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 …

generalised autoregressive conditional heteroskedasticity (GARCH) model and extend the analysis using the exponential GARCH … than the GARCH model in estimating the volatility of the Australian stock returns. However, another interesting finding is …

forecasting accuracy and risk management efficiency. The results demonstrate that the RNN outperforms GARCH and EWMA in average …

investigated the sources of heavy tails by estimating autoregressive models in which innovations can be subject to GARCH effects … both within- and out-of-sample. We found strong evidence in favour of modelling both GARCH effects and non …

, including principal component analysis, GARCH-family model, and LASSO regression. The results of this paper suggest that the …