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http://hdl.handle.net/10609/127050
Títol: | Combining a matheuristic with simulation for risk management of stochastic assets and liabilities |
Autoria: | bayliss, christopher Serra Plomer, Martí Nieto Ranero, Armando Miguel Juan, Angel A. |
Altres: | Universitat Oberta de Catalunya (UOC) Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3) University of Liverpool Divina Pastora Seguros |
Citació: | Bayliss, C., Serra, M., Nieto. A., Juan, A. A.(2020). Combining a matheuristic with simulation for Risk management of stochastic assets and liabilities. Risks, 8(4). pág. 1-14. doi: 10.3390/risks8040131 |
Resum: | Specially in the case of scenarios under uncertainty, the efficient management of risk when matching assets and liabilities is a relevant issue for most insurance companies. This paper considers such a scenario, where different assets can be aggregated to better match a liability (or the other way around), and the goal is to find the asset-liability assignments that maximises the overall benefit over a time horizon. To solve this stochastic optimisation problem, a simulation-optimisation methodology is proposed. We use integer programming to generate efficient asset-to-liability assignments, and Monte-Carlo simulation is employed to estimate the risk of failing to pay due liabilities. The simulation results allow us to set a safety margin parameter for the integer program, which encourage the generation of solutions satisfying a minimum reliability threshold. A series of computational experiments contribute to illustrate the proposed methodology and its utility in practical risk management. |
Paraules clau: | gestió d'actius i passius gestió de riscos incertesa matemàtiques simulació |
DOI: | 10.3390/risks8040131 |
Tipus de document: | info:eu-repo/semantics/article |
Versió del document: | info:eu-repo/semantics/publishedVersion |
Data de publicació: | 4-des-2020 |
Llicència de publicació: | http://creativecommons.org/licenses/by/3.0/es/ |
Apareix a les col·leccions: | Articles cientÍfics Articles |
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Arxiu | Descripció | Mida | Format | |
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risks-08-00131.pdf | 474,13 kB | Adobe PDF | Veure/Obrir |
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