Default Resilience and Worst-Case Effects in Financial Networks
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| Format: | Preprint |
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2024
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| author | Calafiore, Giuseppe Fracastoro, Giulia Proskurnikov, Anton |
| author_facet | Calafiore, Giuseppe Fracastoro, Giulia Proskurnikov, Anton |
| contents | In this paper we analyze the resilience of a network of banks to joint price fluctuations of the external assets in which they have shared exposures, and evaluate the worst-case effects of the possible default contagion. Indeed, when the prices of certain external assets either decrease or increase, all banks exposed to them experience varying degrees of simultaneous shocks to their balance sheets. These coordinated and structured shocks have the potential to exacerbate the likelihood of defaults. In this context, we introduce first a concept of {default resilience margin}, $ε^*$, i.e., the maximum amplitude of asset prices fluctuations that the network can tolerate without generating defaults. Such threshold value is computed by considering two different measures of price fluctuations, one based on the maximum individual variation of each asset, and the other based on the sum of all the asset's absolute variations. For any price perturbation having amplitude no larger than $ε^*$, the network absorbs the shocks remaining default free. When the perturbation amplitude goes beyond $ε^*$, however, defaults may occur. In this case we find the worst-case systemic loss, that is, the total unpaid debt under the most severe price variation of given magnitude. Computation of both the threshold level $ε^*$ and of the worst-case loss and of a corresponding worst-case asset price scenario, amounts to solving suitable linear programming problems.} |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2403_10631 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Default Resilience and Worst-Case Effects in Financial Networks Calafiore, Giuseppe Fracastoro, Giulia Proskurnikov, Anton Risk Management Computational Engineering, Finance, and Science Optimization and Control Mathematical Finance In this paper we analyze the resilience of a network of banks to joint price fluctuations of the external assets in which they have shared exposures, and evaluate the worst-case effects of the possible default contagion. Indeed, when the prices of certain external assets either decrease or increase, all banks exposed to them experience varying degrees of simultaneous shocks to their balance sheets. These coordinated and structured shocks have the potential to exacerbate the likelihood of defaults. In this context, we introduce first a concept of {default resilience margin}, $ε^*$, i.e., the maximum amplitude of asset prices fluctuations that the network can tolerate without generating defaults. Such threshold value is computed by considering two different measures of price fluctuations, one based on the maximum individual variation of each asset, and the other based on the sum of all the asset's absolute variations. For any price perturbation having amplitude no larger than $ε^*$, the network absorbs the shocks remaining default free. When the perturbation amplitude goes beyond $ε^*$, however, defaults may occur. In this case we find the worst-case systemic loss, that is, the total unpaid debt under the most severe price variation of given magnitude. Computation of both the threshold level $ε^*$ and of the worst-case loss and of a corresponding worst-case asset price scenario, amounts to solving suitable linear programming problems.} |
| title | Default Resilience and Worst-Case Effects in Financial Networks |
| topic | Risk Management Computational Engineering, Finance, and Science Optimization and Control Mathematical Finance |
| url | https://arxiv.org/abs/2403.10631 |