Speaker:Dacheng Xiu（Professor of Econometrics and Statistics,University of Chicago, Booth School of Business）
Description: Because machine learning can handle a large number of predictive variables and has a variety of functional forms, the application of machine learning methods in the financial field is always a concerned issue in the cademia and industry.
This paper applies a variety of representative machine learning methods to solve the most studied and classic problem in the field of empirical asset pricing: measuring the risk premium of assets. This paper focuses on comparing the different methods. It is found that using machine learning to predict can bring huge economic benefits to investors, which is better than the long-term regression analysis strategy in the literature. Among them, classification tree and neural network are the two learning methods with the best performance. Compared with other methods, they take into account the nonlinear relationship and interaction between variables and effectively improve the prediction accuracy.
Time：June 3, June 10 8:00-13:00 (Beijing Time)
Venue: Tencent Meeting
