EcoSta 2018: Registration
View Submission - EcoSta2018
A0660
Title: Statistical learning for optimal personalized wealth management Authors:  Yi Ding - The Hong Kong University of Science and Technology (Hong Kong) [presenting]
Yingying Li - Hong Kong University of Science and Technology (Hong Kong)
Rui Song - North Carolina State University (United States)
Abstract: A statistical learning method of continuous decision making for investment is proposed. We develop a Q-learning framework that allows one to make personalized wealth management decisions. Statistical properties are established for Q-learning in optimal continuous decision making. As an important application in investment, algorithms for optimal personalized investment decision making are developed. Empirically, we show that the proposed personalized investment decision making rule can substantially improve individuals financial well-being under a framework of consumption based utility analysis.