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Empirical (historical) versus parametric loss distribution

In this brief screencast, I show the difference between a parametric and empirical approach to loss distribution. My parametric approach is a normal distribution with mean of 0 and standard deviation of 5. Based on only these two parameters, I can generate 100 randomized losses (that's the advantage of parametric approach: I only need to pick the distribution and specify the parameters). My empirical approach also generates 100 random losses, but instead generates the losses via a so-called statistical bootstrap: armed with a set of 100 historical gains/losses, I simply select 100 randomly with replacement
Length: 08:38

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