استعمال إنموذج الانحدار الذاتي المعمم المشروط بعدم تجانس التباين (GARCH (p,q في تمثيل بيانات السلاسل الزمنية و استخدامها في التنبؤ مع تطبيق عملي على الأسعار اليومية العالمية للنفط

الملخص EN

Using the Generalized Auto-Regression that conditioned by Heteroscedasticity in representing the time series data and its using in predicting with GARCH (p, q): Case study of daily global oil prices Assist.

Lecturer.

Ali abdal-Zahra HuseenUniversity of BasrahDepartment of StatisticsFaculty of Administration and Economics ARCH and GARCH models have become important tools in the analysis of time series data, particularly in financial applications.

These models are especially useful when the objectiveof the study is to analyze and forecast volatility.

The research aims to build an appropriate model that explains the behavior of the daily series of international oil prices using the GARCH models because it takes into consideration the returns during periods of trading as well as volatility and is considered a measure of risk.

The results of the study showed that the appropriate model of this series, GARCH (1.1)