FORECASTING GRAIN EXPORTS THROUGH UKRAINE'S PORTS BASED ON THE ARIMA MODEL

Ukraine is one of the leading global exporters of grain, making it a pivotal player in the international agricultural market. Grain exports hold substantial economic importance, particularly given the high dependency of the agricultural sector on global prices, transportation infrastructure, and external factors such as political instability and armed conflicts. In the context of dynamic changes in global trade and increasing international competition, the need for accurate, timely forecasting of grain export volumes becomes essential for effective management of logistics processes and ensuring stable supply to global markets.This article explores a method for forecasting grain exports through Ukraine’s ports based on the ARIMA model, recognized as one of the most effective approaches for time-series analysis. The study employs time-series theory, the EViews 12 software, and statistical data on historical grain export volumes. The research includes an evaluation of the model’s adequacy, residual diagnostics, and the development of short- and medium-term forecasts. The findings demonstrate that the ARIMA model delivers highly accurate forecasts, proving its adaptability to volatile conditions and data variability. The projected grain export volumes can serve as a foundation for optimizing logistics planning, inventory management, and supply chain strategies—critical components for ensuring stability and competitiveness in Ukraine’s grain export sector. The study's conclusions hold significant practical relevance for agricultural companies, logistics operators, and governmental institutions. Reliable forecasts empower these stakeholders to make informed decisions regarding resource allocation, supply chain optimization, and strategic planning. This is particularly vital in mitigating risks associated with external disruptions and maintaining Ukraine’s status as a dependable supplier in the global grain market.Moreover, the research underscores the ARIMA model's utility in addressing challenges posed by the rapidly changing global trade environment and geopolitical uncertainties. By leveraging such robust forecasting tools, stakeholders can enhance operational efficiency and strengthen their competitive positioning in international markets. The insights presented in this article contribute to advancing methodologies for forecasting and provide a strategic framework for navigating the complexities of modern grain export logistics.