Description: This is the abstract of a paper that complements the existing research on optimal reinsurance by proposing another model for the determination of the optimal reinsurance design.

Description: The theme of this paper relates to solving portfolio selection problems using linear programming. The authors extend the linear optimization framework for Conditional Value-at-Risk-based portfolio selection problems to optimization over a more general class of risk measure known as the class of Coherent Distortion Risk Measure. From Actuarial Research Clearing House, 2012 Vol. 1.

Description: It is well-known that reinsurance can be an effective risk management technique for an insurer. An appropriate use of reinsurance reduces the adverse risk exposure of an insurer and improves the overall viability of the underlying business. The use of reinsurance, on the other hand, incurs additional cost to the insurer in the form of reinsurance premium. This implies that an insurer is faced with a classic tradeoff between risk spreading and risk retaining. The thrust of my research is to propose some reinsurance designs that are optimal from the perspective of an insurer. This presentation describes an empirical approach to optimal reinsurance designs. This new method has the advantage that it does not need to make any explicit assumptions on the distribution of the underling risk. More importantly, it provides a simple and yet practical way of obtaining solution on a wide range of optimal reinsurance models.

Description: The theme of this presentation relates to solving portfolio selection problems using linear and fractional programming. Two key contributions: 1. Generalization of the CVaR linear optimization framework. 2. Equivalences among four formulations of Coherent Distortion Risk Mearures optimization problems. From Actuarial Research Clearing House, 2012, Vol. 1.