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报告时间：2022年11月9日下午14:00

报告地点：经管楼A927

Title：Robust reinsurance contract with asymmetric information in a stochastic Stackelberg differential Game

Abstract：In this paper, we determine a robust reinsurance contract from joint interests of the insurer and reinsurer under the framework of Stackelberg differential game. More specifically, the reinsurer is the leader of the game and decides on an optimal reinsurance premium to charge, while the insurer is the follower of the game and chooses an optimal proportional reinsurance to purchase. In order to defend the large shocks of wealth process, a loss-dependent premium principle is applied to the insurer.Meanwhile,we incorporate model uncertainty into the reinsurer’s controlled surplus due to the asymmetric information. Under the time-consistent mean-variance criterion, we derive the robust reinsurance contract explicitly by solving the coupled extended Hamilton–Jacobi–Bellman systems. It is interesting to prove that the optimal premium control for the reinsurer is determined by a time-adjusted variance principle. In addition, we find that the reinsurer would like to raise the reinsurance price to guard against the model uncertainty, which consequently decreases the insurer’s reinsurance demand. Finally, further analyses are provided to show the necessity of considering the model uncertainty; otherwise, the reinsurance company will suffer a great loss of utility.

报告人简介： 梁志彬，博士，南京师范大学数学科学学院教授，博士生导师。主要研究方向：风险管理与精算，数理金融与定价，随机最优风险控制。目前感兴趣的研究领域是：金融保险市场不确定环境下的博弈与优化；机器学习算法下的量化投资与随机最优控制。近年来，在SAJ，IME，AMO等数理金融与精算以及优化相关期刊发表学术论文40余篇，主持和完成国家自然科学基金项目以及省部级基金项目多项。2008年以来，先后访问过英国LondonImperialCollege的Tanaka商学院；美国UniversityofMichigan的数学系（先后三年半）；加拿大ConcordiaUniversity的数学与统计系；美国北卡州立大学数学系；以及多次访问香港大学的统计与精算系等。目前是国家自然科学基金委员会数理科学部的网上通讯评议专家，以及教育部学位中心网上通讯评议专家。同时，担任中国现场统计研究会风险管理与精算分会理事会理事，双法研究会量化金融与保险分会理事，江苏省统计学会理事。