documented with statistical tools such as exceedance correlation, extreme value theory, and Gaussian bivariate GARCH or regime … modèles GARCH bivarié en langage Gauss ou avec changement de régime. Nous signalons les limites de ces outils pour …

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 …

Germany. Using a GARCH model, I evaluate the effect of wind electricity generation on the level and the volatility of the …

-augmented GARCH specification for the period from May 1987 to October 2013, our key findings are as follows: (i) Volatilities on … choice of other frequently used GARCH model variants, like GARCH-M, TGARCH and CGARCH. …