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FRM Part I · FRM Exam Part I · Simulation and Bootstrapping

An analyst uses the standard (iid) bootstrap to estimate the sampling distribution of the mean daily return from 500 historical observations. Which feature of the data would most directly undermine the validity of this procedure?

Serial dependence such as volatility clustering undermines the iid bootstrap. Resampling observations independently with replacement breaks the time ordering, so the dependence structure is lost and the resulting standard errors and confidence intervals can be misleading. Units and sample size parity do not affect validity.

  1. AReturns are measured in percentages rather than decimals
  2. BStrong serial dependence, such as volatility clustering in the squared returnsCorrect
  3. CThe sample contains an even number of observations
  4. DThe bootstrap sample size equals the original sample size

Explanation

The iid bootstrap resamples observations with replacement independently, which destroys any time-ordering. If the data show serial dependence or volatility clustering, the resampled series will not reproduce that structure and standard errors can be misstated. The units, parity of the sample size, and use of a resample size equal to n are all standard and harmless.

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