Application of Combined Arma-Neural Network Models to Predict Stock Prices

Predicting the prices of stocks is a very important field of research nowadays. Many different types of models have already been implemented. Two types of techniques include ARMA models and Neural Networks. In this work, ARMA models, along with two types of Neural Networks (Back Propagation) and Multi-Layer Perceptron (MLP) have been used. Furthermore, the two neural networks were combined with ARMA models (individually) in order to generate the best forecasted prices. The two indexes used for forecasting are the Dow Jones Industrial Average (DJI) and the Saudi Stock Exchange Tadawul (TASI). 800 values were used to predict the future 200 values. It was found out that for such large number of predictions, MLP yields the best results, which are drastically improved when combined with ARMA forecasting.