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Quantitative reverse stress testing, bottom up

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  • Claudio Albanese
  • Stéphane Crépey
  • Stefano Iabichino

Abstract

We propose a bottom-up quantitative reverse stress testing framework that identifies forward-looking fragilities tailored to a bank's portfolio, credit and funding strategies, models, and calibration constraints. Thus, instead of relying on historical events, we run a Monte Carlo simulation, and we mine those future states that contribute the most to a bank's cost of capital expressed in terms of scenario differential. This approach allows identifying both the systemic and idiosyncratic weaknesses of the bank's portfolio, with applications that include solvency risk, extreme events hedging, liquidity risk management, trading and credit limits, model validation and model risk management.

Suggested Citation

  • Claudio Albanese & Stéphane Crépey & Stefano Iabichino, 2023. "Quantitative reverse stress testing, bottom up," Quantitative Finance, Taylor & Francis Journals, vol. 23(5), pages 863-875, May.
    • Handle: RePEc:taf:quantf:v:23:y:2023:i:5:p:863-875
    DOI: 10.1080/14697688.2023.2187315
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    1. Peter Grundke & Kamil Pliszka, 2018. "A macroeconomic reverse stress test," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1093-1130, May.
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    4. Giuseppe Montesi & Giovanni Papiro, 2018. "Bank Stress Testing: A Stochastic Simulation Framework to Assess Banks’ Financial Fragility †," Risks, MDPI, vol. 6(3), pages 1-54, August.
    5. Claudio Albanese & Stéphane Crépey & Rodney Hoskinson & Bouazza Saadeddine, 2021. "XVA analysis from the balance sheet," Quantitative Finance, Taylor & Francis Journals, vol. 21(1), pages 99-123, January.
    6. Albanese, Claudio & Vidler, Alicia, 2007. "A STRUCTURAL MODEL FOR CREDIT-EQUITY DERIVATIVES AND BESPOKE CDOs," MPRA Paper 5227, University Library of Munich, Germany, revised 09 Sep 2007.
    7. Claudio Albanese & Toufik Bellaj & Guillaume Gimonet & Giacomo Pietronero, 2011. "Coherent global market simulations and securitization measures for counterparty credit risk," Quantitative Finance, Taylor & Francis Journals, vol. 11(1), pages 1-20.
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