Optimal Reinsurance With Random Inflation Rate Under VaR Risk Measures

In this paper, the mixture reinsurance model with random inflation rate under VaRrisk measures is considered. According to this model, the expression of VaR andoptimal reinsurance strategy is discussed in this article. The result enriches thereinsurance research, provides theoretical basis for the practical application ofreinsurance business and promotes the development of insurance and reinsurance.Firstly, this paper presents the development history of the reinsurance, the researchstatus of reinsurance, VaR risk measures and premium principle. These basics makesthe reader have a preliminary understanding of reinsurance.Then we discuss theexpression of VaR based on mixture reinsurance model with random inflation rate.Secondly, Some important research results related to this article under the VaR riskmessures is given. Including optimal amount of retention based on stop-loss reinsuranceand optimal proportion of retention based on the proportional reinsurance. In theinsurance business, the most important thing is to study the proportion of retention andretention. Thus it is easy to share responsibility between the insurance companies andreinsurance companies and provide a theoretical basis for the distribution of profits.This study was carried out under the VaR risk measures. Based on the existingresearch results, mixture reinsurance with random inflation rate is study. According tothe expression of mixture reinsurance model with random inflation rate under VaR riskmeasures, optimal self-retention amount and VaR optimal value when the proportion isknown is calculated by using of expectations premium principles. Then optimalself-retention amount VaR optimal value when the proportion is known is calculated byusing of variance premium principle. Optimal self-retention proportion and VaR optimalvalue when the amount is known is given by using of variance premium principle. Inthe final, assume the random inflation rate is fixed number, then the correspondingverifications are given after corresponding theorem and inference. The correspondingverifications describe the accuracy of the results and the breadth scope.