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Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange

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Main Authors: Vahid Amin, S. Hasan, Salehnezhad, Mehrdad, Valipour, Saber, Nasirlu
Other Authors: Vahid.Amin1985@yahoo.com
Format: Article
Language:English
Published: School of Business Innovation and Technopreneurship, Universiti Malaysia Perlis (UniMAP) 2015
Subjects:
Artificial Neural Network (ANN)
Genetic algorithm (GA)
Prediction
Stock price index
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/40039
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spelling my.unimap-400392016-07-21T02:14:40Z Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange Vahid Amin S. Hasan, Salehnezhad Mehrdad, Valipour Saber, Nasirlu Vahid.Amin1985@yahoo.com Shs_489@yahoo.com Valipour@iauneka.ac.ir Saber.nasirlu@gmail.com Artificial Neural Network (ANN) Genetic algorithm (GA) Prediction Stock price index Link to publisher's homepage at http://ijbt.unimap.edu.my/ Using volatility of stock price index by investor caused prediction of stock price index to be considered as one of the most controversial topics in finance. This study have been conducted using two artificial neural network and hybrid models of genetic algorithm-neural network as a successful model to predict the volatility of stock price index in Tehran stock exchange. Inputs to both models are nine indicators of guidance relating to eleven periods of 6-month from 2005 to 2010. Hybrid model of ANN-GA and ANN model were able to predict the volatility of the stock price index for 11 periods, on average, 96.34% and 89.80% respectively and this study showed that genetic algorithm combination with other models create an effective model to predict artificial intelligence model optimization. 2015-05-28T07:47:50Z 2015-05-28T07:47:50Z 2014-10 Article International Journal of Business and Technopreneurship, vol.4(3), 2014, pages 451-465 2231-7090 http://ijbt.unimap.edu.my/ http://dspace.unimap.edu.my:80/xmlui/handle/123456789/40039 en School of Business Innovation and Technopreneurship, Universiti Malaysia Perlis (UniMAP)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Artificial Neural Network (ANN)
Genetic algorithm (GA)
Prediction
Stock price index
spellingShingle Artificial Neural Network (ANN)
Genetic algorithm (GA)
Prediction
Stock price index
Vahid Amin
S. Hasan, Salehnezhad
Mehrdad, Valipour
Saber, Nasirlu
Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange
description Link to publisher's homepage at http://ijbt.unimap.edu.my/
author2 Vahid.Amin1985@yahoo.com
author_facet Vahid.Amin1985@yahoo.com
Vahid Amin
S. Hasan, Salehnezhad
Mehrdad, Valipour
Saber, Nasirlu
format Article
author Vahid Amin
S. Hasan, Salehnezhad
Mehrdad, Valipour
Saber, Nasirlu
author_sort Vahid Amin
title Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange
title_short Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange
title_full Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange
title_fullStr Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange
title_full_unstemmed Predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in Tehran Stock Exchange
title_sort predicting direction of stock price index volatility using genetic algorithms and artificial neural network models in tehran stock exchange
publisher School of Business Innovation and Technopreneurship, Universiti Malaysia Perlis (UniMAP)
publishDate 2015
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/40039
_version_ 1643799244635635712
score 13.160551

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