The loss on a credit portfolio not expected to be exceeded at a given confidence level over a horizon. It captures default correlation and concentration.
Where you will meet it
Credit VaR comes up in 12 learning outcome notes across the FRM syllabus.
A few of them:
External and Internal Credit Ratings FRM Part I · Valuation and risk models
“Matrices are used to build default probability term structures, to simulate migration for credit VaR and to price credit risk.”
Credit Risk Management FRM Part II · Credit risk measurement and management
“Unexpected loss is the variability of losses around that average, which a simplified model measures as a standard deviation, whereas a quantile-based capital measure is credit VaR at a stated confidence level minus EL, a different quantity.”
Estimating Default Probabilities FRM Part II · Credit risk measurement and management
“Forecasting future losses, calculating expected loss for provisioning, credit VaR, stress testing and economic or regulatory capital need real-world probabilities.”
Credit Value at Risk FRM Part II · Credit risk measurement and management
“Market VaR and credit VaR answer the same question, how much could we lose at a given confidence level, but they are built differently.”
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