**教育部人文社科重点研究基地中央财经大学2021欧洲杯足球竞猜官方平台学术活动**

**(2021****年5月31日)**

**2021****年****5****月****31****日2021欧洲杯足球竞猜官方平台风险量化与决策研究中心将协同加拿大滑铁卢大学统计与精算系联合举办“长寿风险管理与量化分析”的小型线上研讨会。**

**（腾讯会议：****411 777 609****）**

**报告题目一：**Common mortality trend model and mortality prediction

**报告时间：****2021****年****5****月****31****日****9:00--9:30**

**报告人：翁成国（滑铁卢大学）**

Dr. Chengguo Weng is a professor of actuarial science at the University of Waterloo. His recent research interest covers insurance predictive analytics, portfolio theory, and the interface of stochastic optimization and statistical inference.

**摘要：**We propose a framework to allow populations at disparate mortality development stages to be contemporaneously considered through a bivariate-population mortality system with an underlying process of common mortality trend (CMT). As one of the main contributions of the paper, the CMT model is used as a base learner in a computationally friendly framework to effectively borrow information from multiple populations for the mortality prediction of a target population through a well-established procedure of model averaging. Empirical studies with the Human Mortality Database (HMD) confirm that the proposed CMT-based prediction framework yields a substantial improvement in prediction performance over a set of benchmark prediction models. Furthermore, these empirical studies reveal that a key parameter introduced in the CMT model can characterize the development stage of one population relative to the other in the CMT model.

**报告题目二：**Pricing and interest rate risk measurement of arithmetic Asian options under Vasicek interest rate model

**报告时间：****2021****年****5****月****31****日****9:30--10:00**

**报告人：韦晓（中央财经大学）**

韦晓，中央财经大学保险学院、2021欧洲杯足球竞猜官方平台副教授。毕业于武汉大学，2006加入中央财经大学保险学院工作，2006年至2008年在法国国家信息与自动化研究院（INRIA）金融数学项目组（Mathfi Team）从事博士后研究，并参与该项目组的金融软件Premia的研发设计，曾先后访问香港科技大学，加拿大滑铁卢大学，意大利乌迪内大学；曾在国际期刊《*Insurance: Mathematics and Economics*》《*Astin Bulletin*》《*Statistics & Probability Letters*》《*Journal of Applied Probabilities*》等发表多篇学术论文；主持国家自然科学基金项目、教育部人文社科项目等多项课题。

**摘要：**Asian options are designed to avoid manipulate of the underlying asset and smooth the payoff of the option at time of maturity, they are feather as long duration derivative and more sensitive to the movement of interest rates, thus interest rate risk should be taken into account when pricing Asian options. Most research on pricing of Asian options focuses on the geometric-average, due to the intractability of the arithmetic-average of the underlying asset, it is difficult to price the arithmetic Asian option by close formula even under the geometric Brownian motions model with a constant interest rate. In this paper, we employ Vasicek model to describe the fluctuation of interest rate, then we introduce a stratified approximation method using lognormal distribution and gamma distribution to obtain the price of arithmetic Asian option. This method allows to approximate the price of arithmetic Asian option under Vasicek interest rate model efficiently. Furthermore we measure the interest rate risk on arithmetic Asian options by sensitivity of option price to the change of parameters in the interest rate model.

**报告题目三：**Optimal Nested Simulation Experiment Design Via Likelihood Ratio Method

**报告时间：****2021****年****5****月****31****日****10:00--10:30**

**报告人：冯铭斌（滑铁卢大学）**

MINGBIN FENG is an assistant professor in actuarial science at the University of Waterloo. He earned his Ph.D. in the Department of Industrial Engineering and Management Sciences at Northwestern University. He is an Associate of the Society of Actuaries (ASA). His research interests include stochastic simulation design and analysis, optimization via simulation, nonlinear optimization, and financial and actuarial applications of simulation and optimization methodologies.

**摘要：**This talk proposes a new experiment design for nested simulation whose inner replication's inputs are generated from probability distributions parameterized by the outer scenario. Prior to running any simulations, we formulate a bilevel optimization problem to decide not only which outer scenarios to simulate and how many times replicate at each, but also how to pool these replications via the likelihood ratio method such that the total simulation effort is minimized while achieving the same level of estimation error as the standard nested simulation. Asymptotic analyses show that various performance measure estimators computed from our design achieve fast convergence. We also show numerical study results that demonstrate our design reduces simulation effort by orders of magnitudes compared to standard nested simulation and other state-of-art designs.

