Measuring Financial Resilience Using Backward Stochastic Differential Equations

Fuente: arXiv
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Autori principali: Laeven, Roger J. A., Ferrari, Matteo, Gianin, Emanuela Rosazza, Zullino, Marco
Natura: Preprint
Pubblicazione: 2025
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author Laeven, Roger J. A.
Ferrari, Matteo
Gianin, Emanuela Rosazza
Zullino, Marco
author_facet Laeven, Roger J. A.
Ferrari, Matteo
Gianin, Emanuela Rosazza
Zullino, Marco
contents We introduce the resilience rate as a measure of financial resilience. It captures the expected rate at which a dynamic risk measure recovers, i.e., bounces back, when the risk-acceptance set is breached. We develop the corresponding stochastic calculus by establishing representation theorems for expected time-derivatives of solutions to backward stochastic differential equations (BSDEs) with jumps, evaluated at stopping times. These results reveal that the resilience rate can be represented as a suitable expectation of the generator of a BSDE. We analyze the main properties of the resilience rate and the formal connection of these properties to the BSDE generator. We also introduce resilience-acceptance sets and study their properties in relation to both the resilience rate and the dynamic risk measure. We illustrate our results in several canonical financial examples and highlight their implications via the notion of resilience neutrality.
format Preprint
id arxiv_https___arxiv_org_abs_2505_07502
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Measuring Financial Resilience Using Backward Stochastic Differential Equations
Laeven, Roger J. A.
Ferrari, Matteo
Gianin, Emanuela Rosazza
Zullino, Marco
Mathematical Finance
Probability
Risk Management
60H10, 60H30, 91B06, 91B30, 62P05
We introduce the resilience rate as a measure of financial resilience. It captures the expected rate at which a dynamic risk measure recovers, i.e., bounces back, when the risk-acceptance set is breached. We develop the corresponding stochastic calculus by establishing representation theorems for expected time-derivatives of solutions to backward stochastic differential equations (BSDEs) with jumps, evaluated at stopping times. These results reveal that the resilience rate can be represented as a suitable expectation of the generator of a BSDE. We analyze the main properties of the resilience rate and the formal connection of these properties to the BSDE generator. We also introduce resilience-acceptance sets and study their properties in relation to both the resilience rate and the dynamic risk measure. We illustrate our results in several canonical financial examples and highlight their implications via the notion of resilience neutrality.
title Measuring Financial Resilience Using Backward Stochastic Differential Equations
topic Mathematical Finance
Probability
Risk Management
60H10, 60H30, 91B06, 91B30, 62P05
url https://arxiv.org/abs/2505.07502