报告一：南开大学李津竹教授学术报告

报告时间：2024年11月22日 16：10-17：10

报告地点：统计与数据科学学院会议室109

题目：Asymptotic Results on Tail Moment for Light-tailed Risks

摘要：In this talk, we focus on the asymptotic behavior of a recently popular risk measure called the tail moment (TM), which has been extensively applied in the field of risk theory. We conduct the study under the framework in which the individual risks of a financial or insurance system follow convolution equivalent or Gamma-like distributions. Precise asymptotic results are obtained for the TM when the individual risks are mutually independent or have a dependence structure of the Farlie-Gumbel-Morgenstern type. Moreover, based on some specific scenarios, we give an asymptotic analysis on the relative errors between our asymptotic results and the corresponding exact values. Since the model settings in this paper are not covered by traditional ones, our work fills in some gaps of the asymptotic study of the TM for light-tailed risks.

报告人简介：李津竹，南开大学数学科学学院教授，博士生导师，主要从事随机过程及其在金融保险中的应用研究，目前主持国家自然科学基金面上项目1项，参与国家自然科学基金重点项目1项，在《Adv. in Appl. Probab.》、《Bernoulli》、《Insurance Math. Econom.》、《Scand. Actuar. J.》、《Astin Bull.》等主流期刊发表学术论文30余篇。

报告二：中央财经大学孟辉教授学术报告

报告时间：2024年11月23日 14：30-15：30

报告地点：统计与数据科学学院会议室109

题目：Optimal Reinsurance Arrangement Under Heterogeneous Beliefs

摘要：In this work, we investigate the optimal per-claim reinsurance problem to minimize the insurer's ruin probability.  Inspired by the exponential upper bound of ruin probability in Cramér-Lundberg model, we take Lundberg exponent maximization as the value function. In the first part, we consider the optimal reinsurance problem under the combined upper moment premium principle. In the second part, we consider the optimal reinsurance problem for an insurer who has different belief about claims with the reinsurer based on the perspective of risk control. With the technique of piecewise modification, we extend the method adopted in Tan et al. [European J. Oper. Res., 282(2020), pp. 345-362] and Meng et al. [SIAM J. Financial Math., 13(2022), pp. 903-943]. This approach proposed here has good applicability for modifying reinsurance candidate to satisfy the incentive compatibility condition based on other value functions, such as the utility maximization problem. As examples, we also present the explicit reinsurance structures under a few representative belief heterogeneity environments.

报告人简介：孟辉，中央财经大学保险学院/中国精算研究院 教授，博士生导师,中央财经大学“青年龙马学者”。研究方向包括保险精算、金融风险分析与决策等，主持多项国家自然科学基金面上项目和中央财经大学创新团队项目，在《SIAM Journal on Control Optimization》、《SIAM Journal on Financial Mathematics》、《Economic Modelling》、《Insurance: Mathematics and Economics》、《ASTIN Bulletin》、《Scandinavian Actuarial Journal》、《中国科学：数学》等国内外重要期刊上发表论文三十余篇。

报告三：东南大学张鑫教授学术报告

报告时间：2024年11月23日 15：30-16：30

报告地点：统计与数据科学学院会议室109

题目：Stochastic linear quadratic optimal control problems with regime-switching jumps in infinite horizon

摘要：In this talk, we investigate a stochastic linear-quadratic (SLQ, for short) control problem regulated by a time-invariant Markov chain in infinite horizon. Under the $L^2$-stability framework, we study a class of linear backward stochastic differential equations (BSDE, for short) in infinite horizon and discuss the open-loop and closed-loop solvabilities of the SLQ problem. The open-loop solvability is characterized by the solvability of a system of coupled forward-backward stochastic differential equations (FBSDEs, for short) in infinite horizon and the convexity of the cost functional, and the closed-loop solvability is shown to be equivalent to the open-loop solvability, which in turn is equivalent to the existence of a static stabilizing solution to the associated constrained coupled algebra Riccati equations (CAREs, for short). Under the uniform convexity assumption, we obtain the unique solvability of associated CAREs and construct the corresponding closed-loop optimal control. Finally, we also solve a class of discounted SLQ problems and give two concrete examples to illustrate the results.

