Artikel
Combining a matheuristic with simulation for risk management of stochastic assets and liabilities
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.
- Sprache
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Englisch
- Erschienen in
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Journal: Risks ; ISSN: 2227-9091 ; Volume: 8 ; Year: 2020 ; Issue: 4 ; Pages: 1-14 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
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assets and liabilities management
risk management
uncertainty
matheuristics
simulation
- Ereignis
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Geistige Schöpfung
- (wer)
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Bayliss, Christopher
Serra, Marti
Nieto, Armando
Juan, Angel A.
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
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Basel
- (wann)
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2020
- DOI
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doi:10.3390/risks8040131
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:42 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Bayliss, Christopher
- Serra, Marti
- Nieto, Armando
- Juan, Angel A.
- MDPI
Entstanden
- 2020