基于RORAC和MSD的多目标最优比例再保险

Multi-Objective Optimal Proportional Reinsurance Based on RORAC and MSD

本文引入金融行业在风险管理和绩效评估等方面所常用的指标——风险调整资本收益率(RORAC),以及单位标准差收益(MSD),在资本约束范围内与条件风险价值(CVaR)建立多目标模型。在期望保费原理下,考虑扩散逼近风险模型中基于RORAC和MSD,以及CVaR的最优比例再保险问题。利用多目标优化理论,我们得到了比例再保险的Pareto最优解。最后,通过数值举例,探讨了初始资本水平,保险年度以及风险喜恶对最优再保险策略的影响。

In this paper, based on some indexes which are always used in risk management and performance appraisals for financial industry, such as return on risk adjusted capital (RORAC) and mean-standard deviation (MSD), we construct two multi-objective optimization models together with conditional value at risk (CVaR) as well as the capital regulation. Under the expected value premium principle, by the multi-objective optimization theory, we obtain the Pareto optimal proportional reinsurance strategy for the diffusion approximation risk model. Some numerical examples are given to show the impact of some important parameters, like initial capital and insurance year as well as risk aversion, on the optimal reinsurance strategy.