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CDF formulation for solving an optimal reinsurance problem
Authors:Chengguo Weng  Sheng Chao Zhuang
Affiliation:Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada.
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.
Keywords:CDF formulation  Lagrangian dual method  optimal reinsurance  survival probability maximization  background risk  generalized Wang’s premium principle
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