Assessing the price gap model for Brent’s crude oil and gasoline implementing econometrics methods, neural networks and wavelet transformation

Najar Firouz Jayi, mohammad; Oryani, Bahare; Zolfaqari, Mahdi

Volume 4, Issue 14 (12-2013) jemr 2013, 4(14): 25-58 | Back to browse issues page

‎ 20.1001.1.22286454.1392.4.14.2.3

Mendeley

Zotero

RefWorks

Najar Firouz Jayi M, Oryani B, Zolfaqari M. Assessing the price gap model for Brent’s crude oil and gasoline implementing econometrics methods, neural networks and wavelet transformation. jemr 2013; 4 (14) :25-58
URL: http://jemr.khu.ac.ir/article-1-565-en.html

Assessing the price gap model for Brent’s crude oil and gasoline implementing econometrics methods, neural networks and wavelet transformation

Mohammad Najar Firouz Jayi

, Bahare Oryani ^*

¹, Mahdi Zolfaqari

1- Institute for trade studies and researchCommerce department , b_oryani2004@yahoo.com

Abstract: (8186 Views)

This report investigates the dominant factors influencing the price gap and the symmetry principle’s evaluation between the crude oil’s price and gasoline. In this regard, the Brent’s crude oil price, gasoline price in six European countries and the fluctuations of the euro vs. US dollar’s exchange rate over the period of 1/1/1999 to 8/25/2011 in weekly intervals are studied. For this purpose, linear models and nonlinear models, such as artificial neural network and wavelet transformation, are implemented. The results indicate insignificant impact of the mentioned parameters in short period price gap both for linear and nonlinear simulations, but nonlinear modeling explicates 92% of long period fluctuations in price gap. According to linear/nonlinear models the symmetry principle is accepted for short period fluctuations in crude oil’s price, but not for long periods.

Keywords: Crude oil, gasoline, linear modeling (panel data modeling), artificial neural network, wavelet transformation.

Full-Text [PDF 341 kb] (2488 Downloads)

Type of Study: Applicable | Subject: انرژی، منابع و محیط زیست
Received: 2012/10/19 | Accepted: 2013/11/16 | Published: 2014/08/13