新加坡国立大学董玉超教授学术报告

发布者:费洋发布时间:2019-12-26浏览次数:142

报告题目Calibrating Equilibrium Mean Variance Strategy with Reinforcement Learning

报告人:董玉超

报告时间20191227(周五)10:00-11:00

报告地点:联合彩票注册212会议室

报告摘要In this talk, we consider the mean-variance problem for terminal log-return under incomplete market. In additional, an entropy term is included in the objective functional to encourage exploration of the strategy. As the problem is time-inconsistent, we characterize the equilibrium strategy with the help of extended HJB equation. Finally, we propose a learning process to obtain the strategy through the interaction with the market.

教授简介Yuchao Dong received Ph.D degree in 2016 from School of Mathematical Sciencea, Fudan University. Now he is a research fellow in the department of mathematics, NUS. His major research interest includes mathematical finance and stochastic optimal control theory.


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