




Skewness is a descriptive statistic that is used in analyzing the distribution of a set of data. In finance and investing, skewness is used in conjunction with other metrics, such as kurtosis and value at risk (VAR). When used to analyze investment returns, skewness measures the asymmetry of those returns. A normally distributed dataset would have a skewness of zero. Investment returns, however, do not usually show a normal distribution.
If investment returns are graphed and they show a positive skewness then the following descriptive statistics have the relation: mean > median > mode. When a distribution exhibits a negative skewness the relation is: mean < median < mode.
Skewness is an important consideration when examining investment returns because it can warn of the potential risk involved based on historical returns. Although a negative skewness can be indicative of a high frequency of relatively small gains, it could also warn of the possibility, though a remote one, of a result that is extremely negative.
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