【题目一】：加密数字货币的发展和交易机制
【主讲人】： 饶一博众米量化创始人&CEO
【时间】：2019年12月20日（周五）9：00-10：30
【地点】：北大经济学院107室
【主讲人简介】：饶一博，武大数理金融本科，13级北大国家发展研究院CCER硕士。福布斯U30创业精英，中国马会海南分会金融顾问。
本科合伙创业极验验证项目，担任副总经理，负责算法开发及财务管理，项目获得IDG红杉等亿元融资。后在深圳创办众米量化，担任CEO，公司专注于量化科技，尤其是人工智能在金融投资中的应用，是深圳高新技术企业，先后获得英诺等6家知名VC千万级融资。饶一博有逾10年量化策略研发与交易经验，对数字货币和国内证券二级市场微观结构和运作机理有深刻理解，同时具有5年以上对深度强化学习应用于金融交易的研发经验。
【题目二】：Advancements of Machine Learning in Econometrics (机器学习在计量经济学中的进展 )
【主讲人】：史震涛 助理教授 香港中文大学
【时间】：2019年12月20日（周五）10：30-12：00
【地点】：北大经济学院107室
【摘要】：Machine learning stands at the frontier of today’s technological progress, and it influences the way we conduct economic research. Given the wide availability of statistical software, economic applications of machine learning methods are burgeoning. However, there remains a wide gap to fill until machine learning becomes mainstream and can be routinely employed in empirical research. The theory of machine learning is mostly established for generic statistical models, but not tailored for context of economic interest. In this talk, I will review my works with collaborators in bridging machine learning and econometrics. They are either innovative machine learning algorithms that shed light on empirical economic questions, or studies of existing machine learning methods’ properties in economic settings, in particular nonstationary time series and panel data. We work under standard econometric theoretical frameworks and make progress in asymptotic guarantee. We also develop open-source software to engage users.
【主讲人简介】： Dr. Zhentao Shi is Assistant Professor at the Department of Economics, the Chinese University of Hong Kong. He obtained Ph.D. from Yale University, M.A. from CCER/NSD at Peking University, and B.A. from Zhejiang University.He specializes in econometric theory. He has published on top economic journals such as Econometrica, Journal of Econometrics, and Journal of Applied Econometrics.
