Modelling and forecasting monthly petroleum prices of Ghana using subset ARIMA models
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Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
Paperback. 110 pages. Dimensions: 8.3in. x 5.8in. x 0.3in.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 20102011, 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. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN.

Lieferung aus: Schweiz, Versandfertig innert 4 - 7 Werktagen.
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. Taschenbuch, 11.09.2013.

Lieferung aus: Österreich, zzgl. Versandkosten.
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. 11.09.2013, Taschenbuch.

Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Versandkostenfrei.
Von Händler/Antiquariat, The Book Depository EURO [60485773], London, United Kingdom.
Language: English Brand New Book ***** Print on Demand *****.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.

Lieferung aus: Deutschland, Versandkostenfrei.
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. Englisch, Taschenbuch.

Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Titel. Neuware - 108 pp. Englisch.

Von Händler/Antiquariat, English-Book-Service - A Fine Choice [1048135], Waldshut-Tiengen, Germany.
This item is printed on demand for shipment within 3 working days.

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