Year: 2014
Type: preprint
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.
Source: arXiv (Cornell University)
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W66467429