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Bank Stress Testing: A Stochastic Simulation Framework to Assess Banks’ Financial Fragility †

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  • Giuseppe Montesi

    (School of Economics and Management, University of Siena, 53100 Siena, Italy)

  • Giovanni Papiro

    (School of Economics and Management, University of Siena, 53100 Siena, Italy)

Abstract

We present a stochastic simulation forecasting model for stress testing that is aimed at assessing banks’ capital adequacy, financial fragility, and probability of default. The paper provides a theoretical presentation of the methodology and the essential features of the forecasting model on which it is based. Also, for illustrative purposes and to show in practical terms how to apply the methodology and the types of outcomes and analysis that can be obtained, we report the results of an empirical application of the methodology proposed to the Global Systemically Important Banks (G-SIB) banks. The results of the stress test exercise are compared with the results of the supervisory stress tests performed in 2014 by the Federal Reserve and EBA/ECB.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jrisks:v:6:y:2018:i:3:p:82-:d:164289
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    Cited by:

    1. Robert J. Powell & Duc H. Vo, 2020. "A Comprehensive Stability Indicator for Banks," Risks, MDPI, vol. 8(1), pages 1-15, February.
    2. 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.
    3. 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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