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Applying Statistical Models to International Crude Oil Price Forecasting

Author: HuangGuanWei
Tutor: CaiJun
School: Xiamen University
Course: Applied Computer Technology
Keywords: Crude oil prices ARIMA Neural Networks Markov regime switching model
CLC: F407.22
Type: Master's thesis
Year: 2008
Downloads: 330
Quote: 5
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Abstract


Some meaningful attempt to utilize some of the basic methods of statistical models and intelligent model in the field of crude oil price forecast from the angle of the time series analysis , the main work is summarized as follows . First, the article describes the factors that influence the price of crude oil and crude oil price analysis , forecast , general and futures arbitrage trading technical analysis method applied to the crude oil futures trading , which is more commonly used trading rules were analog . Secondly, this defect lack a solid mathematical theoretical basis for general technical analysis , using time series analysis of the most commonly used , is also one of the most important model summation autoregressive moving average model (ARIMA) crude oil price series initial mathematical analysis and calculation ; on this basis , we take into account the non-linear fitting ability of artificial neural network (ANN) , ARIMA model from the residuals of the ANN training , selected to fit within a certain range and predict the optimal structure of ANN . Subsequently, using ARIMA and ANN combination forecasting crude oil prices , the experimental results show that the combination of ANN and ARIMA models predict results better than their separate forecast results . Finally , from the point of view of the structural transformation (Regime Switching) , the crude oil price series established state any variable of the second-order autoregressive Markov regime switching model ( Markov Regime Switching Model ) , and using the model of the crude oil price time series analysis and forecasting . Experimental results show that the accuracy of model predictions than the ARIMA model and ANN model , but lower than the forecast of a combination of both . Finally, the work can be carried out next prospect .

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CLC: > Economic > Industrial economy > Industrial economic theory > Industrial sector economy > Energy industry,power industry > Oil and gas industry
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