On statistical learning for personalized wealth management
报告人： Rui Song, North Carolina State University
地点：Room 216, Guanghua Building 2
In this talk, we establish a statistical learning framework for personalized wealth management study. Specifically, a high-dimensional Q-learning methodology is proposed for continuous decision making. The proposed method is shown to enjoy desirable oracle properties and facilitate valid statistical inference for optimal values. Empirically, the proposed statistical learning methodology is used to solve the personalized wealth management problem with data from a Health and Retirement Study. The results show that the proposed personalized optimal strategy can improve individual’s financial well-being and surpasses several benchmark strategies significantly under a consumption based utility framework.
About the Speaker:
Rui Song is an Associate Professor in Department of Statistics at North Carolina State University. She got her BS from Peking University and PhD from University of Wisconsin, Madison, all in Statistics. Her current research focuses on machine learning, data science, precision medicine and financial econometrics. Her research has been continuously supported as principle investigator by National Science Foundation (NSF). She received the prestigious NSF Faculty Early Career Development (CAREER) Award in 2016.