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What is the difference between "Heavy-Tailed" and Gaussian distribution models?

In probability distributions, "heavy-tailed" distributions are those whose tails are not exponentially bounded. Unlike the bell curve with a "normal distribution", heavy-tailed distributions approach zero at a slower rate and can have outliers with very high values. In risk terms, heavy-tailed distributions have a higher probability of a large, unforeseen event occurring.

Graphically, against the  empirical data in blue, the SmartRisk heavy-tailed model, in red, captures more of the risk as described in a model 60/40 Portfolio. The Gaussian model, or bell curve, normal distribution is in green. 

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