**报告题目四：**Multi-period Telser's safety-first portfolio selection problem in a defined contribution pension plan

**报告时间：****2021****年****5****月****31****日****10:30--11:00**

**报告人：伍慧玲（中央财经大学）**

伍慧玲，研究员，博士生导师，主持3项国家自然科学基金项目和教育部人文社科项目，参与多项校级创新团队项目，国家级自然科学基金面上项目、北京市哲学社会科学重点项目、教育部人文社科基地重大项目，以及国家社科基金重点项目；在系统工程理论与实践，中国管理科学学报，管理评论，Insurance: Mathematics and Economics, Economic Modelling, OR Spectrum, Journal of Optimization Theory and Applications等国内外杂志发表了三十余篇论文；担任国内外多个知名学术期刊的匿名审稿人。

**摘要：**This paper investigates a multi-period portfolio optimization problem for a defined contribution pension plan with Telser's safety-first criterion. The plan members aim to maximize the expected terminal wealth subject to a constraint that the probability of the terminal wealth falling below a disaster level is less than a pre-determined number called risk control level. By Tchebycheff inequality, Lagrange multiplier technique, the embedding method and Bellman's principle of optimality, we obtain the conditions under which the optimal strategy exists and derive the closed-form optimal strategy and value function. Special cases show that the obtained results in our paper can be reduced to those in the classical mean-variance model. Finally, numerical analysis is provided to analyze the effects of the risk control level, the disaster level and the contribution proportion on the disasterprobability and the value function. The numerical analysis indicates that the disaster probability in this paper is always less than that in the classical mean-variance model on the premise that the value functions are the same in two models.

**报告题目五：**A framework for measures of risk under uncertainty

**报告时间：****2021****年****5****月****31****日****11:00--11:30**

**报告人：王若度（滑铁卢大学）**

Dr. Ruodu Wang is University Research Chair and Associate Professor of Actuarial Science and Quantitative Finance at the University of Waterloo in Canada. He received his PhD in Mathematics (2012) from the Georgia Institute of Technology, after completing his Bachelor (2006) and Master’s (2009) degrees at Peking University. He holds editorial positions in leading journals in actuarial science and mathematical economics, including Co-Editor of the European Actuarial Journal, and Co-Editor of ASTIN Bulletin. His scientific work has appeared in academic journals in various other fields, such as Management Science, Operations Research, The Annals of Statistics, Biometrika, The Annals of Applied Probability, Mathematics of Operations Research, Mathematical Finance, and Finance & Stochastics. He is an affiliated member of RiskLab at ETH Zurich. He received the Golden Jubilee Research Excellence Award from the Faculty of Mathematics at Waterloo in 2017 and a Discovery Accelerator Supplement Award from the Natural Sciences and Engineering Research Council in 2018.

**摘要：**A risk analyst assesses potential financial losses based on multiple sources of information. In particular, the assessment does not only depend on the loss random variable, but also various economic scenarios. Motivated by this observation, we design a unified axiomatic framework for evaluation principles which quantifies jointly a loss random variable and a set of plausible probabilities. We call such an evaluation principle a generalized risk measure. As the most practical choice, the worst-case generalized risk measure is characterized via a few intuitive axioms. We reveal the relationship between a few natural forms of law invariance, under which we further pin down particular forms of the worst-case generalized risk measures. Some connections to decision theory are discussed, and many open questions remain.

**报告题目六：**Singular Stochastic Control Theories and Differential Games with Markovian Regime Switching

**报告时间：****2021****年****5****月****31****日****11:30--12:00**

**报告人：刘敬真（中央财经大学）**

刘敬真，毕业于香港理工大学，现任中央财经大学保险学院精算系副教授，博士生导师。主持两项国家自然科学基金项目，曾经在Automatica，SIAM等杂志发表文章多篇。

**摘要：**This paper discusses stochastic optimal control theories and stochastic differential games in a system of singular forward-backward stochastic differential equations (FBSDEs) in the presence of Markovian regime-switching effects. These problems may be partly motivated by a utility maximization problem with a stochastic differential utility, a singular consumption process and changing market regimes. The necessary and sufficient stochastic maximum principles for both the singular control and game problems are derived.Finally, the relationship between the maximum principles and dynamic programming is discussed in the case of Markovian-controlled dynamics.

**欢迎各位老师和同学积极参加！**