主题：Next-generation Quantitative Investment: End-to-end All-in on Artificial Intelligence

报告人：Jian GUO, Executive President of IDEA, Chief Scientist of AI ​​Finance and Deep Learning

主持人：Jeff J, YAO, Presidential Chair Professor, School of Data Science, CUHK-Shenzhen

日期：11 October (Tuesday), 2022

时间：10:30 to 11:30 AM, Beijing Time

形式：Hybrid 

线下地点：103 Meeting Room, Daoyuan Building 

Zoom链接：https://cuhk-edu-cn.zoom.us/j/5304767369?pwd=aFErUGFSSDlLNWJld0VNNmpTL0k0UT09

Zoom会议号：5304767369

密码：852648

语言：English

摘要：

Quantitative investment (a.k.a. Quant) is an interdisciplinary field of financial engineering, computer science, mathematics and statistics, and it has grown as one of the mainstream investment methodologies over the past decades. Although artificial intelligence (AI) techniques such as deep learning have been accepted more and more popular in this area, most AI applications of quantitative investment relies on extremely large data volume and labor-extensive tuning deep/reinforcement learning ''black-boxes''. To address these limitations, in this talk, we propose an engineering perspective for the next-generation of quantitative investment, as well as an end-to-end investment engineering pipeline all-in on a more state-of-the-art AI technology. In particular, we claim three key components of AI in next-gen quant, i.e., automated AI, explainable AI, and knowledge-driven AI. We will introduce a number of research and engineering projects at IDEA Research Center of AI Finance & Deep Learning implementing the perspective of next-gen quant.

简介：

Jian Guo is the Executive President of International Digital Economy Academy (IDEA) as well as the Chief Scientist of AI Finance and Deep Learning. He received his Ph.D. degree of Statistics at University of Michigan (major in machine learning) in 2011, and completed his undergraduate education from Tsinghua University (major in mathematics & applied mathematics) in 2003. Prof. Jian Guo started his professorship (tenure-track) at Harvard University in 2011, being a faculty in data science, statistics and machine learning. He published a number of research papers in statistical machine learning, deep learning, reinforcement learning, probabilistic graphical model and bioinformatics, and his research have been applied to various areas including recommendation systems, search engine systems, computational advertising, gene sequence analysis and genetic disease prognosis and quantitative investment. Dr. Guo is also one of the pioneering researchers who explored the application of deep/reinforcement learning and big data techniques in finance investment and risk management, and he has over 6 years' quantitative investment and serial entrepreneurship experience. As a founding member of IDEA  and the founder of IDEA's AI Finance and Deep Learning Research Center (IDEA-FinAI), Jian Guo is leading a number of research projects around the next-generation technology of finance and quantitative investment, including autoML techniques for finance application, financial behavioral knowledge graph and reasoning techniques, large-scale deep learning models for quantitative finance, deep reinforcement learning platform for financial investment etc.

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