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Title: | Combining a matheuristic with simulation for risk management of stochastic assets and liabilities |
Author: | bayliss, christopher Serra Plomer, Martí Nieto Ranero, Armando Miguel Juan, Angel A. |
Others: | Universitat Oberta de Catalunya (UOC) Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3) University of Liverpool Divina Pastora Seguros |
Citation: | 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 |
Abstract: | 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. |
Keywords: | assets and liabilities management risk management uncertainty matheuristics simulation |
DOI: | 10.3390/risks8040131 |
Document type: | info:eu-repo/semantics/article |
Version: | info:eu-repo/semantics/publishedVersion |
Issue Date: | 4-Dec-2020 |
Publication license: | http://creativecommons.org/licenses/by/3.0/es/ |
Appears in Collections: | Articles cientÍfics Articles |
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