Predicting the stock price companies using artificial neural networks (ANN) method (Case Study: National Iranian Copper Industries Company)

Abstract

A B S T R A C T The purpose of this research is the model fitness of predicting the companies' stock price using artificial neural networks (ANN) method of multilayer Perceptron with back propagation algorithm. The research population is Tehran Stock Exchange and National Iranian Copper Industries Company is considered as research sample. In order to model fitness, predicting of two cases is considered, in the first case, predicting occurred based on independent variables including the Tehran Stock Exchange price index, the price index of operating companies in the field of basic metals, the dollar exchange rate to Rial and monthly inflation rate and in the second case, predicting occurred based on the time series of past prices. The model of predicting stock price of National Iranian Copper Industries Company in the next day was studied and analyzed for each case individually on the fitted training data collection and then performance of fitted models in two cases, on the total testing data based on measuring criteria of error including mean absolute percentage error (MAPE), mean squared error (MSE) and root mean square error (RMSE). Evidence indicates the superiority of the predictive power of artificial neural network based on time series of the past prices. And to provide the predictive model the powerful software of MATLAB2014 is used.