Author/Authors :
Amin, Vahid payame noor university - Department of Accounting, تهران, ايران , Salehnezhad, S. Hasan payame noor university - Department of Accounting, تهران, ايران , Valipour, Mehrdad Islamic Azad University, Neka Branch - Department of Accounting, ايران , Nasirlu, Saber Islamic Azad University, Qazvin Branch - Department of Accounting, ايران
Abstract :
Using volatility of stock price index by investor caused prediction of stock priceindex to be considered as one of the most controversial topics in finance. Thisstudy have been conducted using two artificial neural network and hybridmodels of genetic algorithm-neural network as a successful model to predict thevolatility of stock price index in Tehran stock exchange. Inputs to both modelsare nine indicators of guidance relating to eleven periods of 6-month from 2005to 2010. Hybrid model of ANN-GA and ANN model were able to predict thevolatility of the stock price index for 11 periods, on average, 96.34% and89.80% respectively and this study showed that genetic algorithm combinationwith other models create an effective model to predict artificial intelligencemodel optimization.
Keywords :
Artificial Neural Network (ANN) , Genetic Algorithm (GA) , prediction , stock price index
