-44, August.
    10. Peter Grundke & Kamil Pliszka, 2018. "A macroeconomic reverse stress test," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1093-1130, May.
    11. Paul Glasserman & Mike Li, 2022. "Should Bank Stress Tests Be Fair?," Papers 2207.13319, arXiv.org, revised May 2023.
    12. Michel Baes & Eric Schaanning, 2023. "Reverse stress testing: Scenario design for macroprudential stress tests," Mathematical Finance, Wiley Blackwell, vol. 33(2), pages 209-256, April.
    13. Pliszka, Kamil, 2021. "System-wide and banks' internal stress tests: Regulatory requirements and literature review," Discussion Papers 19/2021, Deutsche Bundesbank.
    14. Packham, N. & Woebbeking, F., 2023. "Correlation scenarios and correlation stress testing," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 55-67.
    15. Jingnan Chen & Mark D. Flood & Richard B. Sowers, 2015. "Measuring the Unmeasurable: An Application of Uncertainty Quantification to Financial Portfolios," Working Papers 15-19, Office of Financial Research, US Department of the Treasury.
    16. Levy-Carciente, Sary & Kenett, Dror Y. & Avakian, Adam & Stanley, H. Eugene & Havlin, Shlomo, 2015. "Dynamical macroprudential stress testing using network theory," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 164-181.
    17. Dror Y. Kenett & Sary Levy-Carciente & Adam Avakian & H. Eugene Stanley & Shlomo Havlin, 2015. "Dynamical Macroprudential Stress Testing Using Network Theory," Working Papers 15-12, Office of Financial Research, US Department of the Treasury.
    18. Seabrook, Isobel & Caccioli, Fabio & Aste, Tomaso, 2022. "Quantifying impact and response in markets using information filtering networks," LSE Research Online Documents on Economics 115308, London School of Economics and Political Science, LSE Library.
    19. Thomas Breuer & Martin Summer, 2018. "Systematic Systemic Stress Tests," Working Papers 225, Oesterreichische Nationalbank (Austrian Central Bank).
    20. Aikman, David & Angotti, Romain & Budnik, Katarzyna, 2024. "Stress testing with multiple scenarios: a tale on tails and reverse stress scenarios," Working Paper Series 2941, European Central Bank.
    21. Pritsker, Matt, 2019. "An overview of regulatory stress-testing and steps to improve it," Global Finance Journal, Elsevier, vol. 39(C), pages 39-43.
    22. Packham, N. & Woebbeking, C.F., 2019. "A factor-model approach for correlation scenarios and correlation stress testing," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 92-103.
    23. Natalie Packham & Fabian Woebbeking, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," Papers 1807.11381, arXiv.org, revised Jan 2019.

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