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 …

exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral …

Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and …

Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance … volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions …

follow GARCH and stochastic volatility (SV). Under certain regularity conditions, we give asymptotic results for the … approximate maximum likelihood estimator for the GARMA-GARCH model. We discuss a Monte Carlo likelihood method for the GARMA …