FRM Part II · FRM Exam Part II · Case Study: Model Risk and Model Validation
Two models, A and B, price the same loan portfolio. Both pass backtesting, but they give materially different fair values because each rests on a different, plausible assumption set, and no data can distinguish between them. This situation is best described as:
This is model specification, or model uncertainty, risk. Several plausible model forms fit the available evidence equally well yet give materially different values, so the true model cannot be identified from data and the choice itself creates risk.
- AModel specification (uncertainty) riskCorrect
- BArithmetic coding risk
- CStale data risk
- DRounding risk
Explanation
When several plausible specifications fit the evidence equally and give different results, the risk comes from uncertainty about the correct model form. Coding, data staleness and rounding are not the cause here.
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