A decision support system for the stock market through integration of fuzzy neural networks and fuzzy delphi

The stock market, which has been investigated by various researchers, is a very complicated environment. Most past research is only concerned with the quantitative factors such as index in open and volume, rather than the qualitative factors, such as the political effect. However, the latter plays a critical role in the stock market environment. Therefore, this research proposes a decision support system for the stock market that considers the quantitative factors as well as the qualitative factors. The proposed system consists of four steps: (1)factors collection, (2) quantitative model (fuzzy neural network \[FNN]), (3) qualitative model (fuzzy Delphi), and (4) decision integration (FNN). An example based on the Taiwan stock market is utilized to evaluate the proposed intelligent system. Evaluation results indicate that the proposed system can perform more effectively than the single artificial neural network.