A Portfolio optimization approach using combinatorics with a genetic algorithm for developing a reinsurance model

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      <subfield code="a">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</subfield>
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