A Survey on the Application of Hybrid Techniques for Stock Market Forecasting

This paper is aimed to present a survey on recent literature in the areas of applying Soft Computing, Data-mining and Swarm Intelligence for Stock Market Forecasting. The objective is to synergize new ideas in the field of developing expert systems in the field of stock market forecasting. This papers‘ contribution is to explore the major areas where researches have been undertaken, and attempt to identify the degree of successes associated with different research approaches. This paper discusses various research approaches used for stock market forecasting which reflects the fact that using only one approach or tool cannot lead to successful forecasts, hence it can be concluded that combining soft-computing, data-mining and swarm-optimization would definitely result in better and reliable forecasting systems. These three approaches can closely model the human behavior and knowledge, which is very much desired while forecasting stock markets and developing expert systems for the same.