Normal distribution of returns is a common error in model assumptions. The most

accurate description of this type of error is that:

Models that work in normal conditions should not be used in times of greater uncertainties.

Data points can include a number of outliers, which can distort the shape of the distribution curve and make parametric computation unreliable.

Returns are also severely impacted by abnormal liquidity conditions, which can affect the accuracy of the model results.

Tax and transactional costs will affect the normal pricing data and distort model results.