Background | Demo | Conclusion | References
Package: tsmarch 1.0.3
Alexios Galanos
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>.
Authors:
tsmarch_1.0.3.tar.gz
tsmarch_1.0.3.zip(r-4.7)tsmarch_1.0.3.zip(r-4.6)tsmarch_1.0.3.zip(r-4.5)
tsmarch_1.0.3.tgz(r-4.6-x86_64)tsmarch_1.0.3.tgz(r-4.6-arm64)tsmarch_1.0.3.tgz(r-4.5-x86_64)tsmarch_1.0.3.tgz(r-4.5-arm64)
tsmarch_1.0.3.tar.gz(r-4.7-arm64)tsmarch_1.0.3.tar.gz(r-4.7-x86_64)tsmarch_1.0.3.tar.gz(r-4.6-arm64)tsmarch_1.0.3.tar.gz(r-4.6-x86_64)
tsmarch_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tsmarch/json (API)
| # Install 'tsmarch' in R: |
| install.packages('tsmarch', repos = c('https://tsmodels.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tsmodels/tsmarch/issues
Datasets:
- dji30retw - Dow Jones 30 Constituents Closing Value log Weekly Return
- globalindices - Global Financial Indices Closing Value log Weekly Return
econometricsfinancegarchmultivariate-timeseriestime-seriesopenblascpp
Last updated from:e0de455e99. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 300 | ||
| linux-devel-x86_64 | OK | 299 | ||
| source / vignettes | OK | 606 | ||
| linux-release-arm64 | OK | 320 | ||
| linux-release-x86_64 | OK | 349 | ||
| macos-release-arm64 | OK | 456 | ||
| macos-release-x86_64 | OK | 587 | ||
| macos-oldrel-arm64 | OK | 293 | ||
| macos-oldrel-x86_64 | OK | 383 | ||
| windows-devel | OK | 305 | ||
| windows-release | OK | 278 | ||
| windows-oldrel | OK | 296 | ||
| wasm-release | OK | 200 |
Exports:breadcgarch_modelspeccombn_fastdcc_modelspecdfftescc_testestfunexpected_shortfallfasticagogarch_modelspecnewsimpactpfftqfftradicalvalue_at_risk
Dependencies:abindalabamaaskpassbase64encbslibcachemclicodetoolscpp11data.tabledigestDistributionUtilsdplyrevaluatefastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverfsfuturefuture.applygdtoolsGeneralizedHyperbolicgenericsglobalsgluehighrhtmltoolsjquerylibjsonliteKernSmoothknitrlatticelifecyclelistenvlubridatemagrittrMASSMatrixmemoisemevmimenleqslvnloptrnumDerivofficeropensslparallellypillarpkgconfigprogressrpurrrR6raggrappdirsrbibutilsRcppRcppArmadilloRcppBesselRcppEigenRcppParallelRdpackrlangrmarkdownRsolnpsandwichsassshapeSkewHyperbolicstringistringrsyssystemfontstextshapingtibbletidyrtidyselecttimechangetinytexTMBtruncnormtsdistributionstsgarchtsmethodsutf8uuidvctrswithrxfunxml2xtsyamlzipzoo
Constant correlation test
Last update: 2024-12-12
Started: 2024-12-12
tsmarch demo
Introduction | GOGARCH Dynamics | Model Specification and Estimation | Filtering | Conditional Co-moments | Weighted Portfolio Distribution | DCC Dynamics | Filtering | Copula with DCC Dynamics | Conditional Mean Dynamics | Method 1: Conditional Mean Re-centering | Method 2: Innovation Distribution Injection | Method Comparison
Last update: 2024-12-09
Started: 2024-11-12
Feasible Multivariate GARCH Models
Introduction | Covariance Decomposition Models (dcc and cgarch) | Constant Correlation | Dynamic Conditional Correlation | Estimation | Standard Errors | Distributions | Multivariate Student Distribution (mvt) | Copula Distribution (cgarch) | Generalized Dynamics | Forecasting and Simulation | Weighted Distribution | News Impact Surface | Critique | Generalized Orthogonal GARCH Model (gogarch) | Estimation | Co-Moments | Weighted Distribution | Factor News Impact Surface | Methods and Classes | Appendix | Correlation and Kendall's $\tau$ | Notes on Selected Methods | References
Last update: 2024-11-15
Started: 2024-09-29
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Transform a test object into flextable | as_flextable.tstest.escc |
| Bread Method | bread.cgarch.estimate bread.dcc.estimate |
| Generic Methods for the Copula GARCH model specification | cgarch_modelspec |
| Copula GARCH model specification | cgarch_modelspec.tsgarch.multi_estimate |
| Extract Model Coefficients | coef coef.cgarch.estimate coef.dcc.estimate coef.gogarch.estimate |
| Fast combination of n elements, taken m at a time | combn_fast |
