Showing 3 results for Crude Oil
Mohammad Najar Firouz Jayi, Bahare Oryani, Mahdi Zolfaqari,
Volume 4, Issue 14 (12-2013)
Abstract
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.
Mrs Nafiseh Behradmehr, Mr Mohsen Mehrara, Mr Mohammad Mazraati, Mr Hadi Dadafarid,
Volume 8, Issue 29 (10-2017)
Abstract
In this paper, risk-premium (the difference between the future prices and expected future spot price) in US crude oil futures market over the period of 1989:1 to 2012: 11 is investigated, and then variability of risk-premium through time is explained. In addition, risk premium in different time horizons of US crude oil futures market is predicted using BVAR and VAR models. The results showed that significantly 10% risk-premium existence in US crude oil futures market is approved for all time horizons (one month, two months, three months and four months), and on the other hand,by comparing RMSE of BVAR and VAR models, the results generally confirmed better predictions of risk premium by BVAR models in comparison with VAR models.
Navid Salek, Morteza Khorsandi,
Volume 13, Issue 47 (5-2022)
Abstract
The price of crude oil is one of the factors affecting economic indicators. Therefore, the prediction of oil prices and the accuracy of the applied methods have always been discussed by economists. In this study, the effect of all effective variables on the supply and demand of crude oil based on McAvoy's competitive theory is investigated, and the supply and demand are estimated using the system of simultaneous equations and conventional statistical methods. Then, using algebraic operations and the assumption of equality of oil supply and demand in the long term, the long-term potential of oil supply and demand is extracted with respect to each of the variables in the model. Based on the results, the world's gross domestic product (GDP) has the greatest impact on oil prices with a demand potential of 0.6039, and the world's military and security tensions have the least impact with a demand potential of –0.0110. After estimating the model, the prediction accuracy of three combined mothod is compared with conventional and single-variable methods of neural network and ARIMA. These three combined methods are: (a) neural network and system of simultaneous equations, (b) ARIMA and system of simultaneous equations, (c) neural network and ARIMA and system of simultaneous equations. The results showed that the combined method of ARIMA and simultaneous equation system provides better reslts for 5-year forecasts while the combined method of neural network and ARIMA and simultaneous equation system shows better results for 10-year forecasts.
