Navigating the Dynamics of Brent Crude Oil Prices

decision-making and risk control in the global energy market. This
paper examines the dynamics of Brent Crude Oil prices over the
previous 35 years, utilizing predictive modelling techniques to
project future prices and analyzing historical trends and relationships
with the GDPs of major economies. The statistical methods used in
this paper include the moving average and Pearson correlation
coefficient. While correlation studies show significant positive links
between Brent Crude Oil prices and the GDPs of major economies
like China, Saudi Arabia, Europe, Russia, and the United States,
historical data analysis reveals large price volatility. Highly accurate
price forecasting using LSTM (Long Short-Term Memory)
modelling approaches provides detailed risk management and
decision-making information in the global energy market. The
application of the Neural Network and the ARIMA model shows an
increase in the price of Brent crude oil in the next year, 2024.
Identifying the importance of the Brent crude oil price forecast and
its effect on the international market is highly needed. This paper thus
might help to increase economic growth. These results highlight the
importance of advanced modelling techniques and economic
indicators in managing oil price changes and help make informed
decisions in the energy industry.