DEVELOPMENT OF A NEW NUMERICAL MODEL OF DYNAMIC HARMONIC REGRESSION FOR THE FORECAST OF SELLING FUEL PRICE IN THE MOROCCAN PETROLEUM SECTOR

IF 0.8 Q4 ENGINEERING, INDUSTRIAL

Acta Logistica Pub Date : 2022-06-30 DOI:10.22306/al.v9i2.290

Younes Fakhradine El Bahi, L. Ezzine, Zineb Aman, Haj El Moussami

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Abstract

The liberalization of the petroleum sector in Morocco has a significant effect for petroleum product distributors. Since the beginning of December 2015, fuel prices are freely determined. This event presents many constraints affecting the balance of the sector plus the competition among its economic players. As all fuel products are imported, we will be interested in the evolution by making forecasts of the price of fuels in the Moroccan market. In this context, our paper aims mainly to study the time series of diesel and gasoline in order to provide precise forecasts to the company and to respect the permissible error margin of 3%. To this end, the harmonic dynamic regression model through the proposed process approach yielded excellent forecasting results for the first quarter of 2017 with an average error margin of 1.617%. Compared to ARIMA model, the harmonic dynamic regression proves its strength manifested in the low rate of error. In addition, the assumption that the residuals are a Gaussian white noise has always been verified. The forecasts obtained are very crucial for managers to take good decisions at the strategic level.

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摩洛哥石油行业销售燃料价格预测的动态调和回归新数值模型的开发

摩洛哥石油部门的自由化对石油产品分销商产生了重大影响。自2015年12月初以来，燃料价格是自由决定的。这一事件带来了许多制约因素，影响了该行业的平衡及其经济参与者之间的竞争。由于所有燃料产品都是进口的，我们将通过预测摩洛哥市场的燃料价格来对其演变感兴趣。在此背景下，我们的论文主要研究柴油和汽油的时间序列，以便为公司提供准确的预测，并遵守3%的允许误差范围。为此，通过所提出的过程方法，谐波动态回归模型在2017年第一季度取得了良好的预测结果，平均误差率为1.617%。与ARIMA模型相比，谐波动态预测模型的优势在于误差率低。此外，残差是高斯白噪声的假设一直得到验证。所获得的预测对于管理者在战略层面做出良好决策至关重要。

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