A PRACTICAL RISK ANALYSIS OF THE BRENT OIL PRICES

Abstract

This research investigates three approaches to determine the best model for identifying risk in Brent oil prices: Value at Risk, Monte Carlo Simulations, and Conditional Value At Risk (CVaR).The study also aims to contribute to the literature by examining whether it is possible to measure risk in advance for Brent oil prices and compares the performance of various risk measurement models to determine the best-performing method in measuring risk.Our findings show that the VaR model underestimated risk at the 95% confidence level. This may be due to the non-normal distribution of returns. Our results on conditional value at risk (CVaR) indicate that CVaR produced superior results compared to VaR in cases where the distribution of returns was highly skewed or had fat tails. This is because the expected shortfall measure takes into account expected loss beyond the VaR threshold.