学术报告

题      目：Learning Optimal Trading Strategy with Transaction Costs

报  告  人：戴民  教授  (邀请人：杨舟 )

                                   香港理工大学

时      间：1月8日  11：00-12：00

地     点：数科院西楼二楼会议室

报告人简介:

        戴民，香港理工大学应用统计与金融数学讲座教授。戴民教授2000年于复旦大学获得数学博士学位后，先后担任了新加坡国立大学重庆研究院金融与金融风险管理研究室主任，新加坡国立大学数量金融中心主任，北京大学金融数学系副教授。其研究领域为数量金融和金融科技，随机控制，应用和数值偏微分方程，在Journal of Economic Theory, Journal of Finance, Journal of Financial and Quantitative Finance，Management Science，Mathematical Finance，Review of Financial Studies，SIAM Journals等期刊发表或待发表论文50余篇。现任Digital Finance联合主编及Finance and Stochastics，Journal of Economic Dynamics and Control，SIAM Journal on Financial Mathematics，Mathematics and Financial Economics，Asia-Pacific Journal of Operational Research，Frontiers of Mathematical Finance等期刊编委。

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.

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