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

Compared with a parametric Monte Carlo simulation of portfolio returns, which is a genuine advantage of the bootstrap?

The bootstrap's key advantage is that it needs no assumed parametric distribution, since it resamples the actual observed data. Its limits are that it cannot create values beyond those observed and it inherits any bias or unrepresentativeness in the original sample.

  1. AIt does not require specifying a parametric distribution for the data because it uses the empirical observationsCorrect
  2. BIt can generate outcomes more extreme than any observed in the sample
  3. CIt removes the effect of sampling error in the original data set
  4. DIt works even if the original sample is unrepresentative of the true population

Explanation

The bootstrap draws from observed data, so no distribution needs to be assumed. However, it cannot produce values outside the observed range, does not eliminate sampling error in the original sample, and inherits any unrepresentativeness of that sample.

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