Using mathematical time series models to optimize iraq's oil export predictions

Authors

  • Manar Naji Ghayyib Collage of Engineer, Baghdad university, Baghdad, Iraq Author
  • Farah Alaa Adnan Collage of Science, Baghdad university, Baghdad, Iraq Author
  • Aseel Aboud Jawad University of Information Technology and Communications Bio Medical Informatics college, Baghdad, Iraq Author
  • Halah Qahtan Hamdi Collage of Science, Baghdad university, Baghdad, Iraq Author
  • Marwah Hadi Sabr Abed University of Technology, Computer Engineering, Baghdad, Iraq Author

DOI:

https://doi.org/10.56053/9.S.157

Keywords:

Exports of Iraqi oil, Forecasting, Monthly oil exports, Autocorrelation

Abstract

This study examined and analyzed monthly data on the volume of Iraq's oil exports for the time period (January 2014 to December 2022) using time series models. The prediction values, which revealed that they are reasonably close to the actual series, serve as evidence of the model's correctness. In this paper, we determined from the results of the data analysis in this study that the integrated autoregressive model of the ARIMA moving average (0,1,1) is the best model for representing the data under study after several analysis models are applied to a sample of oil revenues over a nine-year period. The predicted values for the years 2023 and 2024 are then extracted

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Published

2025-02-15

How to Cite

Using mathematical time series models to optimize iraq’s oil export predictions. (2025). Experimental and Theoretical NANOTECHNOLOGY, 9(1), 157-166. https://doi.org/10.56053/9.S.157