The population coefficient of variation (CV) is $\sigma/\mu,$ where $\sigma$ is the population standard deviation and $\mu$ is the sample mean. [Perhaps see
[Wikipedia](https://en.wikipedia.org/wiki/Coefficient_of_variation)
for definition and examples of useful and improper applications.]

One commonly used estimate of the population CV uses the sample standard deviation and mean $S/\bar X$ and, for small sample sizes $n.$ the adjusted value $(1 + \frac 4 n)S/\bar X.$ Appropriate uses are for positive interval data (height, weight, etc.). 

The CV has no units, so it is the same for a group of stock prices, whether they are measured in dollars or yen. [There is a sense
in which ants are of more variable weight than elephants that is captured by the CV. Various species of ants can vary in weight by an order of magnitude or more, but the same can't be said for elephants.]

So it is usually a mistake to make comparisons between
standard deviations (which have units) with CVs (which do not). If you are using an F-test to compare variances, as suggested in the answer by @josef_joestarr, you should make sure both sample variances have the same units.