Asai, ManabuMcAleer, Michael2023-06-172023-06-1720182341-2356https://hdl.handle.net/20.500.14352/17409The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the information of returns and realized measure of co-volatility matrix simultaneously. The paper also considers an alternative multivariate asymmetric function to develop news impact curves. We consider Bayesian MCMC estimation to allow non-normal posterior distributions. For three US financial assets, we compare the realized MEGARCH models with existing multivariate GARCH class models. The empirical results indicate that the realized MEGARCH models outperform the other models regarding in-sample and out-of-sample performance. The news impact curves based on the posterior densities provide reasonable results.engAtribución-NoComercial-CompartirIgual 3.0 Españahttps://creativecommons.org/licenses/by-nc-sa/3.0/es/technical reporthttps://www.ucm.es/icaeopen accessC11C32Multivariate GARCHRealized MeasureMatrix-ExponentialBayesian Markov chain Monte Carlo methodAsymmetry.Análisis matemáticoEconometría (Economía)1202 Análisis y Análisis Funcional5302 Econometría