Hybrid Network of Neuro-Fuzzy based Decision Tool for Stock Market Analysis

Prediction of stock market return is an important issue in finance. Fuzzy and Artificial neural networks have been used in stock market prediction during the last decade. Studies were performed for the forecast of stock index values as well as daily direction of change in the index. This work compares fuzzy and arrangement of ANN model and makes these models to train with the past 5 years stock price datasets of various companies like (TCS, HCL) and the prediction of future stock price of company has been found. Membership functions (LOW, MEDIUM, HIGH) based fuzzy model will give recommendation for investor which says the current situation of the stock market. The Root Mean Square error (RMSE), Mean Absolute Performance (MAPE) metrics calculates the error rate value of each model. The proposed Hybrid Network model has expecting to given high performance.