文件名称:12_-Fallahi-AAM-R358-SF-012211
介绍说明－－下载内容均来自于网络，请自行研究使用
The cement industry is one of the most important and profitable industries in Iran and great
content of financial resources are investing in this sector yearly. In this paper a GMDH-type
neural network and genetic algorithm is developed for stock price prediction of cement sector.
For stocks price prediction by GMDH type-neural network, we are using earnings per share
(EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio
(P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data
of ten cement companies is gathering Tehran stock exchange (TSE) in decennial range
(1999-2008). GMDH type neural network is designed by 80 of the experimental data. For
testing the appropriateness of the modeling, reminder of primary data were entered into the
GMDH network. The results are very encouraging and congruent with the experimental results.-The cement industry is one of the most important and profitable industries in Iran and great
content of financial resources are investing in this sector yearly. In this paper a GMDH-type
neural network and genetic algorithm is developed for stock price prediction of cement sector.
For stocks price prediction by GMDH type-neural network, we are using earnings per share
(EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio
(P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data
of ten cement companies is gathering Tehran stock exchange (TSE) in decennial range
(1999-2008). GMDH type neural network is designed by 80 of the experimental data. For
testing the appropriateness of the modeling, reminder of primary data were entered into the
GMDH network. The results are very encouraging and congruent with the experimental results.
content of financial resources are investing in this sector yearly. In this paper a GMDH-type
neural network and genetic algorithm is developed for stock price prediction of cement sector.
For stocks price prediction by GMDH type-neural network, we are using earnings per share
(EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio
(P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data
of ten cement companies is gathering Tehran stock exchange (TSE) in decennial range
(1999-2008). GMDH type neural network is designed by 80 of the experimental data. For
testing the appropriateness of the modeling, reminder of primary data were entered into the
GMDH network. The results are very encouraging and congruent with the experimental results.-The cement industry is one of the most important and profitable industries in Iran and great
content of financial resources are investing in this sector yearly. In this paper a GMDH-type
neural network and genetic algorithm is developed for stock price prediction of cement sector.
For stocks price prediction by GMDH type-neural network, we are using earnings per share
(EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio
(P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data
of ten cement companies is gathering Tehran stock exchange (TSE) in decennial range
(1999-2008). GMDH type neural network is designed by 80 of the experimental data. For
testing the appropriateness of the modeling, reminder of primary data were entered into the
GMDH network. The results are very encouraging and congruent with the experimental results.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
12_ Fallahi AAM-R358-SF-012211.pdf