An analysis of investor's portfolio utilizing NeuroFuzzy control systems
by
Jack Allen
Griffith University , Gold Coast , Queensland Australia
Coauthors: Sukanto Bhattcharya, Bond University Gold Coast Queensland Australia

There is no doubt that there exists a defined parallel between investor behavior as studied in portfolio theory and consumer behavior as studied under the light of control finance theory. In this paper, we have used the classical financial framework of control utility theory to devise a structured system for investor risk classification according to the utility preferences of individual investors. However, an individual investor may not have a fixed utility function over time. This will bring some form of classification into an investor's portfolio, such a control utility function could have a time-dependent dynamic structure. An investor who may be classified under a particular class may well have to be re-classified. Therefore, the first part of this work has explored the implications of classical control utility theory in financial engineering and in the second part we have incorporated NeuroFuzzy control systems to produce and compute risk classification for the homological utility of an investor under several scenarios. NeuroFuzzy classification examines the homological effect of the investor's utility in any given portfolio.

Date received: August 3, 2001