Author: United States. Bureau of Mines
Publisher:
ISBN:
Category :
Languages : en
Pages : 458
Book Description
Monthly Petroleum Forecast
Author: United States. Bureau of Mines
Publisher:
ISBN:
Category :
Languages : en
Pages : 458
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 458
Book Description
Monthly Petroleum Forecast
Author: United States. Bureau of Mines
Publisher:
ISBN:
Category :
Languages : en
Pages : 522
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 522
Book Description
Weekly Petroleum Status Report
Author:
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 32
Book Description
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 32
Book Description
Short-term Energy Outlook
Modelling and forecasting monthly petroleum prices of Ghana using subset ARIMA models
Author: Francis Okyere
Publisher: GRIN Verlag
ISBN: 3656483620
Category : Business & Economics
Languages : en
Pages : 110
Book Description
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.
Publisher: GRIN Verlag
ISBN: 3656483620
Category : Business & Economics
Languages : en
Pages : 110
Book Description
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.
Forecasting Accuracy of Crude Oil Futures Prices
Author: Mr.Manmohan S. Kumar
Publisher: International Monetary Fund
ISBN: 1451951116
Category : Business & Economics
Languages : en
Pages : 54
Book Description
This paper undertakes an investigation into the efficiency of the crude oil futures market and the forecasting accuracy of futures prices. Efficiency of the market is analysed in terms of the expected excess returns to speculation in the futures market. Accuracy of futures prices is compared with that of forecasts using alternative techniques, including time series and econometric models, as well as judgemental forecasts. The paper also explores the predictive power of futures prices by comparing the forecasting accuracy of end-of-month prices with weekly and monthly averages, using a variety of different weighting schemes. Finally, the paper investigates whether the forecasts from using futures prices can be improved by incorporating information from other forecasting techniques.
Publisher: International Monetary Fund
ISBN: 1451951116
Category : Business & Economics
Languages : en
Pages : 54
Book Description
This paper undertakes an investigation into the efficiency of the crude oil futures market and the forecasting accuracy of futures prices. Efficiency of the market is analysed in terms of the expected excess returns to speculation in the futures market. Accuracy of futures prices is compared with that of forecasts using alternative techniques, including time series and econometric models, as well as judgemental forecasts. The paper also explores the predictive power of futures prices by comparing the forecasting accuracy of end-of-month prices with weekly and monthly averages, using a variety of different weighting schemes. Finally, the paper investigates whether the forecasts from using futures prices can be improved by incorporating information from other forecasting techniques.
Monthly Petroleum Statistics Report
Author:
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 16
Book Description
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 16
Book Description
Monthly Energy Review
Author:
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 544
Book Description
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 544
Book Description
Energy Information Administration Weekly Petroleum Status Report
Author:
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 612
Book Description
Publisher:
ISBN:
Category : Petroleum industry and trade
Languages : en
Pages : 612
Book Description
Do High-frequency Financial Data Help Forecast Oil Prices?
Author: Christiane Baumeister
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 0
Book Description
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency real-time VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil.
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 0
Book Description
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency real-time VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil.