Abstract
Box-Jenkins modeling approach has been applied for the time series analysis of monthly average prices of Oman crude oil taken over a period of ten years. Basic statistical properties of these series were investigated. The time series plots clearly indicated a non stationary trend which was observed to be first differenced stationary. Sample Auto Correlations (SAC) and Sample Partial Auto Correlations (SPAC) plots were used to make tentative identification of the form and order of Box-Jenkins’ Auto Regressive Integrated Moving Average (ARIMA) models. Initially several seasonal and non seasonal ARIMA models were postulated for further analysis. These models were then estimated and compared for their adequacy based on the significance of the parameter estimates, mean square and Modified Box-Pierce (Ljung-Box) Chi-Square statistic. Based on these criterion a multiplicative seasonal model of the form ARIMA(1,1,5)x(1,1,1) was recommended for short term forecasting.
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