The coefficient of variability provides you with a measurement of how much your forecast values vary relative to the mean value. Because this statistic is independent of the forecast units, you can use it to compare the variability of two or more forecasts, even when the forecast scales differ.
For example, if you are comparing the forecast for a penny stock with the forecast for a stock on the New York Stock Exchange, you would expect the average variation (standard deviation) of the penny stock price to appear smaller than the variation of the NYSE stock. However, if you compare the coefficient of variability statistic for the two forecasts, you will notice that the penny stock shows significantly more variation on an absolute scale.
The coefficient of variability typically ranges from a value greater than 0 to 1. It might exceed 1 in a few cases in which the standard deviation of the forecast is unusually high. This statistic is computed by dividing the standard deviation by the mean.
The coefficient of variability is calculated by dividing the standard deviation by the mean, as follows.
To present this number as a percentage, multiply the result of the coefficient of variability calculation by 100.