bmgarch: Bayesian Multivariate GARCH Models

Fit Bayesian multivariate GARCH models using 'Stan' for full Bayesian inference. Generate (weighted) forecasts for means, variances (volatility) and correlations. Currently DCC(P,Q), CCC(P,Q), pdBEKK(P,Q), and BEKK(P,Q) parameterizations are implemented, based either on a multivariate gaussian normal or student-t distribution. DCC and CCC models are based on Engle (2002) <doi:10.1198/073500102288618487> and Bollerslev (1990) <doi:10.2307/2109358>. The BEKK parameterization follows Engle and Kroner (1995) <doi:10.1017/S0266466600009063> while the pdBEKK as well as the estimation approach for this package is described in Rast et al. (2020) <doi:10.31234/osf.io/j57pk>. The fitted models contain 'rstan' objects and can be examined with 'rstan' functions.

Package details

AuthorPhilippe Rast [aut, cre] (<https://orcid.org/0000-0003-3630-6629>), Stephen Martin [aut] (<https://orcid.org/0000-0001-8085-2390>)
MaintainerPhilippe Rast <rast.ph@gmail.com>
LicenseGPL (>= 3)
Version1.0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bmgarch")

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bmgarch documentation built on June 14, 2021, 9:09 a.m.