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Conditional Heteroscedasticity (GARCH) volatility model. The optimization was performed by employing a Nondominated Sorting … to those obtained from applying more customary mean-multivariate GARCH and historical VaR models. The results hold true …
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applied within a Bayesian analysisof a GARCH-mixture model which is used for the evaluation of theValue-at-Risk of the return …
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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 …
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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 …
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