Title :
A hybrid model for portfolio selection based on Grey Relational Analysis and RS theories
Author :
Huang, Kuang Yu ; Jane, Chuen-Jiuan ; Chang, Ting-Cheng
Author_Institution :
Dept. of Manage. Inf., Ling Tung Univ., Taichung, Taiwan
Abstract :
In this study, the Grey Relational Analysis (GRA) model is combined with Fuzzy C-Means (FCM) clustering scheme and Rough Set (RS) theory to create an automatic portfolio selection mechanism. In the proposed approach, 53 financial indices are collected automatically for each stock item every quarter and a GRA model is used to consolidate these indices into six predetermined financial ratios (Grey Relational Grades (GRGs)). The GRGs of the stock items are then clustered using a FCM scheme and the resulting cluster indices are processed using RS theory to identify the lower approximate set within the stock system. The stock items within the lower approximate set are filtered in accordance with established investment principles and the six GRGs of each surviving stock item are then consolidated to a single GRG indicating the overall merit of the corresponding stock item in terms of its ability to maximize the rate of return on the investment portfolio. It is shown that the rate of return on the investment portfolio selected using the proposed GRA/FCM/RS system is higher than the average rate of return predicted by the variation in the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) over the same period.
Keywords :
fuzzy set theory; grey systems; investment; pattern clustering; rough set theory; stock markets; Taiwan stock exchange capitalization weighted stock index; financial indices; fuzzy c-means clustering; grey relational analysis; investment portfolio; portfolio selection; rough set theory; stock items; Filtering theory; IP networks; Indexes; Investments; Portfolios; Stock markets; Grey Relational Analysis; ROE; Rough Set; Stock Portfolio; TAIEX;
Conference_Titel :
Computer Symposium (ICS), 2010 International
Conference_Location :
Tainan
Print_ISBN :
978-1-4244-7639-8
DOI :
10.1109/COMPSYM.2010.5685542