tsmarch: Multivariate ARCH Models

Feasible Multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models including Dynamic Conditional Correlation (DCC), Copula GARCH and Generalized Orthogonal GARCH with Generalized Hyperbolic distribution. A review of some of these models can be found in Boudt, Galanos, Payseur and Zivot (2019) <doi:10.1016/bs.host.2019.01.001>.

Version: 1.0.0
Depends: R (≥ 3.5.0), methods, tsmethods (≥ 1.0.2)
Imports: Rcpp, RcppParallel, tsgarch (≥ 1.0.3), tsdistributions (≥ 1.0.2), RcppBessel, Rsolnp, nloptr, numDeriv, abind, shape, Rdpack, xts, zoo, lubridate, sandwich, future.apply, future, stats, utils, data.table
LinkingTo: Rcpp (≥ 0.10.6), RcppArmadillo, RcppParallel, RcppBessel
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), tstests
Published: 2024-11-18
DOI: 10.32614/CRAN.package.tsmarch
Author: Alexios Galanos ORCID iD [aut, cre, cph]
Maintainer: Alexios Galanos <alexios at 4dscape.com>
BugReports: https://github.com/tsmodels/tsmarch/issues
License: GPL-2
URL: https://github.com/tsmodels/tsmarch, https://www.nopredict.com
NeedsCompilation: yes
SystemRequirements: GNU make
In views: TimeSeries
CRAN checks: tsmarch results

Documentation:

Reference manual: tsmarch.pdf
Vignettes: Feasible Multivariate GARCH Models (source, R code)
tsmarch demo (source, R code)

Downloads:

Package source: tsmarch_1.0.0.tar.gz
Windows binaries: r-devel: tsmarch_1.0.0.zip, r-release: tsmarch_1.0.0.zip, r-oldrel: tsmarch_1.0.0.zip
macOS binaries: r-release (arm64): tsmarch_1.0.0.tgz, r-oldrel (arm64): tsmarch_1.0.0.tgz, r-release (x86_64): tsmarch_1.0.0.tgz, r-oldrel (x86_64): tsmarch_1.0.0.tgz

Linking:

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