several advantages compared to the linear correlation measure in modeling comovement. This paper introduces a copula ARMA-GARCH … model for analyzing the comovement of indexes in German equity markets. The model is implemented with an ARMA-GARCH model … skewed Student's t copula ARMA(1,1)-GARCH(1,1) model with Lévy fractional stable noise is superior to alternative models …

-Exponential Conditional Correlation (MECC) model. The paper applies the WDCC approach to the exponential GARCH (EGARCH) and GJR models to …

intermediate regimes is considered and modeled with the introduction of a smooth-transition mechanism in a GARCH specification. One … power. A smooth-transition GARCH specification is tested and estimated with stock returns and exchange-rate data. While a …

This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed by Nakatsuma (1998 …). This algorithm allows us to generate Monte Carlo samples of parameters in a GARCH model from their joint posterior … distribution. The samples obtained by this algorithm are used for Bayesian analysis of the GARCH model. As numerical examples …

Using unobservable conditional variance as measure, latentvariable approaches, such as GARCH and stochasticvolatility …

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been … employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which …

, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility …

) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast …