Skew & Kurtosis

Skew and Kurtosis have been highly overlooked statistics by private/retail investors. Ignoring skew and kurtosis ignores the nature of your return’s distributions. The skew of a distribution measures asymmetry of distributions around a mean. If it’s a positive distribution, a non-symmetric tail extends into positive values. If negative, the tail extends into the negative values. Prefer investments with a solidly positive mean, and thin tail going into the positive with little or no negative tail.

Kurtosis shows the nature of the distribution’s peak. A higher peak has a higher kurtosis, and a flatter peak has a lower or negative kurtosis. Normal distributions have a kurtosis of 3 which is known as a mesokurtic kurtosis. Above 3 a kurtosis is known as leptokurtic, which features a higher, sharply peaked distribution. Below 3 is a flatter distribution called platykurtic, becoming increasingly flat as kurtosis approaches zero or below. I prefer a peaked kurtosis with a deep positive mean, especially on a recent time frame, with a positive skew. I want the vast majority of returns to be in positive with a positive mean.

Lastly, you should never try to eyeball skewness and kurtosis. Always rely on data output to tell you standard deviation, skew, and kurtosis.