Final answer:
Criticism of using standard deviation as a measure of risk centers on its focus on total risk, overlooking the shape of distribution. While convenient for symmetric data, its utility is limited for skewed distributions where alternative measures like median or quartiles may be more insightful.
Step-by-step explanation:
One of the main criticisms of using standard deviation as a measure of risk is that it only measures total risk and therefore should not be used with portfolios. This criticism is grounded in the notion that standard deviation doesn't fully capture the nuances of an investment's risk profile, particularly when considering diverse portfolios. The standard deviation, while providing a numerical measure of the overall amount of variation in a data set, may not account for the shape of the distribution or the likelihood of extreme values, also known as the higher moments of distribution.
When using standard deviation, we typically rely on calculating software or tools such as calculators or computer programs because the computations can be complex. Despite the complexity, it's essential for understanding how data points or outcomes of a statistical experiment spread out from the mean of a distribution. This measure can be particularly insightful for symmetrical distributions, but its utility may diminish in skewed distributions where measures like the median or quartiles can offer better insights.