Evaluating the Employment of Technical Indicators in Predicting Stock Price Index Variations Using Artificial Neural Networks (Case Study: Tehran Stock Exchange)

Abstract

Stock price index is the initial significant factor influencing on investors' financial decision making. That's whypredicting the exact movements of stock price index is considerably regarded. This study aims at evaluating theeffectiveness of using technical indicators, such as Moving Average, RSI, CCI, MACD, etc in predictingmovements of Tehran Exchange Price Index (TEPIX). An artificial neural network is employed for stock priceindex forecasting. The existing data are achieved from Tehran Stock Exchange. To capture the relationshipbetween the technical indicators and the levels of the index in the market for the period under investigation, aback propagation neural network is used. The statistical and financial performance of this technique is evaluatedand empirical results revealed that artificial neural networks are dominant tools for financial market predicting.