报告人简介：张鑫，东南大学数学学院，教授，博士生导师。2009年南开大学数学科学学院博士毕业并留校任教，2011年在澳大利亚Macquarie大学从事博士后研究，2014年调入东南大学数学学院。主要研究领域为精算数学，金融数学，随机控制理论及其金融保险中的应用，共主持国家自然科学基金4项，教育部博士点专项基金(新教师类) 1 项，在 SIAM Journal on Control and Optimization、Insurance Mathematics and Economics、Applied Mathematics and Optimization、Scandinavian Actuarial Journal 等国内外期刊上发表论文三十余篇。

报告四：中国矿业大学张帅琪教授学术报告

报告时间：2024年11月23日 16：30-17：30

报告地点：统计与数据科学学院会议室109

题目：Forward backward stochastic differential equation driven by sub-diffusion and its stochastic maximum principle

摘要：This talk starts with existence and uniqueness of fully coupled forward backward stochastic differential equation (FBSDEs) driven by anomalous sub-diffusion B_{L_t} under suitable monotonicity conditions on the coefficients. Here B_{L_t} is the Brownian motion on R and L_t is the inverse of a subordinator that is independent of B_{L_t}. Various priori estimates on the solution of the FBSDEs are also presented. Then we study optimal stochastic control problems which have nontrivial mixed features of deterministic and stochastic controls. Both the stochastic maximum principle (SMP) and sufficient SMP are obtained by using a convex variational method. The paper ends with an application of the main results of this paper to a linear quadratic problem in the subdiffusive setting, which is solved explicitly.

报告人简介：张帅琪，中国矿业大学数学学院教授，2012年毕业于中南大学， 澳⻔大学博士后，新加坡国立大学博士后。主要从事随机分析，随机控制，保险精算领域的研究。迄今在 SIAM Journal on Control and Optimization, Stochastic Processes and their Applications，Journal of Differential Equations ，Scandinavian Actuarial Journal, System Control Letters,中国科学:数学等刊物发表论文二十余篇，出版“十四五”国家重点出版物《随机分析与控制简明教程》，主持国家青年基金，教育部人文社科基金规划项目，江苏省面上等。

报告五：南方科技大学张艺赢教授学术报告

报告时间：2024年11月25日 14：30-15：30

报告地点：腾讯会议 593 237 040

题目：Mechanism design of government premium subsidies and disaster relief based on catastrophe insurance

摘要：In this talk, we examine the mechanism design of catastrophe insurance from the perspective of governmental interventions, considering both ex ante and ex post measures sequentially being into effect. The decision-maker (hereafter, DM) considers purchasing catastrophe insurance with premium subsidies backed by the government. The DM will select the optimal insurance policy to minimize her terminal risk exposure, and her risk preference is characterized by distortion risk measures. The government will determine the optimal subsidy level by minimizing total fiscal expenditures, which encompass both premium subsidy expenses and disaster relief payouts. Our findings demonstrate that premium subsidies can increase DM's insurance demand and result in better alignment with government expenditure objectives when compared to policies that rely solely on ex post relief measures.

报告人简介：张艺赢，南方科技大学数学系助理教授，研究员，博士生导师。主要研究兴趣包括最优（再）保险设计、系统性风险、信度理论等。研究成果主要发表在保险精算、金融数学和运筹管理等领域主流期刊，如：Insurance: Mathematics and Economics、ASTIN Bulletin、Scandinavian Actuarial Journal、North American Actuarial Journal、Quantitative Finance、European Journal of Operational Research、Naval Research Logistics、TEST、Reliability Engineering & System Safety、Computers & Industrial Engineering等杂志上。主持或完成省部级自然科学基金4项。