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FRM Part II · FRM Exam Part II · Non-parametric Approaches

A bank's historical simulation VaR used a 1,000-day window. During a calm period, volatility was low for 900 days, then a sharp volatility spike occurred in the last 10 days. The reported 99% VaR barely moved. Which weakness of equally weighted historical simulation best explains this?

Equally weighted historical simulation reacts slowly to new conditions, because the ten volatile days are only a tiny fraction of a 1,000-day sample and barely affect the 99% quantile. Age-weighting or volatility-weighting can fix this problem.

  1. ASlow response to recent changes in risk because all observations carry equal weightCorrect
  2. BOverstated VaR resulting from the assumption of normally distributed returns
  3. CInability to incorporate any option positions in the portfolio
  4. DExcess sensitivity to the choice of a parametric volatility model

Explanation

With equal weights, the 10 recent volatile days make up only 1% of the sample, so they hardly affect the 99% quantile. Weighting schemes such as age-weighting or volatility-weighting address this. The method is not parametric, so normality and volatility model choices are not relevant.

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