Tail Risk in Hedge Funds: Classical Skewness Coefficients vs Azzalini's Skewness Parameter

Recent literature discusses the persistence of skewness and tail risk in hedge fund returns. The aim of this paper is to suggest an alternative skewness measure which is derived as the normalized shape parameter from the skew-normal distribution. First, we illustrate that the skew-normal distribution is better able to catch the characteristics of hedge fund returns than the normal distribution. And second, we show that using the skewness parameter has a number of advantages compared to common measures of skewness, e.g., it has a limpid financial interpretation as a skewness shock on normally distributed returns and tail-risk measures such as Value-at-Risk and Conditional Value-at-Risk are decreasing functions of .