Optimal Reinsurance through Minimizing New Risk Measures under Technical Benefit Constraints

Abstract:

In this paper we present an approach to minimize the actuarial risk for the optimal choice of a form of reinsurance, and this is intended to be through a choice of treated parameters that minimize the risk using the Conditional Tail Expectation and the Conditional Tail Variance risk measures. The minimization procedure is based on the Augmented Lagrangian and a genetic algorithm with technical benefit as a constraint. This approach can be seen as a decision support tool that can be used by managers to minimize the actuarial risk in the insurance company.

• Periodical: International Journal of Engineering Research in Africa (Volume 35)
• Pages: 24-37
• DOI: https://doi.org/10.4028/www.scientific.net/JERA.35.24
• Online since: March 2018
• Authors: Abderrahim El Attar*, Mostafa El Hachloufi, Zine El Abidine Guennoun
• Keywords: Augmented Lagrangian, Conditional Tail Expectation, Conditional Tail Variance, Genetic Algorithms, Premium Principle, Reinsurance, Technical Benefit

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