Title :
Comparing Personal Portfolio Strategies by Genetic Algorithm Mixed with Association Rules
Author_Institution :
Dept. of Int. Bus., Nat. Kaohsiung Univ. of Appl. Sci.
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
In this article, we utilize the genetic algorithm (GA) mixed with association rules (AR) to determine the optimal personal portfolio strategy in the complicated stock market of Taiwan. According to the investors´ preference, the size of fund, the period of investment and financial ratio, etc., a portfolio which is fitted to the personality of the investor and optimal return is proposed. We analyze the data of Taiwan stock market during the period between 1991 and 1997. By comparing the portfolio strategies determined by GA and by GA combined with RA (GA-RA), we conclude that the latter could provide a better portfolio for return on investment (ROI) and an improved execution rate than those of the former
Keywords :
data mining; genetic algorithms; investment; stock markets; Taiwan stock market; association rules; genetic algorithm; investment; optimal personal portfolio strategy; Artificial intelligence; Association rules; Data analysis; Data mining; Fluctuations; Genetic algorithms; Hazards; Investments; Portfolios; Stock markets;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.252
