报告时间：2025年11月14日下午15：00-17：00

报告地点：统计与数据科学学院106会议室

报告题目： Worst-case values of target semi-variances with applications to robust portfolio selection

报告摘要： The expected regret and target semi-variance are two of the most important risk measures for downside risk. When the distribution of a loss is uncertain, and only partial information of the loss is known, their worst-case values play important roles in robust risk management for finance, insurance, and many other fields. In this paper, we first derive the closed-form expressions for the worst-case target semi-variance when only the mean and variance of a loss are known, and the loss is symmetric or non-negative. Then, we investigate worst-case target semi-variances over uncertainty sets that represent undesirable scenarios faced by an investor. We propose robust portfolio selection methods that minimize the worst-case target semi-variance of a portfolio loss over different uncertainty sets. To explore the insights of our robust portfolio selection methods, we conduct numerical experiments with real financial data and compare our portfolio selection methods with several existing portfolio selection models.

专家简介：蔡军, 加拿大滑铁卢大学统计与精算科学系教授, 博士生导师。他的研究兴趣包括精算科学, 运筹学, 数理金融, 应用概率。目前，他的研究主要集中在保险和金融中的风险量化管理, 最优决策问题,模型不确定性下的风险分析。他的研究成果发表在多个相关领域的权威学术期刊上, 包括 Operations Research, European Journal of Operational Research, Mathematical Finance, Finance and Stochastics, Journal of Risk and Insurance, Insurance: Mathematics and Economics, Advances in Applied Probability, Journal of Multivariate Analysis, Stochastic Processes and their Applications。 他与中国科学技术大学毛甜甜共同荣获2020年国际精算协会 (IAA） Bob Alting von Geusau奖。 目前, 他还担任Insurance: Mathematics and Economics期刊的副主编。