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
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.