Systemic values-at-risk and their sample-average approximations

Fuente: arXiv
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Main Authors: AlAli, Wissam, Ararat, Çağın
Format: Preprint
Published: 2024
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author AlAli, Wissam
Ararat, Çağın
author_facet AlAli, Wissam
Ararat, Çağın
contents This paper investigates the convergence properties of sample-average approximations (SAA) for set-valued systemic risk measures. We assume that the systemic risk measure is defined using a general aggregation function with some continuity properties and value-at-risk applied as a monetary risk measure. We focus on the theoretical convergence of its SAA under Wijsman and Hausdorff topologies for closed sets. After building the general theory, we provide an in-depth study of an important special case where the aggregation function is defined based on the Eisenberg-Noe network model. In this case, we provide mixed-integer programming formulations for calculating the SAA sets via their weighted-sum and norm-minimizing scalarizations. To demonstrate the applicability of our findings, we conduct a comprehensive sensitivity analysis by generating a financial network based on the preferential attachment model and modeling the economic disruptions via a Pareto distribution.
format Preprint
id arxiv_https___arxiv_org_abs_2408_08511
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Systemic values-at-risk and their sample-average approximations
AlAli, Wissam
Ararat, Çağın
Risk Management
Optimization and Control
Probability
26E25, 90C29, 91G45, 91G70
This paper investigates the convergence properties of sample-average approximations (SAA) for set-valued systemic risk measures. We assume that the systemic risk measure is defined using a general aggregation function with some continuity properties and value-at-risk applied as a monetary risk measure. We focus on the theoretical convergence of its SAA under Wijsman and Hausdorff topologies for closed sets. After building the general theory, we provide an in-depth study of an important special case where the aggregation function is defined based on the Eisenberg-Noe network model. In this case, we provide mixed-integer programming formulations for calculating the SAA sets via their weighted-sum and norm-minimizing scalarizations. To demonstrate the applicability of our findings, we conduct a comprehensive sensitivity analysis by generating a financial network based on the preferential attachment model and modeling the economic disruptions via a Pareto distribution.
title Systemic values-at-risk and their sample-average approximations
topic Risk Management
Optimization and Control
Probability
26E25, 90C29, 91G45, 91G70
url https://arxiv.org/abs/2408.08511