It is of real and direct significance for China to cope with oil price fluctuations and ensure oil security. This paper aims to quantitatively analyze the specific contribution ratios of the complex factors influencin...It is of real and direct significance for China to cope with oil price fluctuations and ensure oil security. This paper aims to quantitatively analyze the specific contribution ratios of the complex factors influencing international crude oil prices and to establish crude oil price models to forecast long-term international crude oil prices. Six explanatory influential variables, namely Dow Jones Indexes, the Organization for Economic Cooperation and Development oil stocks, US rotary rig count, US dollar index, total open interest, which is the total number of outstanding contracts that are held by market participants at the end of each day, and geopolitical instability are specified, and the samples, from January 1990 to August 2017, are divided into six sub-periods. Moreover, the co-integration relationship among variables shows that the contribution ratios of all the variables influencing Brent crude oil prices are in accordance with the corresponding qualitative analysis. Furthermore, from September 2017 to December 2022 outside of the sample, the Vector Autoregressive forecasts show that annually averaged Brent crude oil prices for 2017-2022 would be $53.0, $61.3, $74.4, $90.0, $105.5, and $120.7 per barrel, respectively. The Vector Error Correction forecasts show that annual average Brent crude oil prices for 2017-2022 would be $53.0, $56.5, $58.5, $60.7, $63.0 and $65.4 per barrel, respectively.展开更多
Forecasts can either be short term, medium term or long term. In this work we considered short term forecast because of the problem of limited data or time series data that is often encounter in time series analysis. ...Forecasts can either be short term, medium term or long term. In this work we considered short term forecast because of the problem of limited data or time series data that is often encounter in time series analysis. This simulation study considered the performances of the classical VAR and Sims-Zha Bayesian VAR for short term series at different levels of collinearity and correlated error terms. The results from 10,000 iteration revealed that the BVAR models are excellent for time series length of T=8 for all levels of collinearity while the classical VAR is effective for time series length of T=16 for all collinearity levels except when ρ = -0.9 and ρ = -0.95. We therefore recommended that for effective short term forecasting, the time series length, forecasting horizon and the collinearity level should be considered.展开更多
基金supported by the National Science Foundation of China(NSFC No.41271551/71201157)the National Key Research and Development Program(2016YFA0602700)
文摘It is of real and direct significance for China to cope with oil price fluctuations and ensure oil security. This paper aims to quantitatively analyze the specific contribution ratios of the complex factors influencing international crude oil prices and to establish crude oil price models to forecast long-term international crude oil prices. Six explanatory influential variables, namely Dow Jones Indexes, the Organization for Economic Cooperation and Development oil stocks, US rotary rig count, US dollar index, total open interest, which is the total number of outstanding contracts that are held by market participants at the end of each day, and geopolitical instability are specified, and the samples, from January 1990 to August 2017, are divided into six sub-periods. Moreover, the co-integration relationship among variables shows that the contribution ratios of all the variables influencing Brent crude oil prices are in accordance with the corresponding qualitative analysis. Furthermore, from September 2017 to December 2022 outside of the sample, the Vector Autoregressive forecasts show that annually averaged Brent crude oil prices for 2017-2022 would be $53.0, $61.3, $74.4, $90.0, $105.5, and $120.7 per barrel, respectively. The Vector Error Correction forecasts show that annual average Brent crude oil prices for 2017-2022 would be $53.0, $56.5, $58.5, $60.7, $63.0 and $65.4 per barrel, respectively.
文摘Forecasts can either be short term, medium term or long term. In this work we considered short term forecast because of the problem of limited data or time series data that is often encounter in time series analysis. This simulation study considered the performances of the classical VAR and Sims-Zha Bayesian VAR for short term series at different levels of collinearity and correlated error terms. The results from 10,000 iteration revealed that the BVAR models are excellent for time series length of T=8 for all levels of collinearity while the classical VAR is effective for time series length of T=16 for all collinearity levels except when ρ = -0.9 and ρ = -0.95. We therefore recommended that for effective short term forecasting, the time series length, forecasting horizon and the collinearity level should be considered.
