Modelling and forecasting monthly petroleum prices of Ghana using subset ARIMA models

Bachelor Thesis from the year 2012 in the subject Economics - Statistics and Methods, grade: none, language: English, abstract: The study is an attempt to build a univariate Time Series Model to forecast monthly petroleum prices for 2010/2011, from January 1990 to September 2010, since national petroleum agency (NPA) is failing to plan for fluctuation of petroleum prices. The data was source from the website of Bank of Ghana. The study employs Box-Jenkins methodology of building Seasonal Autoregressive Integrated Moving Average (SARIMA) model to achieve various objectives. Different selected models were tested by Residual plots of Autocorrelation and Partial Autocorrelation and Ljung Box Q statistic to ensure adequacy of results. The results reveal that demand and supply, crudel oil prices, gasoline, natural disasters and government regulations are some of factors that can influence fuel prices and ARIMA(1,1,5)×(1,0,1)11 is the best model for forecast. The future values expose that during the months to come; petroleum prices are going to experience an insignificant increase. In light of the forecast, I know Ghana will ascertain a healthy state of economy.