Skewness measures the degree of asymmetry of a distribution around its mean. Positive skewness indicates a distribution with an asymmetric tail extending toward more positive values; negative skewness indicates a distribution with an asymmetric tail extending toward more negative values; zero skewness means the tails are symmetric. Interpreted as downside risk, positive skewness suggests fewer/smaller negative outcomes whereas negative skewness suggests more/greater.
Kurtosis measures the "tail-heaviness" (as opposed to "peakedness" or "flatness") of a distribution compared against a normal distribution (k = 3). A "low" kurtosis (k < 3) indicates fewer/smaller outliers whereas a "high" kurtosis (k > 3) indicates more/greater. With high kurtosis, one will have "fat" tails, higher frequency of outcomes at the extreme negative and positive ends of the distribution curve.
The Conditional Sharpe Ratio is defined as the ratio of expected excess return to the expected shortfall. CVaR is used as the denominator in the C-Sharpe calculation whereas the standard Sharpe ratio uses Standard Deviation as the denominator. The conditional Sharpe ratio would be important to selecting stocks if CVaR was an important risk variable to the investor.
All information and calculations are from Zoonova.com.
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