Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques
The characteristics of crude oil and the factors affecting the price of this energy carrier have made its price forecast always considered by researchers, oil market participants, governments, and policymakers. Because the price of crude oil is affected by many factors, ongoing studies should be don...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | fas |
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Allameh Tabataba'i University Press
2020-09-01
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| Series: | Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān |
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| Online Access: | https://jiee.atu.ac.ir/article_13729_11bd5c27bb90bb4965a6a245fc4922a8.pdf |
| _version_ | 1797369222445137920 |
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| author | Hossein Yadegari Teymour Mohamadi Hamid Amadeh abdorrasoul ghasemi, hamidreza mostafaee |
| author_facet | Hossein Yadegari Teymour Mohamadi Hamid Amadeh abdorrasoul ghasemi, hamidreza mostafaee |
| author_sort | Hossein Yadegari |
| collection | DOAJ |
| description | The characteristics of crude oil and the factors affecting the price of this energy carrier have made its price forecast always considered by researchers, oil market participants, governments, and policymakers. Because the price of crude oil is affected by many factors, ongoing studies should be done to make more accurate and reliable estimates over time. In this paper, a combination of GM (1,1) and ARIMA models and a hybrid model (GM-ARIMA) for crude oil price forecasting is proposed. The Brent crude oil price data for seasonal (2015Q1-2021Q2), monthly(2020m3-2020m12), and weekly(w12-2020: w16-2021) periods were used to examine this method. The results show that based on the evaluation criteria of mean absolute error percentage (MAPE) and square mean square error (RMSE), the evaluation criteria of MAPE and RMSE in the combined GM-ARIMA model are always lower than the GM and ARIMA models alone. Therefore, the GM-ARIMA hybrid model will be able to predict more accurately than the GM and ARIMA models. Therefore, for more accurate prediction, the GM-ARIMA hybrid model can be used instead of single models. |
| first_indexed | 2024-03-08T17:43:30Z |
| format | Article |
| id | doaj.art-177bfb02fc124e24b5654214303b713f |
| institution | Directory Open Access Journal |
| issn | 2423-5954 2476-6437 |
| language | fas |
| last_indexed | 2024-03-08T17:43:30Z |
| publishDate | 2020-09-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān |
| spelling | doaj.art-177bfb02fc124e24b5654214303b713f2024-01-02T10:49:18ZfasAllameh Tabataba'i University PressPizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān2423-59542476-64372020-09-0193614917110.22054/jiee.2022.62826.186213729Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics TechniquesHossein Yadegari0Teymour Mohamadi1Hamid Amadeh2abdorrasoul ghasemi,3hamidreza mostafaee4Ph.D. Student in Oil and Gas Economics, Allameh Tabataba’i University, Tehran, IranAssociate Professor of Economics, Allameh Tabataba’i University, Tehran, IranyAssociate Professor, Department of Energy Economics, Allameh Tabataba’i University, Tehran, IranAssociate Professor, Department of Energy Economics, Allameh Tabataba’i University, Tehran, IranAssociate Professor, Department of Statistics, North Tehran Branch, Islamic Azad University, Tehran, IranThe characteristics of crude oil and the factors affecting the price of this energy carrier have made its price forecast always considered by researchers, oil market participants, governments, and policymakers. Because the price of crude oil is affected by many factors, ongoing studies should be done to make more accurate and reliable estimates over time. In this paper, a combination of GM (1,1) and ARIMA models and a hybrid model (GM-ARIMA) for crude oil price forecasting is proposed. The Brent crude oil price data for seasonal (2015Q1-2021Q2), monthly(2020m3-2020m12), and weekly(w12-2020: w16-2021) periods were used to examine this method. The results show that based on the evaluation criteria of mean absolute error percentage (MAPE) and square mean square error (RMSE), the evaluation criteria of MAPE and RMSE in the combined GM-ARIMA model are always lower than the GM and ARIMA models alone. Therefore, the GM-ARIMA hybrid model will be able to predict more accurately than the GM and ARIMA models. Therefore, for more accurate prediction, the GM-ARIMA hybrid model can be used instead of single models.https://jiee.atu.ac.ir/article_13729_11bd5c27bb90bb4965a6a245fc4922a8.pdfcrude oil pricecrude oil price forecastgm grey modelarima modelgm-arima hybrid model |
| spellingShingle | Hossein Yadegari Teymour Mohamadi Hamid Amadeh abdorrasoul ghasemi, hamidreza mostafaee Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān crude oil price crude oil price forecast gm grey model arima model gm-arima hybrid model |
| title | Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques |
| title_full | Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques |
| title_fullStr | Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques |
| title_full_unstemmed | Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques |
| title_short | Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques |
| title_sort | brent crude oil price forecasting by combining grey theory and econometrics techniques |
| topic | crude oil price crude oil price forecast gm grey model arima model gm-arima hybrid model |
| url | https://jiee.atu.ac.ir/article_13729_11bd5c27bb90bb4965a6a245fc4922a8.pdf |
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