Trading the stock markets using genetic fuzzy modeling

Author

Ettes, Drs Dennis

Author_Institution

Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands

fYear

2000

fDate

2000

Firstpage

22

Lastpage

25

Abstract

In this paper the reliability of trading systems that use prediction models as a rating model of stocks is analyzed and an improvement is proposed. It was found that the RISE criterion is unreliable for selecting a profitable model. To increase the reliability of the trading systems an approach is proposed that optimizes the rating models with a profit goal. Two different profit goals are tested. The first is a direct profit goal and the second goal includes sensitivity analysis in the goal function. In both cases, the rating models are optimized using a GA. The simulations show that the results are better and more reliable

Keywords

digital simulation; financial data processing; fuzzy logic; genetic algorithms; sensitivity analysis; stock markets; RISE criterion; direct profit goal; genetic algorithm; genetic fuzzy modeling; optimization; prediction models; sensitivity analysis; simulations; stock market trading; stock rating model; trading system reliability; Data preprocessing; Electronic mail; Fuzzy sets; Genetics; Laboratories; Portfolios; Predictive models; Sensitivity analysis; Stock markets; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Financial Engineering, 2000. (CIFEr) Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on

Conference_Location

New York, NY

Print_ISBN

0-7803-6429-5

Type

conf

DOI

10.1109/CIFER.2000.844591

Filename

844591