This paper proposes an alternative approach based on a genetic algorithm and neural network (GA–NN) for the prediction of the West Texas Intermediate (WTI) crude oil price. Comparative simulation results suggested that the proposed GA–NN approach is better than the baseline algorithms in terms of prediction accuracy and computational efficiency. Mann–Whitney test results indicated that the WTI ...

In this study, a multiscale neural network learning paradigm based on empirical mode decomposition (EMD) is proposed for crude oil price prediction. In this learning paradigm, the original price series are first decomposed into various independent intrinsic mode components (IMCs) with a range of frequency scales. Then the internal correlation structures of different IMCs are explored by neural ...

Futures contract is one of the most important derivatives that is used in financial markets in all over the world to buy or sell an asset or commodity in the future. Pricing of this tool depends on expected price of asset or commodity at the maturity date. According to this, theoretical futures pricing models try to find this expected price in order to use in the futures contract. So in this ar...

Bahrain is a very small oil-exporting country in the Middle East with a fixed exchange rate against the US dollar and has no restricton capital flows. Because its economy evolves around the oil sector, its economy is thought to be vulnerable to oil price movements. It is feared that the recent oil price hike would feed from foreign assets to monetary base and money supply to inflation. Empirica...

We consider whether oil prices can account for business cycle asymmetries. We test for asymmetries based on the Markov switching autoregressive model popularized by Hamilton (1989), using the tests devised by Clements and Krolzig (2000). We select the transformation of the oil price of Lee, Ni and Ratti (1995), based on a linear analysis of the relationship between output growth and the oil pri...

This paper presents a hybrid wavelet support vector machines (WSVM) model that combines both wavelet technique and the SVM model for crude oil price forecasting. Based on the purpose, the main time series was decomposed to some multi-frequently time series by wavelet theory and these time series were imposed as input data to the SVM for forecasting of crude oil price series. To assess the effec...

B etween 1986 and 1998, the price of a barrel of West Texas Intermediate (WTI) oil remained quite stable, fluctuating between $16 and $42 constant 2011-U.S. dollars, with the exception of a brief spike in 1990 at the time of the first Gulf War. In December 1998, the barrel of WTI had reached a low point of $17. Almost 10 years later, in July 2008, the same barrel cost $134. By March 2009, the p...

Acute volatile movements in primary commodity prices have drawn enough interests from empirical researchers. Exports of these commodities account for the bulk of export earnings of developing countries. The traditional demand based framework has been unable to explain the marked deterioration in these prices during 1980s. This paper tries to ascertain the role played by real oil prices in expla...