Package: MSGARCH 2.51

Keven Bluteau

MSGARCH: Markov-Switching GARCH Models

Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.

Authors:David Ardia [aut], Keven Bluteau [aut, cre], Kris Boudt [ctb], Leopoldo Catania [aut], Alexios Ghalanos [ctb], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]

MSGARCH_2.51.tar.gz
MSGARCH_2.51.zip(r-4.7-x86_64)MSGARCH_2.51.zip(r-4.7-arm64)MSGARCH_2.51.zip(r-4.6-x86_64)MSGARCH_2.51.zip(r-4.6-arm64)
MSGARCH_2.51.tar.gz(r-4.7-arm64)MSGARCH_2.51.tar.gz(r-4.7-x86_64)MSGARCH_2.51.tar.gz(r-4.6-arm64)MSGARCH_2.51.tar.gz(r-4.6-x86_64)
MSGARCH_2.51.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MSGARCH/json (API)

# Install 'MSGARCH' in R:
install.packages('MSGARCH', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/keblu/msgarch/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • dem2gbp - DEM/GBP exchange rate log-returns
  • SMI - Swiss market index dataset

On CRAN:

Conda:

openblascpp

1.78 score 1 stars 2 packages 673 downloads 12 exports 10 dependencies

Last updated from:8cf35e5ed0. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK307
linux-devel-x86_64OK399
source / vignettesOK614
linux-release-arm64OK299
linux-release-x86_64OK249
windows-devel-arm64OK440
windows-devel-x86_64OK508
windows-release-arm64OK477
windows-release-x86_64OK1263
wasm-releaseOK201

Exports:CreateSpecDICExtractStateFitFitMCMCFitMLPITPredPdfRiskStateTransMatUncVolVolatility

Dependencies:codaexpmfanplotlatticeMASSMatrixnumDerivRcppRcppArmadillozoo

Readme and manuals

Help Manual

Help pageTopics
The R package MSGARCHMSGARCH-package MSGARCH
Model specification.CreateSpec
DEM/GBP exchange rate log-returnsdem2gbp
Deviance Information Criterion (DIC).DIC DIC.MSGARCH_MCMC_FIT
Single-regime model extractor.ExtractStateFit ExtractStateFit.MSGARCH_MCMC_FIT ExtractStateFit.MSGARCH_ML_FIT
MCMC/Bayesian estimation.FitMCMC
Maximum Likelihood estimation.FitML
Probability integral transform.PIT PIT.MSGARCH_MCMC_FIT PIT.MSGARCH_ML_FIT PIT.MSGARCH_SPEC
predict method.predict.MSGARCH_MCMC_FIT predict.MSGARCH_ML_FIT predict.MSGARCH_SPEC
Predictive density.PredPdf PredPdf.MSGARCH_MCMC_FIT PredPdf.MSGARCH_ML_FIT PredPdf.MSGARCH_SPEC
Value-at-Risk and Expected-shortfall.Risk Risk.MSGARCH_MCMC_FIT Risk.MSGARCH_ML_FIT Risk.MSGARCH_SPEC
Simulation of MSGARCH processes.simulate.MSGARCH_MCMC_FIT simulate.MSGARCH_ML_FIT simulate.MSGARCH_SPEC
Swiss market index datasetSMI
State probabilities.State State.MSGARCH_MCMC_FIT State.MSGARCH_ML_FIT State.MSGARCH_SPEC
Transition matrix.TransMat TransMat.MSGARCH_ML_FIT TransMat.MSGARCH_SPEC
Unconditional volatility.UncVol UncVol.MSGARCH_MCMC_FIT UncVol.MSGARCH_ML_FIT UncVol.MSGARCH_SPEC
Volatility filtering.Volatility Volatility.MSGARCH_MCMC_FIT Volatility.MSGARCH_ML_FIT Volatility.MSGARCH_SPEC