Bayesian structural time series for forecasting oil prices
المؤلفون المشاركون
al-Mudirs, Ali Husayn
Kazim, Tasnim H.
المصدر
Ibn al-Haitham Journal for Pure and Applied Science
العدد
المجلد 34، العدد 2 (30 يونيو/حزيران 2021)، ص ص. 100-107، 8ص.
الناشر
جامعة بغداد كلية التربية ابن الهيثم
تاريخ النشر
2021-06-30
دولة النشر
العراق
عدد الصفحات
8
التخصصات الرئيسية
الموضوعات
الملخص EN
There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime.
The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method.
Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq.
Oil prices directly affect the health of the economy.
Thus, it is necessary to forecast future oil price with models adapted for emerging events.
In this article, we study the Bayesian structural time series (BSTS) for forecasting oil prices.
Results show that the price of oil will increase to 156.2$ by There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime.
The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method.
Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq.
Oil prices directly affect the health of the economy.
Thus, it is necessary to forecast future oil price with models adapted for emerging events.
In this article, we study the Bayesian structural time series (BSTS) for forecasting oil prices.
Results show that the price of oil will increase to 156.2$ by 2035.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
al-Mudirs, Ali Husayn& Kazim, Tasnim H.. 2021. Bayesian structural time series for forecasting oil prices. Ibn al-Haitham Journal for Pure and Applied Science،Vol. 34, no. 2, pp.100-107.
https://search.emarefa.net/detail/BIM-1255699
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
al-Mudirs, Ali Husayn& Kazim, Tasnim H.. Bayesian structural time series for forecasting oil prices. Ibn al-Haitham Journal for Pure and Applied Science Vol. 34, no. 2 (2021), pp.100-107.
https://search.emarefa.net/detail/BIM-1255699
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
al-Mudirs, Ali Husayn& Kazim, Tasnim H.. Bayesian structural time series for forecasting oil prices. Ibn al-Haitham Journal for Pure and Applied Science. 2021. Vol. 34, no. 2, pp.100-107.
https://search.emarefa.net/detail/BIM-1255699
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 106-107
رقم السجل
BIM-1255699
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر