Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches
This study introduces a set of multivariate models with the aim of forecasting global prices of 1) crude oil, 2) natural gas, 3) iron ore, and 4) steel. Various versions of vector autoregression and error-correction models are applied to monthly data for the short-term prediction of nominal commodit...
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| Format: | Article |
| Language: | English |
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National Bank of Ukraine
2022-12-01
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| Series: | Visnyk of the National Bank of Ukraine |
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| Online Access: | https://journal.bank.gov.ua/en/article/2022/254/02 |
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| author | Diana Balioz |
| author_facet | Diana Balioz |
| author_sort | Diana Balioz |
| collection | DOAJ |
| description | This study introduces a set of multivariate models with the aim of forecasting global prices of 1) crude oil, 2) natural gas, 3) iron ore, and 4) steel. Various versions of vector autoregression and error-correction models are applied to monthly data for the short-term prediction of nominal commodity prices six months ahead, and to examine forecast accuracy. The fundamentals for metal and energy price predictions include inter alia, stock changes, changes in commodity production volumes, export volumes by the largest players, changes in the manufacturing sector of the largest consumers, the state of global real economic activity, freight rates, recession, and so on. Kilian's (2009) index of global real economic activity is found to be a useful proxy for global demand and a reliable input in forecasting both energy and metal prices. The findings suggest that models with smaller lag orders tend to outperform those with a higher number of lags. At the same time, selected individual models, while showing a standalone high performance, have varying forecast precision during different periods, and no individual model outperforms others consistently throughout the forecast horizon. |
| format | Article |
| id | doaj-art-c53ad5202bd4438b89378f895784a467 |
| institution | Kabale University |
| issn | 2414-987X |
| language | English |
| publishDate | 2022-12-01 |
| publisher | National Bank of Ukraine |
| record_format | Article |
| series | Visnyk of the National Bank of Ukraine |
| spelling | doaj-art-c53ad5202bd4438b89378f895784a4672025-01-27T10:23:56ZengNational Bank of UkraineVisnyk of the National Bank of Ukraine2414-987X2022-12-01254152810.26531/vnbu2022.254.02Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM ApproachesDiana Balioz0National Bank of UkraineThis study introduces a set of multivariate models with the aim of forecasting global prices of 1) crude oil, 2) natural gas, 3) iron ore, and 4) steel. Various versions of vector autoregression and error-correction models are applied to monthly data for the short-term prediction of nominal commodity prices six months ahead, and to examine forecast accuracy. The fundamentals for metal and energy price predictions include inter alia, stock changes, changes in commodity production volumes, export volumes by the largest players, changes in the manufacturing sector of the largest consumers, the state of global real economic activity, freight rates, recession, and so on. Kilian's (2009) index of global real economic activity is found to be a useful proxy for global demand and a reliable input in forecasting both energy and metal prices. The findings suggest that models with smaller lag orders tend to outperform those with a higher number of lags. At the same time, selected individual models, while showing a standalone high performance, have varying forecast precision during different periods, and no individual model outperforms others consistently throughout the forecast horizon.https://journal.bank.gov.ua/en/article/2022/254/02forecastingvarforecast evaluationcommoditiesvecms |
| spellingShingle | Diana Balioz Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches Visnyk of the National Bank of Ukraine forecasting var forecast evaluation commodities vecms |
| title | Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches |
| title_full | Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches |
| title_fullStr | Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches |
| title_full_unstemmed | Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches |
| title_short | Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches |
| title_sort | short term forecasting of global energy and metal prices var and vecm approaches |
| topic | forecasting var forecast evaluation commodities vecms |
| url | https://journal.bank.gov.ua/en/article/2022/254/02 |
| work_keys_str_mv | AT dianabalioz shorttermforecastingofglobalenergyandmetalpricesvarandvecmapproaches |