Abstract

An expert system for automatically selecting stock portfolio is presented. The expert system involved Grey Relational Analysis (GRA) model, the VPRS-index clustering / classification method, and Variable Precision Rough Set (VPRS) theory. The GRA model is applied to consolidate the 53 financial indices into six financial ratios (Grey Relational Grades (GRGs)) for each stock item. The VPRS-index method is used to determine the optimal number of clusters per GRG. VPRS theory is then applied to identify the stocks within the -lower approximate sets. Finally, the GRGs of each candidate stock item are consolidated to a single GRG indicating the ability of the stock item to maximize the rate of return. The validity and effectiveness of the VPRS-index clustering / classification method is first evaluated prior to that of the expert system. After that, results of this study showed that this expert system yields a higher rate of return than those of several existing portfolio selection systems.

Key words: Fuzzy C-Means, VPRS, VPRS-index method, classification, stock portfolio.