Adjusting VAR to correct sample volatility bias
The calculation of value-at-risk often relies on using a sample variance for that of the forward-looking distribution. However, using an unbiased estimate of variance leads to biased estimates of VAR. David Frank proposes an adjustment that can be easily retrofitted into existing models to correct for this bias
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In this article, we propose a simple adjustment that can be used when computing value-at-risk (RiskMetrics Group 1996) if a sample standard deviation of returns rather than the true standard deviation is employed. Using the sample standard deviation as if it were the true standard deviation (the usual procedure) results in VAR estimates that are biased downwards. We propose a correction for this bias by adjusting the VAR level itself, where the adjustment depends on
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