A Prototype Intelligent Agent Based DSS for Quadratic Portfolio Optimization Calculations with Case Based Reasoning

Abstract

A variety of intelligent agent systems have assisted portfolio management decisions. The majority of these systems have focused on analysis methods, such as fundamental analysis, technical analysis or analysis of trader behavior. According to Clarke et al, because of the efficient markets hypothesis, portfolio managers should limit the time that they spend on analysis of this type and instead concentrate on other aspects of portfolio management, such as diversification, asset allocation or cost management. This study investigates the application of intelligent agents to strategic asset allocation. Traditionally, strategic asset allocation is calculated using tools for quadratic optimization and determining an investor's utility towards risk. Associated with strategic asset allocation are many complexities, such as the distributed nature of problems that make a solution difficult to implement. This paper outlines results of an evaluation of whether intelligent agent and case based reasoning could overcome these complexities. From a review of literature there does not appear to have been a study that has considered this problem in the way proposed in this paper