Modelling and forecasting Oman crude oil prices using Box-Jenkins techniques
International Journal of Trade and Global Markets
This paper used Box-Jenkins Techniques in Modelling and Forecasting Nigeria Crude Oil Prices obtained from 1982 to 2013 from the Central Bank of Nigeria's website. The descriptive statistics obtained showed, among other statistics, the mean to be 40.63USD/Barrel with a standard deviation of 32.28. The Augmented Dickey -Fuller test revealed that the time series data was unit root non-stationary. First order differencing was done to coerce the non-stationary time series into a stationary one -a
... stationary one -a condition that allowed the use of the univariate Box-Jenkins modelling approach. The time series, the ACF and the PACF plots of the first order difference of the crude oil price data suggested ARIMA(6,1,7). It was discovered that a lot of the model parameters was redundant hence settling for only statistically significant parameters of the model resulted to fitting ARIMA( 2,1,2) which led to a reduced and parsimonious model. From the diagnostic plots, an overall consistency with the white noise process was noticed. The paper further compared the two models on the basis of their information criterion statistics and ARIMA (2, 1,2) fared better and was used to make forecast. Comparison of the actual/observed prices from January to July 2014 was done with their corresponding forecast values and a t-test of significance showed no significant difference. The motivation is derived from the fact that reliable and adequate estimates of crude oil prices are very essential for planning and policy-making by not only the government but international agencies as well.