Leveraging Data Analytics and Transformer Neural Networks for Predictive Oil Price Forecasting

Abstract

In the ever-changing world of the oil industry, the ability to predict oil prices accurately and promptly is vital for participants in various fields like energy, finance, and policy formulation for governments. This paper presents an innovative method that utilizes data analytics and the advanced capabilities of Transformer neural networks to improve the accuracy of predictions regarding oil prices. I utilize extensive historical data, including the cost of crude oil, output levels, geopolitical incidents, and economic indexes, applying thorough data processing techniques for the quality and relevance of the data. I utilized Transformer neural networks to process sequential data, for modeling the complex forces and relationships that affect the oil market.