Application of Enhanced Classification Method to Automatic Stock Portfolio Selection System Application of Enhanced Cluster Validity Index Method
An automatic stock portfolio selection system is presented. In the proposed approach, 53 financial indices are collected for each stock item and are consolidated into six financial ratios (Grey Relational Grades (GRGs)) using a Grey Relational Analysis (GRA) model. The GRGs are processed using a modified form of the PBMF index function method (designated as the Huang index function method) to determine the optimal number of clusters per.GRG; The resulting cluster indices are then processed using Rough Set (RS) theory to identify the stocks within the lower approximate sets. Finally, the GRGs of each stock item in the lower approximate sets are consolidated to a single GRG indicating the ability of the stock item to maximize the rate of return. It is shown that the stock selection mechanism yields a higher rate of return than a system in which the number of clusters per GRG is specified in advance.
Grey Relational Analysis Rough Set Huang index function PBMF index function Classification Cluster Portfolio
Kuang Yu Huang
Department of Management Information Ling Tung University Taichung City, Taiwan
国际会议
重庆
英文
1384-1388
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）