1
Professor in Faculty of Economics, University of Tehran
2
MA in economics,University of Tehran, Oil company employees.
3
PhD student in economics, Allameh Tabatabaee University.
Abstract
In this paper, a model based on GMDH Type Neural Network, is used to predict gas price in the spot market while using oil spot market price, gas spot market price, gas future market price, oil future market price and average temperature of the weather. The results suggest that GMDH Neural Network model, according to the Root Mean Squared Error (RMSE) and Direction statistics (Dstat) statistics are more effective than OLS method. Also, first lag of gas price in the future market is the most efficient variable in predicting gas price in spot market.
Abrishami,H. , Bourbour,F. and Aghajani,M. (2014). Prediction of Natural Gas Price Using GMDH Type Neural Network:A Case Study of USA Market. The International Journal of Humanities, 21(3), 1-16.
MLA
Abrishami,H. , , Bourbour,F. , and Aghajani,M. . "Prediction of Natural Gas Price Using GMDH Type Neural Network:A Case Study of USA Market", The International Journal of Humanities, 21, 3, 2014, 1-16.
HARVARD
Abrishami H., Bourbour F., Aghajani M. (2014). 'Prediction of Natural Gas Price Using GMDH Type Neural Network:A Case Study of USA Market', The International Journal of Humanities, 21(3), pp. 1-16.
CHICAGO
H. Abrishami, F. Bourbour and M. Aghajani, "Prediction of Natural Gas Price Using GMDH Type Neural Network:A Case Study of USA Market," The International Journal of Humanities, 21 3 (2014): 1-16,
VANCOUVER
Abrishami H., Bourbour F., Aghajani M. Prediction of Natural Gas Price Using GMDH Type Neural Network:A Case Study of USA Market. The International Journal of Humanities, 2014; 21(3): 1-16.
The International Journal of Humanities
