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A Portfolio Optimization Approach Using Combinatorics With A Genetic Algorithm For Developing A Reinsurance Model

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Journal of Risk & Insurance

Published online on

Abstract

Some insurance firms challenged with a portfolio of high‐variance risks face the classic trade‐off between risk spreading and risk retaining. Using crop insurance as an example, a new solution to this problem is undertaken to uncover an improved reinsurance design. Joint self‐managed reinsurance pooling and private reinsurance are combined in a portfolio approach utilizing combinatorial optimization with a genetic algorithm (Model C), achieving high surplus, high survival probability, and low deficit at ruin. This portfolio model may also be useful for other large natural disaster and weather‐related insurance portfolios, and other portfolio applications.