Selection of the Best Oil Price Forecasting Model in the Iraqi Economy

The ARIMA model provides a relatively sophisticated approach to time series prediction, capable of realistically describing dynamic patterns of change. This model is suitable for statistical analysis and chronological forecasting under specific circumstances. Based on our results from EViews ۹, we observe that it facilitates effective time series modeling and forecasting using the ARIMA methodology. It is important to note that, for a specific time series, predictions are influenced by numerous factors. Predictions based solely on current values and historical data may sometimes deviate from actual outcomes. The Box-Jenkins ARIMA methodology, which relies on degrees of autoregression, integration, and moving averages, has been employed to predict Iraqi oil prices under both global and local conditions. This methodology was instrumental in constructing the time series model and selecting the most accurate model to forecast Iraqi oil prices for the period ۲۰۲۴–۲۰۳۵. The best forecasting model identified is ARIMA (۱,۱,۱), which predicts a rise in oil prices during the research period.

کلیدواژه ها:

Iraqi oil prices ، prediction ، autoregression ، degree of integration ، moving averages