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International crude oil prices volatility has significant effects on global economic activities. On the basis of WTI crude oil futures price of New York Mercantile Exchange (NYMEX) from Apr 1983 to Aug 2008, this paper analyze the multifractal spectrum of crude oil futures prices. The results show that the crude oil prices have multifractal characteristics; international oil futures market has the...
The volatility of the oil future price is extremely complex, therefore an accurate forecasting on oil price is an important and challenging topic. This paper presents a GRNN forecasting model for Brent crude oil price. Careful attention is paid on finding number of features as input data to achieve best performance for model. Also to overcome unforeseen critical conditions, a crisis index is defined...
With the cointegration theory, oil consumption, national economic growth, population, oil price, industrial structure, energy structure and technical progress variables are discussed in this paper. By analyses, it is found that cointegration relationship exist among variables of oil consumption, industrial structure, energy structure and technical progress. The error correction model about oil consumption...
This paper presents a neuro-based approach for Iran annual gasoline demand forecasting by several socio-economic indicators. In order to analyze the influence of economic and social indicators on the gasoline demand, the gross domestic product (GDP), the population and the total number of vehicles are selected. This approach is structured as a multi-level artificial neural network (ANN) based on supervised...
Grey prediction method is characterized by small amount data, simple calculation and accurate prediction. On the basis of WTI crude oil futures monthly price of New York Mercantile Exchange (NYMEX) from June 2008 to Feb 2009, this paper gives a grey prediction model of intentional crude oil prices. The results show that the model of GM (1,1) is suitable for crude oil prices forecast. It predicts that...
The fluctuation of oil prices attracts the great attention of the world. However, the prediction of oil prices is very difficult because the oil price system is so complex. In this paper, AR-GMDH algorithm and AC algorithm are adopted to forecast oil prices. The validity and feasibility of self-organizing data mining are manifested by the comparisons of the prediction result with that of conventional...
Understanding of market efficiency is the cornerstone of market analysis. Oil market efficiency test can not only provide the theoretical foundation for oil price forecast but offer evidence of comparing the information efficiency of different markets. The generalized spectrum method is applied on the daily data from January 2001 to July 2008 to test the weak form efficiency of main crude oil markets...
Grey theory is a multidisciplinary and generic theory to cope with systems of poor or deficient information. In this paper, at first a new grey-based model MGM(1, n, m)is proposed based on the general MGM(1, n) forecasting model to deal with the forecasting problems of input-output systems. Then the efficiency and accuracy of this model is tested by applying it to the dynamic forecasting problem of...
In this study, a generalized Intelligent-agent-based fuzzy group forecasting model is proposed for oil price prediction. In the proposed model, some single Intelligent-agent-based predictors with much disagreement are first created for crude oil price prediction. Then these single prediction results produced by these single intelligent predictors are fuzzified into some fuzzy prediction representations...
The volatility of the oil futures price is extremely complex with its nonlinear and high noise. Therefore, an accurate forecasting on oil futures price is an important and challenging topic. In this study, a new model for oil futures price forecasting based on cluster analysis is proposed. The complex forecasting problem is divided into simpler problems in the presented model. The whole input space...
This paper makes a prediction of Chinapsilas energy consumption in 2015. The assumption in this paper is established as that urbanization, industrial GDP and energy pricing indices are independent variables. With this hypothesis we select time as a single independent variable to make forecasting of these variables. In the paper, we firstly predict these variables with time series method and the tool...
In this study, a Al-agent-based trapezoidal fuzzy ensemble forecasting model is proposed for crude oil price prediction. In the proposed ensemble model, some single AI models are first used as predictors for crude oil price prediction. Then these single prediction results produced by the single Al-based predictors are fuzzified into some fuzzy prediction representations. Subsequently, these fuzzified...
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