Historical simulation
Estimating a portfolio's possible outcomes by applying risk-factor changes actually observed over a past window to today's positions. It needs no distributional assumption but cannot show what the window never saw.
Where you will meet it
Historical simulation appears in 5 learning outcomes on the CFA syllabus. A few of them:
- Explain historical simulation and how it is used in investing
“Historical simulation estimates the range of possible outcomes by applying risk-factor changes actually observed over a look-back period to today's portfolio.”
- Contrast three ways to estimate VaR: Monte Carlo simulation, historical simulation, and the parametric (variance–covariance) method
“Historical simulation revalues today's portfolio under the actual returns of a past window and reads VaR from the chosen percentile; it needs no distribution assumption and handles options, but depends entirely on whether the window contains stressful periods.”
- Contrast historical simulation with Monte Carlo simulation and with bootstrap resampling
“Historical simulation replays actual past periods once each, in order.”
- Estimate VaR by Monte Carlo simulation, by historical simulation, and by the parametric method, and explain what each result means
“For historical simulation, rank the revalued outcomes and take the one at the chosen percentile, for example the 25th worst of 500 for a 5% VaR under a common convention.”
Learn it properly
Practise it
Practise historical simulation until it is automatic: questions that explain every wrong option.
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