Package: fHMM 1.4.1
Lennart Oelschläger
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>.
Authors:
fHMM_1.4.1.tar.gz
fHMM_1.4.1.tar.gz(r-4.5-noble)fHMM_1.4.1.tar.gz(r-4.4-noble)
fHMM_1.4.1.tgz(r-4.4-emscripten)fHMM_1.4.1.tgz(r-4.3-emscripten)
fHMM.pdf |fHMM.html✨
fHMM/json (API)
NEWS
| # Install 'fHMM' in R: |
| install.packages('fHMM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/loelschlaeger/fhmm/issues
Pkgdown site:https://loelschlaeger.de
- dax - Deutscher Aktienindex (DAX) index data
- dax_model_2n - DAX 2-state HMM with normal distributions
- dax_model_3t - DAX 3-state HMM with t-distributions
- dax_vw_model - DAX/VW hierarchical HMM with t-distributions
- sim_model_2gamma - Simulated 2-state HMM with gamma distributions
- spx - Standard & Poor’s 500 (S&P 500) index data
- unemp - Unemployment rate data USA
- unemp_spx_model_3_2 - Unemployment rate and S&P 500 hierarchical HMM
- vw - Volkswagen AG (VW) stock data
Last updated 4 months agofrom:6f628087a1. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 16 2024 |
| R-4.5-linux-x86_64 | OK | Dec 16 2024 |
Exports:compare_modelscompute_residualsdecode_statesdownload_datafHMM_eventsfHMM_parametersfit_modelll_hmmnparpar2parConpar2parUnconparCon2parparCon2parUnconparUncon2parparUncon2parConprepare_datareorder_statesset_controlssimulate_hmmviterbi
Dependencies:askpassassertthatbackportsBBbenchmarkmebenchmarkmeDatabriocallrcheckmateclicodetoolscolorspacecpp11crayoncurldescdiffobjdigestdoParalleldplyrevaluatefansifarverforeachfsgenericsGenOrdggfunggimageggplot2ggplotifyglueGPArotationgridGraphicsgtablehexbinhexStickerhmshttrisobanditeratorsjsonlitelabelinglatex2explatticelifecyclelubridatemagickmagrittrMASSMatrixmgcvmimemnormtmunsellmvtnormnleqslvnlmeoeliopensslpadrpillarpkgbuildpkgconfigpkgloadpracmapraiseprettyunitsprocessxprogresspspsychquadprogR6RColorBrewerRcppRcppArmadillorlangrprojrootscalesshowtextshowtextdbSimMultiCorrDatastringistringrsyssysfontstestthattibbletidyselecttimechangetriangleutf8vctrsVGAMviridisLitewaldowithryulab.utils
Controls
Rendered fromv02_controls.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
Data management
Rendered fromv03_data_management.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
Introduction
Rendered fromfHMM.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
Model checking
Rendered fromv06_model_checking.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
Model definition
Rendered fromv01_model_definition.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
Model estimation
Rendered fromv04_model_estimation.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
Model selection
Rendered fromv07_model_selection.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
State decoding and prediction
Rendered fromv05_state_decoding_and_prediction.Rmdusingknitr::rmarkdownon Dec 16 2024.Last update: 2024-09-17
Started: 2022-03-14
