STOCK EXCHANGE INDEX PREDICTION USING HYBRID MODELS

Abstract

ABSTRACT Prediction of stock price index and the direction of its movement are regarded as one of the most challenging applications of time series. In this study, Tehran Stock Exchange index is predicted for 5next periods, using data from gold price, Europe Brent oil price index, New York Stock Exchange and the exchange rate, using single, hybrid and combination model, in which they are used, the multi-layer neural network and time series models