Kurtosis is a measure of how the distribution of a set of data compares with a normal distribution. Specifically, kurtosis measures the tailedness of a distribution with respect to a normal bell curve. We should think of this in terms of the distribution of probability. A normal bell curve is said to be mesokurtic. Distributions that have more kurtosis than a normal bell curve are called leptokurtic. Leptokurtic distributions have wide tails, meaning that they have a wide range of outliers, with some of those outliers being extreme. Distributions with less kurtosis than a normal bell curve are called platykurtic. Platykurtic distributions are stable with a paucity of extreme outliers. Kurtosis is a useful computation for decision-making in that kurtosis directly speaks to risk. For example, investors who invest in stocks with a leptokurtic distribution are engaging...
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