An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network

Citation
Rj. Kuo et al., An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network, FUZ SET SYS, 118(1), 2001, pp. 21-45
Citations number
37
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Engineering Mathematics
Journal title
FUZZY SETS AND SYSTEMS
ISSN journal
0165-0114 → ACNP
Volume
118
Issue
1
Year of publication
2001
Pages
21 - 45
Database
ISI
SICI code
0165-0114(20010216)118:1<21:AISTDS>2.0.ZU;2-I
Abstract
The stock market, which has been investigated by various researchers, is a rather complicated environment. Most research only concerned the technical indexes (quantitative factors), instead of qualitative factors, e.g., polit ical effect. However, the latter plays a critical role in the stock market environment. Thus, this study develops a genetic algorithm based fuzzy neur al network (GFNN) to formulate the knowledge base of fuzzy inference rules which can measure the qualitative effect on the stock market. Next, the eff ect is further integrated with the technical indexes through the artificial neural network (ANN). An example based on the Taiwan stock market is utili zed to assess the proposed intelligent system. Evaluation results indicate that the neural network considering both the quantitative and qualitative f actors excels the neural network considering only the quantitative factors both in the clarity of buying-selling points and buying-selling performance . (C) 2001 Elsevier Science B.V. All rights reserved.