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

A firm plans to use Monte Carlo simulation to assess portfolio risk and generates scenarios from a model calibrated to a calm historical period. Which is the most important limitation of this approach?

Simulation results depend on the assumed model and calibrated inputs, so a misspecified model, such as one fitted to a calm period, yields precise-looking but wrong risk estimates. More draws reduce sampling error only, not model risk.

  1. AIncreasing the number of simulations will eliminate model risk
  2. BSimulation output is only as reliable as the assumed model and its inputs, so misspecification produces precise but wrong resultsCorrect
  3. CMonte Carlo simulation cannot be applied to nonlinear instruments
  4. DSimulated results are always identical across different random seeds

Explanation

Simulation error from sampling shrinks with more draws, but errors from a misspecified model or poorly calibrated parameters persist. A model calibrated to calm data may understate risk in stressed markets. Simulation handles nonlinear instruments well, and results vary with the seed.

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