Volume 21, Issue 3 (2014)                   IQBQ 2014, 21(3): 1-16 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Abrishami H, Bourbour F, Aghajani M. Prediction of Natural Gas Price Using GMDH Type Neural Network:A Case Study of USA Market. IQBQ. 21 (3) :1-16
URL: http://eijh.modares.ac.ir/article-27-5139-en.html
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:   (4198 Views)
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.
Full-Text [PDF 300 kb]   (1513 Downloads)    

Received: 2012/12/10 | Accepted: 2014/01/27 | Published: 2015/07/23

Add your comments about this article : Your username or Email: