L. Li
A model based approach is typically adopted for solving financial decision making problems, which is prone to model error. In this project, we develop a data-driven approach that is free of parametric models and we use neural networks to approximate the control functions. The availability of massive computing power makes it possible to implement our approach within time constraints in reality.