Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …

heteroskedasticity (GARCH) models capture extreme events in stock market returns. We estimate Hill's tail indexes for individual S&P 500 … stock market returns ranging from 1995-2014 and compare these to the tail indexes produced by simulating GARCH models. Our … results suggest that actual and simulated values differ greatly for GARCH models with normal conditional distributions, which …

employed in a bivariate GARCH model, where the joint distribution of the disturbances is split into its marginals and its …-dependent distribution. -- value-at-risk ; copula ; non-normal bivariate GARCH ; asymmetric dependence ; profile likelihood-ratio test …

Poland. Applying the GARCH model and based on a sample during 1999.Q2 to 2012.Q4, this paper finds that Poland’s stock market …