Title :
Evolutionary stock trading decision support system using sliding window
Author :
Wang, Jung-Hua ; Chen, Shiuan-Ming
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
Abstract :
A novel evolutionary decision support system (EDSS) that is effective for making profitable trading decisions in the stock market is presented. A genetic algorithm is incorporated with a sliding window scheme to effectively estimate the most profitable trading decision, namely buy, hold or sell. Because of its data-driven nature and the genetic change to the positive course, EDSS bypasses the complicated steps of network establishment and subsequent training, and it can directly deal with the problem of structural instability that plagues traditional rule-based systems. Empirical tests are conducted on the weighted price index of the Taiwan stock market (TSEWSI). Compared to the buy-and-hold strategy, the EDSS can achieve a significant improvement in profit gains
Keywords :
decision support systems; electronic trading; genetic algorithms; stock markets; Taiwan Stock Exchange Weighted Share Index; Taiwan stock market; buy-and-hold strategy; data-driven nature; evolutionary decision support system; genetic algorithm; profit gains; profitable trading decisions; sliding window scheme; structural instability; weighted price index; Decision making; Decision support systems; Economic forecasting; Expert systems; Genetic algorithms; Hardware; Knowledge based systems; Oceans; Stock markets; Testing;
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
DOI :
10.1109/ICEC.1998.699721
