Forecasting Brent Crude Prices with AI and ML
In this whitepaper, released in early January 2016, we tackle the challenge of predicting Brent Crude prices using Artificial Intelligence and Machine Learning techniques. With significant fluctuations in crude oil prices during 2015, the paper presents a data-driven approach to uncover hidden relationships between factors influencing oil prices and forecasting future trends.
The approach combines historical price data and fundamental factors like Real GDP, production levels, supply and consumption patterns, and inventory levels to model price discovery. Using decision forests and multiple regression models, the analysis demonstrates the potential of AI/ML in commodity price prediction.
This paper introduces a machine learning-based model for crude oil price prediction and provides insights into the factors affecting price discovery:
Additionally, the whitepaper explores the stages of building an ML prediction model, offering readers a glimpse into the power of Big Data Analytics and Machine Learning for solving complex forecasting problems.
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