A unifying approach to constrained and unconstrained optimal reinsurance.

In this paper, we study two classes of optimal reinsurance models from perspectives of both insurers and reinsurers by minimizing their convex combination of the total losses where the risk is measured by a distortion risk measure and the reinsurance premium is calculated according to a distortion premium principle. In the first place, we show how to formulate the unconstrained optimization problem and constrained optimization problem in a unified way. Then, we propose a geometric approach to solve optimal reinsurance problems directly. This paper considers a class of increasing convex ceded loss functions and derives the explicit solutions of the optimal reinsurance, which can be in forms of quota-share, stop-loss, change-loss, the combination of quota-share and change-loss or the combination of change-loss and change-loss with different retentions. Finally, we consider two specific cases of the distortion risk measures: Value at Risk (VaR) and Tail Value at Risk (TVaR). [ABSTRACT FROM AUTHOR]