——Thoughts on the application of large-scale pre trained models such as GPT in quantitative investment&AI quantification: framework and case studies
On the afternoon of April 11, 2023, the School of Statistics at Shanghai University of Finance and Economics invited Mr. Wang Zhenzhou, General Manager of Taiping Asset Quantitative Investment Department, and Mr. Yi Chao, Investment Manager of Taiping Asset Quantitative Investment Department, to participate in an industry forum to teach "Reflections on the Application of Large scale Pre trained Models such as GPT in Quantitative Investment&AI Quantification: Framework and Cases" and provide guidance and exchange for students.
Teacher Wang Zhenzhou has worked as a fund manager in multiple fund companies. Through quantitative stock selection techniques and a deep understanding of the industry, he has managed multiple funds that have achieved huge returns and ranked among the top performers. Established the Taiping Asset Quantitative Investment Department, established and invested in Taiping series quantitative products, and ranked among the top ten in terms of performance among similar funds.
Professor Yi Chao graduated from Shanghai Jiao Tong University with a major in Applied Statistics. He has previously worked as an AI Quantitative Engineer at Huaxia Fund Management Co., Ltd. and has been serving as an Investment Manager in the Quantitative Investment Department of Taiping Asset Management Co., Ltd. since June 2022, possessing a profound understanding of quantitative investment.
The lecture first introduced the recently popular ChatGPT artificial intelligence model. Standing at the node of ChatGPT's explosion, which is known as the "AI iPhone era", how to apply AI to quantitative investment and obtain a framework and application that combines the two is an important issue. To this end, two teachers introduced the basic concepts of quantitative investment and artificial intelligence, and explained the application framework of artificial intelligence in quantitative investment. Next, in order to enable students to have a deeper and more intuitive understanding of the corresponding concepts and models, the teacher also told us several real cases in investment trading. In the final stage, the teacher also mentioned two important issues that need to be addressed after quantifying artificial intelligence, namely how to explain the model and what is the supervisory logic in model construction?
The wonderful lecture aroused a strong thirst for knowledge among the students, and the teacher patiently explained various questions raised by the students, including the data order problem of time series models, why most of the investment results obtained by AI models are ETFs, whether AI models target human weaknesses, data acquisition, and so on. After listening to the teacher's explanation, the students all benefited greatly. In the end, the industry forum came to a successful conclusion, and the students gained a lot of knowledge through this lecture, gaining deeper insights into AI and quantitative investment.
Author: Feng Jiaqi
Image provided by: Zhu Xiangyu
