On-demand forecasting of stock prices using a real-time predictor

This paper presents a fuzzy stochastic prediction method for real-time predicting of stock prices. A complete contrast to the crisp stochastic method, it requires a fuzzy linguistic summary approach to computing parameters. This approach, which is found to be better than the gray prediction method, can eliminate outliers and limit the data to a normal condition for prediction, with a comparatively very small deviation of 4.5 percent.