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A method of calculating value-at-risk (VaR) that uses historical data to assess the impact of market moves on a portfolio. A current portfolio is subjected to historically recorded market movements; this is used to generate a distribution of returns on the portfolio. This distribution can then be used to calculate the maximum loss with a given likelihood – that is, the VaR.
Because historical simulation uses real data, it can capture unexpected events and correlations that would not necessarily be predicted by a theoretical model.