Brent Oil Price Analysis
A time series analysis and forecasting system for Brent crude oil prices, combining statistical models with event-driven analysis to understand price dynamics and geopolitical impacts.
Overview
A time series analysis and forecasting system for Brent crude oil prices, combining statistical models with event-driven analysis to understand price dynamics and geopolitical impacts.
Problem
Brent crude oil prices are highly volatile and influenced by geopolitical events, supply-demand dynamics, and macroeconomic factors. Accurate forecasting and understanding of price drivers is critical for energy companies, traders, and policymakers.
Dataset
Historical daily Brent crude oil prices spanning multiple decades, enriched with macroeconomic indicators and annotated with major geopolitical events (OPEC decisions, conflicts, sanctions). Data sourced from public financial databases.
Architecture
ARIMA and GARCH models for baseline time series forecasting and volatility modeling. Bayesian change point detection (PyMC) to identify structural breaks in the price series corresponding to major events. Correlation analysis with macroeconomic variables.
Training
Models fitted on rolling windows to simulate real-time forecasting. Change point analysis identifies regime shifts. Impulse response analysis quantifies the price impact and recovery time of specific geopolitical events.
Results
GARCH model captured volatility clustering effectively. Change point detection identified 12 major structural breaks aligned with known geopolitical events. Event impact analysis showed OPEC production cuts have a median price effect of +8% over 30 days.