The Comparison of Fuzzy Neural Network Methods with Wavelet Fuzzy Neural Network in Predicting Stock Prices of Banks Accepted in Tehran Stock Exchange

Abstract

The purpose of this study was to compare the predictive power of fuzzy neural network with fuzzy wavelet neural network in predicting stock prices of banks in Tehran Stock Exchange. The period of this research was from 2011 to 2016. In this research, the fuzzy logic system with the use of a multi-layer neural network system with an error-optimized back-propagation optimization structure and a Maximum Overlapping Discrete Wavelet Transform for exchange rate variables, opec oil, each ounce of gold, the total stock index as well as the volume of trades were used in order to predict stock prices.The results of the model were done by using the updated cost function. The results of the research in comparison of fuzzy wavelet network and fuzzy neural network showed that the reliability of banks with fuzzy wavelet neural network is over 90% and with fuzzy neural network above is 80%. As a result, fuzzy wavelet neural network is more reliable than fuzzy neural network

Keywords

• Neural Network
• Fuzzy Logic
• Wavelet
• Predict Stock Prices