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

A bank wants to retain the intuitive appeal of historical simulation but address its slow adaptation to current market conditions. Which of the following modifications directly targets this weakness?

Age-weighting observations, so recent returns receive more weight than older ones, directly addresses slow adaptation while staying non-parametric. Fitting a normal distribution abandons the non-parametric approach, and changing the confidence level or using the worst day does not improve responsiveness to current conditions.

  1. AAssigning weights that decline with the age of observations so recent returns count moreCorrect
  2. BReplacing historical returns with draws from a fitted normal distribution
  3. CReducing the confidence level from 99% to 95% to cut sampling error
  4. DUsing only the single worst day in the window as the VaR

Explanation

Age-weighted (or volatility-weighted) historical simulation gives recent data greater influence, so VaR adapts faster. Fitting a normal makes the method parametric and loses the non-parametric benefit. Lowering confidence changes the risk measure rather than responsiveness, and using the worst day is a crude, unstable estimate.

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