国产a片 学术报告[2026]007号

(高水平大学建设系列报告1266号)

报告题目：Learning to optimally stop a diffusion process

报告人：许左权 教授(香港理工大学）

报告时间：2026年1月20日 10:30-11:30

报告地点：汇星楼514

报告内容：We study optimal stopping for diffusion processes with unknown model primitives within the continuous-time reinforcement learning (RL) framework developed by Wang et al. (2020), and present applications to option pricing and portfolio choice. By penalizing the corresponding variational inequality formulation, we transform the stopping problem into a stochastic optimal control problem with two actions. We then randomise controls into Bernoulli distributions and add an entropy regulariser to encourage exploration. We derive a semi-analytical optimal Bernoulli distribution, based on which we devise RL algorithms using the martingale approach established in Jia and Zhou (2022a). We establish a policy improvement theorem and prove the fast convergence of the resulting policy iterations. We demonstrate the effectiveness of the algorithms in pricing finite-horizon American put options, solving Merton's problem with transaction costs, and scaling to high-dimensional optimal stopping problems. In particular, we show that both the offline and online algorithms achieve high accuracy in learning the value functions and characterising the associated free boundaries. This is a joint work with Min Dai, Yu Sun, and Xun Yu Zhou.

报告人简历：许左权教授先后于南开大学、北京大学、香港中文大学获得本科、硕士、博士学位，曾任英国牛津大学数学研究所任野村金融数学研究员，并兼任牛津Oxford-Man研究所通讯研究员。现任教于香港理工大学应用数学系，主要从事金融数学理论研究，包括量化行为金融学、投资组合、保险契约理论等研究领域，多次于世界著名学术机构及学术会议上作学术报告，主持过多项国家自然科学基金及香港研究资助局项目。其主要学术成果发表在《Mathematical Finance》,《Anna ls of Applied Probability》，《Finance and Stochastics》，《Mathematics of Operations Research》，《SIAM Journal on Financial Mathematics》，《Quantitative Finance》，《Insurance: Mathematics and Economics》等著名国际学术期刊上。现为著名国际期刊《Mathematics of Operations Research》编委。欢迎师生参加！

邀请人：董海玲

国产a片

2026年1月15日