Free GARP FRM Part II Market Risk Practice Questions

Market Risk Measurement and Management carries 20% of GARP FRM Part II (GARP). Questions cover non-parametric and extreme value approaches to VaR, backtesting and VaR mapping, validating VaR models, how correlations behave and bottom-up correlation modeling, regression hedging and principal component analysis, term structure models (drift, volatility, Vasicek and Gauss+), volatility smiles and surfaces, and the Fundamental Review of the Trading Book.

237 questions 80 easy 94 medium 63 hard 2026 syllabus

Sample Questions

Question 1 Easy
Which short-rate model can produce negative interest rates with positive probability?
Solution
C is correct. The Vasicek model assumes the short rate follows a normal Ornstein-Uhlenbeck process with support on the entire real line, so the rate has positive probability of going below zero. CIR uses a square-root diffusion whose variance vanishes as the rate approaches zero, keeping rates non-negative. Black-Karasinski and Black-Derman-Toy use lognormal dynamics, which keep rates strictly positive.
Question 2 Medium
Which statement most accurately describes empirically observed properties of equity-return correlations documented in long-horizon studies of pairwise correlations?
Solution
D is correct. Empirical work on equity-pair correlations documents two robust regularities. First, realized correlations revert toward a long-run average over multi-year horizons, motivating mean-reverting specifications. Second, the realized correlation series is itself highly volatile, with month-to-month swings comparable in magnitude to return volatility, which is why stochastic-correlation extensions of static models are needed.
Question 3 Hard
A portfolio's daily P&L is normally distributed with zero mean. The one-day 95% parametric VaR is $1 million. Using z0.95=1.645z_{0.95} = 1.645, z0.99=2.326z_{0.99} = 2.326, and assuming square-root-of-time scaling, the 10-day 99% expected shortfall is closest to:
Solution
D is correct. First back out the dollar standard deviation from the given 95% VaR: σV=$1,000,000/1.645=$607,903\sigma V = \$1{,}000{,}000 / 1.645 = \$607{,}903. Next, the daily 99% expected shortfall multiplier under normality is ϕ(z0.99)/(10.99)=0.02665/0.012.665\phi(z_{0.99})/(1-0.99) = 0.02665/0.01 \approx 2.665, where ϕ\phi is the standard normal density. Then daily 99% ES =2.665×$607,903$1,620,000= 2.665 \times \$607{,}903 \approx \$1{,}620{,}000. Scaling to a 10-day horizon by 103.162\sqrt{10} \approx 3.162 gives $1,620,000×3.162$5.12\$1{,}620{,}000 \times 3.162 \approx \$5.12 million.

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