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Bayesian analysis of realized matrix-exponential GARCH models

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Asai, Manabu and McAleer, Michael (2018) Bayesian analysis of realized matrix-exponential GARCH models. [ Documentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE); nº 04, 2018, ISSN: 2341-2356 ]

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Abstract

The 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.


Item Type:Working Paper or Technical Report
Uncontrolled Keywords:Multivariate GARCH; Realized Measure; Matrix-Exponential; Bayesian Markov chain Monte Carlo method; Asymmetry.
Subjects:Sciences > Mathematics > Mathematical analysis
Social sciences > Economics > Econometrics
JEL:C11, C32
Series Name:Documentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
Volume:2018
Number:04
ID Code:46148
Deposited On:24 Jan 2018 13:43
Last Modified:24 Jan 2018 13:43

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