AN INVESTMENT PORTFOLIO RECOMMENDATION SYSTEM FOR INDIVIDUAL E-COMMERCE USERS

Abstract

Choosing appropriate portfolio which can maximize the revenue in a bearable risk level is the most crucial decision for investors. Traditionally, this kind of decision requires a great deal of efforts and time, and usually made by financial professionals. It’s difficult for people without professional knowledge to choose appropriate investment portfolio by themselves. The objective of this paper is to develop a recommendation system which can recommend specific investment plan for different risk preference Internet investors. In the proposed recommendation system, the VaR method is used to measure the risk level of securities and risk preference of investors. In addition, a collaborative filtering algorithm is adopted to recommend portfolio that satisfy risk preference and requirements of investors, by considering the investor’s history behavior and the history behavior of nearest neighbor investors with similar risk preference. Finally, experiments are conducted to demonstrate the feasibility of the proposed recommendation system.