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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). 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.

Version: 2.0.0
Depends: methods, R (≥ 4.0.0), Rcpp (≥ 1.0.5)
Imports: forecast, ggplot2, loo, MASS, Rdpack, rstan (≥ 2.26.0), rstantools (≥ 2.1.1)
LinkingTo: BH (≥ 1.72.0-0), Rcpp (≥ 1.0.5), RcppParallel (≥ 5.0.1), RcppEigen (≥ 0.3.3.7.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: testthat (≥ 2.3.2)
Published: 2023-09-12
DOI: 10.32614/CRAN.package.bmgarch
Author: Philippe Rast ORCID iD [aut, cre], Stephen Martin ORCID iD [aut]
Maintainer: Philippe Rast <rast.ph at gmail.com>
BugReports: https://github.com/ph-rast/bmgarch/issues
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
In views: Finance
CRAN checks: bmgarch results

Documentation:

Reference manual: bmgarch.pdf

Downloads:

Package source: bmgarch_2.0.0.tar.gz
Windows binaries: r-devel: bmgarch_2.0.0.zip, r-release: bmgarch_2.0.0.zip, r-oldrel: bmgarch_2.0.0.zip
macOS binaries: r-release (arm64): bmgarch_2.0.0.tgz, r-oldrel (arm64): bmgarch_2.0.0.tgz, r-release (x86_64): bmgarch_2.0.0.tgz, r-oldrel (x86_64): bmgarch_2.0.0.tgz
Old sources: bmgarch archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.