fHMM: Fitting Hidden Markov Models to Financial Data

Fitting (hierarchical) hidden Markov models to financial data via maximum likelihood estimation. See Oelschläger, L. and Adam, T. "Detecting Bearish and Bullish Markets in Financial Time Series Using Hierarchical Hidden Markov Models" (2021, Statistical Modelling) <doi:10.1177/1471082X211034048> for a reference on the method. A user guide is provided by the accompanying software paper "fHMM: Hidden Markov Models for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R. (2024, Journal of Statistical Software) <doi:10.18637/jss.v109.i09>.

Version: 1.4.1
Depends: R (≥ 4.0.0)
Imports: checkmate, cli, curl, foreach, graphics, grDevices, httr, jsonlite, MASS, oeli (≥ 0.3.0), padr, pracma, progress, Rcpp, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: covr, doSNOW, knitr, parallel, rmarkdown, testthat (≥ 3.0.0), tseries
Published: 2024-09-16
DOI: 10.32614/CRAN.package.fHMM
Author: Lennart Oelschläger ORCID iD [aut, cre], Timo Adam ORCID iD [aut], Rouven Michels ORCID iD [aut]
Maintainer: Lennart Oelschläger <oelschlaeger.lennart at gmail.com>
BugReports: https://github.com/loelschlaeger/fHMM/issues
License: GPL-3
URL: https://loelschlaeger.de/fHMM/
NeedsCompilation: yes
Language: en-US
Citation: fHMM citation info
Materials: README NEWS
In views: Finance
CRAN checks: fHMM results

Documentation:

Reference manual: fHMM.pdf
Vignettes: Introduction (source, R code)
Model definition (source, R code)
Controls (source, R code)
Data management (source, R code)
Model estimation (source, R code)
State decoding and prediction (source, R code)
Model checking (source, R code)
Model selection (source, R code)

Downloads:

Package source: fHMM_1.4.1.tar.gz
Windows binaries: r-devel: fHMM_1.4.1.zip, r-release: fHMM_1.4.1.zip, r-oldrel: fHMM_1.4.1.zip
macOS binaries: r-release (arm64): fHMM_1.4.1.tgz, r-oldrel (arm64): fHMM_1.4.1.tgz, r-release (x86_64): fHMM_1.4.1.tgz, r-oldrel (x86_64): fHMM_1.4.1.tgz
Old sources: fHMM archive

Linking:

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