Stock trading decision support system using a rule selector based on sliding window

Author

Wang, Jung-Hua ; Chen, Shiuan-Ming ; Leu, Jia-Yann

Author_Institution

Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan

Volume

1

fYear

1997

fDate

12-15 Oct 1997

Firstpage

559

Abstract

We propose a dynamic decision support system (DDSS) capable of determining a near-optimal rule-combination for each time interval (window). The system provides Buy, Hold and Sell signals from which profitable trading decisions can be made. In DDSS, an intelligent rule selector (GARS) based on genetic algorithms and a sliding window scheme is developed. Experimental results on Taiwan stock exchange weighted stock index (TSEWSI) show that DDSS outperforms its static counterpart as well as the simple buy-and-hold strategy

Keywords

commodity trading; decision support systems; financial data processing; genetic algorithms; GARS; Taiwan stock exchange weighted stock index; dynamic decision support system; genetic algorithms; near-optimal rule-combination; rule selector; sliding window; sliding window scheme; stock trading decision support system; Artificial intelligence; Control systems; Decision support systems; Economic forecasting; Genetics; Oceans; Power system control; Power system dynamics; Power systems; Stock markets;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.625811

Filename

625811