| Generic Methods for the DCC GARCH model specification | dcc_modelspec |
| DCC GARCH model specification | dcc_modelspec.tsgarch.multi_estimate |
| FFT density, distribution and quantile method | dfft dfft.gogarch.fft dfft.gogarch.fftsim pfft pfft.gogarch.fft pfft.gogarch.fftsim qfft qfft.gogarch.fft qfft.gogarch.fftsim |
| Dow Jones 30 Constituents Closing Value log Weekly Return | dji30retw |
| Engle-Sheppard Constant Correlation Test | escc_test |
| Score Method | estfun.cgarch.estimate estfun.dcc.estimate |
| Estimates a model given a specification. | estimate estimate.cgarch.spec estimate.dcc.spec estimate.gogarch.spec |
| Expected Shortfall (ES) method for predicted and simulated objects | expected_shortfall expected_shortfall.cgarch.predict expected_shortfall.cgarch.simulate expected_shortfall.dcc.predict expected_shortfall.dcc.simulate expected_shortfall.gogarch.predict expected_shortfall.gogarch.simulate |
| The Fast ICA (FASTICA) | fastica |
| Extract Model Fitted Values | fitted fitted.cgarch.estimate fitted.cgarch.predict fitted.cgarch.simulate fitted.dcc.estimate fitted.dcc.predict fitted.dcc.simulate fitted.gogarch.estimate fitted.gogarch.predict fitted.gogarch.simulate |
| Global Financial Indices Closing Value log Weekly Return | globalindices |
| GOGARCH Model specification | gogarch_modelspec |
| Extract Log-Likelihood | logLik logLik.cgarch.estimate logLik.dcc.estimate logLik.gogarch.estimate |
| News Impact Surface | newsimpact.cgarch.estimate newsimpact.dcc.estimate newsimpact.gogarch.estimate |
| Probability Integral Transform (PIT) for weighted FFT densities | pit.gogarch.fft |
| Dynamic Correlation Model Plots | plot.cgarch.estimate plot.dcc.estimate |
| News Impact Surface Plot | plot.tsmarch.newsimpact |
| Model Prediction | predict predict.cgarch.estimate predict.dcc.estimate predict.gogarch.estimate |
| Model Estimation Summary Print method | print.summary.cgarch.estimate print.summary.dcc.estimate print.summary.gogarch.estimate print.summary.tsmarch.estimate |
| Print method for escc test | print.tstest.escc |
| The Robust Accurate, Direct ICA ALgorithm (RADICAL) | radical |
| Extract Model Residuals | residuals residuals.cgarch.estimate residuals.dcc.estimate residuals.gogarch.estimate |
| Model Simulation | simulate simulate.cgarch.estimate simulate.dcc.estimate simulate.gogarch.estimate |
| Model Estimation Summary | summary summary.cgarch.estimate summary.dcc.estimate summary.gogarch.estimate |
| Weighted Moments Aggregation | tsaggregate tsaggregate.cgarch.estimate tsaggregate.cgarch.predict tsaggregate.cgarch.simulate tsaggregate.dcc.estimate tsaggregate.dcc.predict tsaggregate.dcc.simulate tsaggregate.gogarch.estimate tsaggregate.gogarch.predict tsaggregate.gogarch.simulate |
| Cokurtosis Extractor | tscokurt tscokurt.gogarch.estimate tscokurt.gogarch.predict tscokurt.gogarch.simulate |
| Convolution | tsconvolve tsconvolve.gogarch.estimate tsconvolve.gogarch.predict tsconvolve.gogarch.simulate |
| Correlation Extractor | tscor tscor.cgarch.estimate tscor.cgarch.predict tscor.cgarch.simulate tscor.dcc.estimate tscor.dcc.predict tscor.dcc.simulate tscor.gogarch.estimate tscor.gogarch.predict tscor.gogarch.simulate |
| Coskewness Extractor | tscoskew tscoskew.gogarch.estimate tscoskew.gogarch.predict tscoskew.gogarch.simulate |
| Covariance Extractor | tscov tscov.cgarch.estimate tscov.cgarch.predict tscov.cgarch.simulate tscov.dcc.estimate tscov.dcc.predict tscov.dcc.simulate tscov.gogarch.estimate tscov.gogarch.predict tscov.gogarch.simulate |
| Model Filtering | tsfilter tsfilter.cgarch.estimate tsfilter.dcc.estimate tsfilter.gogarch.estimate |
| Value at Risk (VaR) method for predicted and simulated objects | value_at_risk value_at_risk.cgarch.predict value_at_risk.cgarch.simulate value_at_risk.dcc.predict value_at_risk.dcc.simulate value_at_risk.gogarch.predict value_at_risk.gogarch.simulate |
| The Covariance Matrix of the Estimated Parameters | vcov vcov.cgarch.estimate vcov.dcc.estimate |
