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Parametric value at risk (VaR): Pros & Cons

Here is a quick explanation of parametric value at risk (VaR) as a means to illustrating its strengths/weaknesses. Please note: The essence of parametric VaR is "no data:" while historical data is surely used to select a distribution and calibrate its parameters, a parametric VaR leans on a statistical distribution to infer losses In this illustration, I use the normal distribution which is typical. The normal is nice because we only need two parameters (expected return and volatility), but we don't need to use the normal! We can use other distributions; e.g., lognormal.
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