Bali et al. (2008) introduced a new method based on theSGT with time-varying parameters. They allowed higher-orderconditional moment parameters of the SGT density to dependon the past information set and hence relax the conventionalassumption in the conditional VaR calculation that the distri-bution of standardised returns is iid. Following Hansen (1994)and Jondeau and Rockinger (2003), they modelled the conditionalhigh-order moment parameters of the SGT density as an autore-gressive process. The maximum likelihood estimates show thatthe time-varying conditional volatility, skewness, tail-thickness,and peakedness parameters of the SGT density are statistically sig-nificant. In addition, they found that the conditional SGT-GARCHmodels with time-varying skewness and kurtosis provided a betterfit or returns than the SGT-GARCH models with constant skew-ness and kurtosis. In their paper, they applied this new approach tocalculate the VaR. The in-sample and out-of-sample performanceresults indicated that the conditional SGT-GARCH approach withautoregressive conditional skewness and kurtosis provided veryaccurate and robust estimates of the actual VaR thresholds.