报告时间: 3 Apr, 2024, 15:00-16:00

报 告 人: Min Dai, Chair Professor, HK Polytechnic University

报告地点: 览秀楼105学术报告厅

报告摘要:  We develop a reinforcement learning method to learn an optimal trading strategy in the presence of transaction costs. Using a connection between singular control and a Dynkin game for portfolio choice with transaction costs, we learn the value function and optimal policy of an associated randomized Dynkin game, where a regularization term is incorporated to encourage exploration. We show that the policy efficiently approximates the optimal trading strategy. We design a reinforcement learning algorithm, which is demonstrated by numerical results. This work is jointly with Yuchao Dong.

报告人简介:戴民教授现任香港理工大学讲座教授，曾任新加坡国立大学数量金融中心主任、风险管理研究所副所长。在金融衍生产品定价与对冲、动态投资策略、缺乏流动性的投资组合设计等领域做了很多深入的工作。文章发表在Journal of Finance, Journal of Economic Theory, Management Science, Mathematical Finance, Review of Financial Studies等国际一流期刊。目前担任SIAM Journal on Financial Mathematics，Journal of Economic Dynamics & Control等期刊编委。