FRM Part II · FRM Exam Part II · Validating Bank Holding Companies' Value-at-Risk Models for Market Risk
A bank's validation team runs a sensitivity analysis on its VaR model. A 99% one-day VaR is USD 10.0 million using a 250-day window. When the window is shortened to 60 days, VaR rises to USD 14.0 million; when it is lengthened to 500 days, VaR falls to USD 9.0 million. Which conclusion is best supported?
VaR is 40% higher with the 60-day window and 10% lower with the 500-day window, showing material sensitivity to the data window. The bank should justify its window choice. A lower longer-window VaR is not inherently wrong, and the largest figure is not automatically the best.
- AThe model is insensitive to the window, since all results are positive
- BThe model is quite sensitive to the data window, with VaR 40% higher for the short window and 10% lower for the long one, so the window choice needs justificationCorrect
- CThe model is wrong because the 500-day VaR is below the 250-day VaR
- DThe 60-day result should be adopted because it is the largest and so always conservative
Explanation
Short window: (14-10)/10 = 40% increase. Long window: (9-10)/10 = 10% decrease. A swing of this size shows material dependence on the window, which the bank should justify, for example by recent volatility regimes. A lower VaR with a longer window is not itself an error, and bigger is not automatically better.
Did you get it right without looking?
One question tells you little. A timed set on Validating Bank Holding Companies' Value-at-Risk Models for Market Risk shows your real accuracy, how long you take and where you lose marks.
More Validating Bank Holding Companies' Value-at-Risk Models for Market Risk questions
- A bank's trading desk shows four VaR exceptions in the last 250 days, but three of them occurred on consecutive days during a single market …
- A risk manager at a bank holding company observes 8 exceptions in 250 days for a 99% one-day VaR model. Using the Basel traffic-light zones …
- A bank's VaR model passes an unconditional coverage test, with exceptions near the expected 1%. However, the exceptions all occurred within …
- When backtesting a trading VaR model, a validator compares VaR with hypothetical P&L, which is generated from end-of-previous-day positions …
- A bank validation team compares its internal VaR model against an independent benchmark model built with different methodology and data on t…
- A bank's model validation team compares the daily VaR produced by its internal model with VaR calculated for the same portfolio using an ind…