medium · Frm Part 2 Market Risk
An institutional risk team uses a non-parametric bootstrap to estimate a 95% confidence interval for their 99% VaR_1-day. The current 500-day historical window contains a maximum loss of 12.5m.
If the true underlying risk regime has shifted such that the potential 99.9% tail loss is now25.0m, what is the primary structural limitation of the bootstrap in this scenario?
- Bootstrapping is a parametric technique that assumes a normal distribution, failing to see the shift.
- The 500-day window is too large for bootstrapping, violating the Central Limit Theorem.
- The bootstrap is strictly bounded by the maximum observed loss in the historical sample.
- The bootstrap will overstate the confidence interval width due to the inclusion of the $12.5m outlier.
Sign up free to see the explanation and track your rank →
More Frm Part 2 Market Risk practice
- A leptokurtic distribution, often modeled by EVT, is characterized by which of the followi
- If a bank records 11 exceptions in a 250-day backtesting window for 99% VaR, what is the r
- In the GPD framework, if the threshold u is chosen too low, what is the most likely error
- In the Kupiec Likelihood Ratio test, what does the null hypothesis (H_0) state?
- The Hill estimator is primarily used to provide a direct estimate of which parameter?
- What happens to the mean of a GPD-distributed variable if the tail index ξ ≥ 1?
- What happens to the VaR estimate if we move from a thin-tailed (Gumbel, ξ = 0) model to a
- What is the base capital multiplier (m) applied to a bank's internal model market risk cap