Quantitative Reverse Stress Testing, Bottom Up

Claudio Albanese, Stéphane Crépey () and Stefano Iabichino
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Stéphane Crépey: UFR Mathématiques UPCité - UFR Mathématiques [Sciences] - Université Paris Cité - UPCité - Université Paris Cité

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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.

Keywords: quantitative reverse stress testing cost of capital (KVA) model validation model risk trading limits PFE JEL Classification: D81 G13 G28 G32 Mathematics Subject Classification: 91B30 91G20 91G30 91G40; quantitative reverse stress testing; cost of capital (KVA); model validation; model risk; trading limits; PFE (search for similar items in EconPapers)
Date: 2022-12-21
New Economics Papers: this item is included in nep-ban and nep-rmg
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