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

摘要

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., political effect. However, the latter plays a critical role in the stock market environment. Thus, this study develops a genetic algorithm based fuzzy neural network (GFNN) to formulate the knowledge base of fuzzy inference rules which can measure the qualitative effect on the stock market. Next, the effect is further integrated with the technical indexes through the artificial neural network (ANN).