… model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying
degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to …

… conditional-SGT-VaR approach with GARCH volatility and autoregressive skewness and
kurtosis… Both the in-sample and out-of-sample performance results indicate that the conditional …

… are given, we characterize the skewness–kurtosis domain for which densities are defined.
This … kurtosis are time varying. We find that there is little predictability of skewness and kurtosis …

… measures of conditional skewness and kurtosis defined in terms of conditional quantiles,
analogous to the unconditional quantile-based measures of skewness and kurtosis studied by …

… Their methodology is applied to several series of stock index returns, and it is found that
autoregressive conditional skewness is significant and that the inclusion of skewness affects the …

Most of the statistical tools are designed to model the conditional mean of a random variable.
The tools described in this article have a rather different purpose – to model the conditional …

… The fourth moment of financial returns, kurtosis, has drawn substantial attention as well,
primarily because kurtosis can be related to the variance of variance and, thus, can be used as a …

… and persistence of conditional skewness and kurtosis of various … We express skewness and
kurtosis of Hansen's GARCH model … the conditional evolution of skewness and kurtosis for a …

Engle's ARCH model is extended to permit parametric specifications for conditional dependence
beyond the mean and variance. The suggestion is to model the conditional density with …

… This article develops an independent factor model for the conditional density of financial
returns with time-varying skewness and kurtosis. In the presence of nonnormally distributed …