A Data-Analytic Look at Skewness and Elongation in Common-Stock-Return Distributions
用Tukey的g和h分布估计个股日收益的偏度和延展性，发现收益分布比正态分布更延展，且偏度和延展性在时间上具有持续性。
Abstract This article explores the nature of skewness and elongation in daily common-stock-return distributions of individual firms using estimates of g (for skewness) and h (for elongation) obtained from Tukey's g and h distributions. Both parametric and nonparametric (bootstrap) estimates of standard errors of the g estimates are computed and compared. Daily return distributions are first examined cross-sectionally over a large sample of firms. The estimates of the skewness parameter exhibit variation across individual firms, but some general trends are evident across industry groups and firm sizes. Return distributions typically seem to be more elongated than the Gaussian distribution. From a time series perspective, both skewness and elongation are persistent in the return distributions of individual firms and vary over a finite range. First-order autocorrelation coefficients of monthly g and h estimates are large and suggest a certain degree of predictability. KEY WORDS: Bootstrap g and h distributionsKurtosisPortfolio strategiesPseudo-sigma.