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Quantitative Reverse Stress Testing, Bottom Up

Author

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  • Claudio Albanese
  • Stéphane Crépey

    (UFR Mathématiques UPCité - UFR Mathématiques [Sciences] - Université Paris Cité - UPCité - Université Paris Cité)

  • 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. We find that such an 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, 2022. "Quantitative Reverse Stress Testing, Bottom Up," Working Papers hal-03910136, HAL.
    • Handle: RePEc:hal:wpaper:hal-03910136
    Note: View the original document on HAL open archive server: https://hal.science/hal-03910136v1
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    References listed on IDEAS

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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.
    2. 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.
    3. 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.
    4. 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.
    5. Tak Siu & Howell Tong & Hailiang Yang, 2004. "On Bayesian Value at Risk: From Linear to Non-Linear Portfolios," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 11(2), pages 161-184, June.
    6. Hull, John & White, Alan, 1990. "Pricing Interest-Rate-Derivative Securities," The Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 573-592.
    7. 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.
    8. 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.
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