BayesDccGarch - An Implementation of Multivariate GARCH DCC Models
Computation
2014-12-10 v1
Abstract
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.
Cite
@article{arxiv.1412.2967,
title = {BayesDccGarch - An Implementation of Multivariate GARCH DCC Models},
author = {Jose A. Fioruci and Ricardo S. Ehlers and Francisco Louzada},
journal= {arXiv preprint arXiv:1412.2967},
year = {2014}
}