Fuzzy clustering rule-based expert system for stock price movement prediction

Through the years, the ability to predict the future trend of financial time series has drawn serious attention from both researchers and practitioners aiming to have better investment decisions. In this paper a fuzzy rule-based expert system is developed for predicting stock price movement. The importance of the proposed expert system is that it would be applicable for stock market´s speculators and traders´ daily transactions. For the experiment and in order to demonstrate the effectiveness of the model, the stock price of Apple Company is used as a sample data set.