Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 5 Issue 7
Combining Neural Network and Firefly Algorithm to Predict Stock Price in Tehran exchange
Aliabdollahi Saharmotamedi
10.7753/IJCATR0507.1006
keywords : Tehran stock exchange, neural network, firefly.
In the present research, prediction of stock price index in Tehran stock exchange by using neural networks and firefly algorithm in chaotic behavior of price index stock exchange are studied. Two data sets are selected for neural network input. Various breaks of index and macro economic factors are considered as independent variables. Also, firefly algorithm is used to [redict price index in next week. The results of research show that combining neural networks and firefly optimization algorithm has better performance than neural network to predict the price index. In addition, acceptable value of error-sequre means for network error in test data show that there are chaotic mevements in behaviour of price index.
@artical{a572016ijcatr05071006,
Title = "Combining Neural Network and Firefly Algorithm to Predict Stock Price in Tehran exchange",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="7",
Pages ="448 - 454",
Year = "2016",
Authors ="Aliabdollahi
Saharmotamedi"}
Combining neural network and firefly algorithm to predict stock price in Tehran exchange
In addition, acceptable value of error-sequre means for network error in test data show that there are chaotic mevements in behaviour of price index.
Organized in three sections. In the first section, literature review is presented.
In order to solve the prediction problem of stock, time series are used