Portfolio management using hybrid recommendation system

Abstract

The goal of a decision support system is to provide the human user with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is the investment domain - the goal of investment decision-making is to select an optimal portfolio that satisfies the investor's objective, or, in other words, to maximize the investment returns under the constraints given by investors. The investment domain contains numerous and diverse information sources, such as expert opinions, news releases and economic figures, and so on. This presents the potential for better decision support, but poses the challenge of building a decision support agent for accessing, filtering, evaluating, incorporating information from different sources, and for making final investment recommendations. We proposed a hybrid recommendation system that utilized two different artificial intelligence techniques to provide human user a decision recommendation on stock portfolio management.