mfGARCH: Mixed-Frequency GARCH Models

Estimating GARCH-MIDAS (MIxed-DAta-Sampling) models (Engle, Ghysels, Sohn, 2013, <doi:10.1162/REST_a_00300>) and related statistical inference, accompanying the paper "Two are better than one: Volatility forecasting using multiplicative component GARCH models" by Conrad and Kleen (2020, <doi:10.1002/jae.2742>). The GARCH-MIDAS model decomposes the conditional variance of (daily) stock returns into a short- and long-term component, where the latter may depend on an exogenous covariate sampled at a lower frequency.

Version:	0.2.1
Depends:	R (≥ 3.3.0)
Imports:	Rcpp, graphics, stats, numDeriv, zoo, maxLik
LinkingTo:	Rcpp
Suggests:	testthat, dplyr, ggplot2, covr, rmarkdown
Published:	2021-06-17
DOI:	10.32614/CRAN.package.mfGARCH
Author:	Onno Kleen [aut, cre]
Maintainer:	Onno Kleen <r at onnokleen.de>
BugReports:	https://github.com/onnokleen/mfGARCH/issues
License:	MIT + file LICENSE
URL:	https://github.com/onnokleen/mfGARCH/
NeedsCompilation:	yes
Citation:	mfGARCH citation info
Materials:	NEWS
CRAN checks:	mfGARCH results

Documentation:

Reference manual:

mfGARCH.pdf

Downloads:

Package source:	mfGARCH_0.2.1.tar.gz
Windows binaries:	r-devel: mfGARCH_0.2.1.zip, r-release: mfGARCH_0.2.1.zip, r-oldrel: mfGARCH_0.2.1.zip
macOS binaries:	r-release (arm64): mfGARCH_0.2.1.tgz, r-oldrel (arm64): mfGARCH_0.2.1.tgz, r-release (x86_64): mfGARCH_0.2.1.tgz, r-oldrel (x86_64): mfGARCH_0.2.1.tgz
Old sources:	mfGARCH archive

Linking:

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