FRM Part II · FRM Exam Part II · Parametric Approaches (II): Extreme Value
Using a POT model with threshold u = 2.0%, shape ξ = 0.2 and scale β = 0.5, a risk manager has computed a 99% VaR of 2.95%. Using ES = (VaR + β − ξu)/(1 − ξ), what is the 99% expected shortfall?
Expected shortfall is about 3.81%. The numerator is VaR plus β minus ξ times u, which is 2.95 + 0.5 − 0.4 = 3.05, and dividing by 1 − ξ = 0.8 gives 3.81%. ES exceeds VaR because it averages losses beyond the VaR.
- AApproximately 3.81%Correct
- BApproximately 4.31%
- CApproximately 2.54%
- DApproximately 3.45%
Explanation
The numerator is 2.95 + 0.5 − 0.2 × 2.0 = 3.05. Dividing by 1 − ξ = 0.8 gives 3.8125, about 3.81%. Omitting the ξu adjustment gives 4.31%. Dividing by 1 + ξ instead gives 2.54%. VaR + β gives 3.45%, which ignores the tail-heaviness scaling.
Did you get it right without looking?
One question tells you little. A timed set on Parametric Approaches (II): Extreme Value shows your real accuracy, how long you take and where you lose marks.
More Parametric Approaches (II): Extreme Value questions
- An analyst fits a generalized Pareto distribution to the tail of operational-style trading losses and obtains a shape parameter ξ = 0.55. Wh…
- A risk team uses POT with threshold u. They raise u substantially to ensure the generalised Pareto approximation is more accurate. Which con…
- Which of the following best explains why the GEV approach is useful for estimating extreme risk compared with fitting a normal distribution …
- A risk analyst fits a Generalized Extreme Value (GEV) distribution to block maxima of daily portfolio losses, where each block is one month.…
- A risk analyst wants to estimate extreme losses on a trading portfolio using only the observations that are unusually large, rather than spl…
- A risk analyst at a bank wants to estimate the 99.9% VaR of daily trading losses using only the extreme tail observations rather than fittin…