VaR, Expected Shortfall, and Stress Testing in Commodities
Value-at-Risk and Expected Shortfall for commodity portfolios; stress scenarios; backtesting
VaR, Expected Shortfall, and Stress Testing in Commodities
Executive Summary
Value at Risk answers: "If I hold this position for one day, how much could I lose with 95% confidence?" Stress testing answers: "If oil crashes 50%, how much would this portfolio lose?" Tail risk asks: "What is the maximum expected loss in a 1-in-100-year event?" These questions sit at the centre of energy risk management. After 2008, many firms learned that "low-risk" hedges could produce huge losses when risk models failed to capture tail scenarios. This module covers VaR methods, their limits, stress testing, scenario analysis, and how to use them for limits and capital. For practitioners and consultants, mastery supports risk measurement and regulatory compliance—and supports book and consulting value.
Learning Objectives
By the end of this module you will be able to calculate Value at Risk (VaR) using historical, parametric, and Monte Carlo methods, understand VaR limitations and complementary risk measures, design and interpret stress tests for energy portfolios, evaluate scenario analysis for worst-case outcomes, and implement risk limits and capital allocation frameworks using VaR/stress testing.