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Modelling and forecasting monthly petroleum prices of Ghana using subset ARIMA models (Paperback)
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Modelling and forecasting monthly petroleum prices of Ghana using subset ARIMA models (Paperback)
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Bachelor Thesis from the year 2012 in the subject Economics -
Statistics and Methods, grade: none, - (University for Development
Studies, Tamale), 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)x(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.
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