• Corpus ID: 88520952

# BayesDccGarch - An Implementation of Multivariate GARCH DCC Models

@article{Fioruci2014BayesDccGarchA,
title={BayesDccGarch - An Implementation of Multivariate GARCH DCC Models},
author={Jos{\'e} Augusto Fioruci and Ricardo S. Ehlers and Francisco Louzada},
journal={arXiv: Computation},
year={2014}
}
• Published 9 December 2014
• Computer Science
• arXiv: Computation
Multivariate GARCH models are important tools to describe the dynamics of multivariate times series of financial returns. Nevertheless, these models have been much less used in practice due to the lack of reliable software. This paper describes the {\tt R} package {\bf BayesDccGarch} which was developed to implement recently proposed inference procedures to estimate and compare multivariate GARCH models allowing for asymmetric and heavy tailed distributions.

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