CDF formulation for solving an optimal reinsurance problem |
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Authors: | Chengguo Weng Sheng Chao Zhuang |
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Affiliation: | Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada. |
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Abstract: | An innovative cumulative distribution function (CDF)-based method is proposed for deriving optimal reinsurance contracts to maximize an insurer’s survival probability. The optimal reinsurance model is a non-concave constrained stochastic maximization problem, and the CDF-based method transforms it into a functional concave programming problem of determining an optimal CDF over a corresponding feasible set. Compared to the existing literature, our proposed CDF formulation provides a more transparent derivation of the optimal solutions, and more interestingly, it enables us to study a further complex model with an extra background risk and more sophisticated premium principle. |
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Keywords: | CDF formulation Lagrangian dual method optimal reinsurance survival probability maximization background risk generalized Wang’s premium principle |
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