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Título:
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Bayesian analysis of realized matrix-exponentialGARCH models
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Autores:
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Asai, Manabu ;
McAleer, Michael
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Tipo de documento:
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texto impreso
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Editorial:
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Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE), 2018
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Dimensiones:
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application/pdf
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Nota general:
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cc_by_nc_sa
info:eu-repo/semantics/openAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Matemáticas: Análisis matemático
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Materia = Ciencias Sociales: Economía: Econometría
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Tipo = Documento de trabajo o Informe técnico
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Resumen:
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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.
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En línea:
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https://eprints.ucm.es/46148/1/1804.pdf
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