龙马奋进 · 校庆70周年学术系列讲座
精算论坛讲座 第162期—Xuezhong He(7月4日)
教育部人文社科重点研究基地中央财经大学中国精算研究院学术活动
精算论坛讲座 第162期—Xuezhong He
(2019年7月4日)
报告人：Professor Xuezhong (Tony) He
Xuezhong He 教授现任悉尼科技大学商学院（ UTS Business School ） 教授(Professor of Finance)，主要活跃于金融市场建模、异质信念下的资产定价和非线性经济动力学等领域，在Journal of Economic Dynamics and Control、Journalof Economic Behavior and Organization 、European Journalof Finance 、SIAM 、Journal ofEvolutionary Economics和Quantitative Finance等国际主流学术期刊上发表文章50多篇，撰写了Handbook of Financial Markets:Dynamics and Evolution（Elsevier）、Handbook on Information Technology in Finance（Springer）等10余部学术书籍的部分章节。此外，Xue-Zhong He教授担任本领域三大顶尖国际学术期刊之一Journal ofEconomic Dynamics and Control的主编（Co-Editor）；还担任Journal of Economic Interaction and Coordination、Journal Differential Equations and Dynamical Systems 和Discrete Dynamics in Nature and Society 等国际学术期刊的副主编（Associate Editor）。
报告时间：2019年7月4日（周四）上午10:00—11:30
报告题目：Reinforcement Learningand Evolutionary Equilibrium in Limit Order Markets（限价订单市场中的强化学习与演化均衡）
报告摘要: With the rapid rising and ubiquity of algorithmic trading in limit ordermarkets, we show that an information-based reinforcement learning can bevery effective to find an evolutionary equilibrium. By performingcomparative dynamics in equilibrium, we show that the order choiceof buy-or-sell and market-or-limit orders for informed traders mainlydepends on their information about fundamental value, while uninformed traders tradeon a short-run momentum of informed market orders. The learning improves marketliquidity and increases uninformed traders' liquidity supply and informedtraders' liquidity consumption, generating order flow persistence andhump-shaped order books. It also improves traders' welfare and pricediscovery. The results shed an economic insight into the market practice ofusing machine learning in trading.
报告地点：学术会堂南楼506（中国精算研究院会议室）
欢迎各位老师和同学积极参加！
