拉斯维加斯赌场全体验

精算论坛讲座 第162期—Xuezhong He(7月4日)

发布时间:2019-06-20 14:24    浏览次数:[]

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(74)

教育部人文社科重点研究基地拉斯维加斯赌场3499学术活动

精算论坛讲座 第162期—Xuezhong He

(201974)

报告人ProfessorXuezhong (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 ControlJournalof Economic Behavior and Organization European Journalof Finance SIAMJournal ofEvolutionary EconomicsQuantitative 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 EvolutionElsevier)、Handbook on Information Technology in FinanceSpringer)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 CoordinationJournal Differential Equations and Dynamical Systems Discrete Dynamics in Nature and Society 等国际学术期刊的副主编(Associate Editor)。

 

报告时间:201974日(周四)上午10:0011:30

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(拉斯维加斯赌场全体验会议室)

 

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