Package: tsgarch 1.0.4
Alexios Galanos
tsgarch: Univariate GARCH Models
Multiple flavors of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a large choice of conditional distributions. Methods for specification, estimation, prediction, filtering, simulation, statistical testing and more. Represents a partial re-write and re-think of 'rugarch', making use of automatic differentiation for estimation.
Authors:
tsgarch_1.0.4.tar.gz
tsgarch_1.0.4.zip(r-4.5)tsgarch_1.0.4.zip(r-4.4)tsgarch_1.0.4.zip(r-4.3)
tsgarch_1.0.4.tgz(r-4.4-x86_64)tsgarch_1.0.4.tgz(r-4.4-arm64)tsgarch_1.0.4.tgz(r-4.3-x86_64)tsgarch_1.0.4.tgz(r-4.3-arm64)
tsgarch_1.0.4.tar.gz(r-4.5-noble)tsgarch_1.0.4.tar.gz(r-4.4-noble)
tsgarch.pdf |tsgarch.html✨
tsgarch/json (API)
NEWS
| # Install 'tsgarch' in R: |
| install.packages('tsgarch', repos = c('https://tsmodels.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tsmodels/tsgarch/issues
Last updated 4 days agofrom:448bd19009. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 14 2024 |
| R-4.5-win-x86_64 | OK | Nov 14 2024 |
| R-4.5-linux-x86_64 | OK | Nov 14 2024 |
| R-4.4-win-x86_64 | OK | Nov 14 2024 |
| R-4.4-mac-x86_64 | OK | Nov 14 2024 |
| R-4.4-mac-aarch64 | OK | Nov 14 2024 |
| R-4.3-win-x86_64 | OK | Nov 14 2024 |
| R-4.3-mac-x86_64 | OK | Nov 14 2024 |
| R-4.3-mac-aarch64 | OK | Nov 14 2024 |
Exports:as_flextablebenchmark_fcpbenchmark_laurentbreadestfunestimate.tsgarch.specgarch_modelspecnewsimpactnloptr_fast_optionsnloptr_global_optionsomegapersistenceto_multi_estimate
Dependencies:alabamaaskpassbase64encbslibcachemclicodetoolscpp11data.tabledigestDistributionUtilsevaluatefastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverfsfuturefuture.applygdtoolsGeneralizedHyperbolicgenericsglobalsgluehighrhtmltoolsjquerylibjsonliteKernSmoothknitrlatticelifecyclelistenvlubridateMASSMatrixmemoisemevmimenleqslvnloptrnumDerivofficeropensslparallellyprogressrR6raggrappdirsrbibutilsRcppRcppArmadilloRcppEigenRdpackrlangrmarkdownRsolnpsandwichsassSkewHyperbolicsyssystemfontstextshapingtimechangetinytexTMBtruncnormtsdistributionstsmethodsuuidxfunxml2xtsyamlzipzoo
Benchmark
Rendered frombenchmark.Rmdusingknitr::rmarkdownon Nov 14 2024.Last update: 2024-10-11
Started: 2024-04-22
GARCH Models
Rendered fromgarch_models.Rmdusingknitr::rmarkdownon Nov 14 2024.Last update: 2024-10-11
Started: 2024-04-22
Package Demo
Rendered fromdemonstration.Rmdusingknitr::rmarkdownon Nov 14 2024.Last update: 2024-10-11
Started: 2024-04-22
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Combine univariate GARCH specifications into a multi-specification object | +.tsgarch.spec |
| Akaike's An Information Criterion | AIC AIC.tsgarch.estimate |
| Transform an object into flextable | as_flextable.benchmark as_flextable.benchmark.fcp as_flextable.benchmark.laurent |
| Transform a summary object into flextable | as_flextable.summary.tsgarch.estimate |
| FCP GARCH Benchmark | benchmark_fcp |
| Laurent APARCH Benchmark | benchmark_laurent |
| Bayesian Information Criterion | BIC BIC.tsgarch.estimate |
| Bread Method | bread.tsgarch.estimate |
| Extract Model Coefficients | coef coef.tsgarch.estimate |
| Confidence Intervals for Model Parameters | confint confint.tsgarch.estimate |
| Deutschemark/British pound Exchange Rate | dmbp |
| Score Method | estfun.tsgarch.estimate |
| Estimates an GARCH model given a specification object using maximum likelihood and autodiff | estimate estimate.tsgarch.multispec estimate.tsgarch.spec |
| Extract Model Fitted Values | fitted fitted.tsgarch.estimate fitted.tsgarch.multi_estimate |
| GARCH Model Specification | garch_modelspec |
| Half Life | halflife halflife.tsgarch.estimate |
| Extract Log-Likelihood | logLik logLik.tsgarch.estimate |
| News Impact Curve | newsimpact newsimpact.tsgarch.estimate |
| Japanese NIKKEI Stock Index | nikkei |
| Default options for nloptr solver | nloptr_fast_options nloptr_global_options nloptr_options |
| Extract the Number of Observations | nobs nobs.tsgarch.estimate |
| Omega (Variance Equation Intercept) | omega omega.tsgarch.estimate omega.tsgarch.spec |
| Model Persistence | persistence persistence.tsgarch.estimate persistence.tsgarch.spec |
| Probability Integral Transform (PIT) | pit pit.tsgarch.estimate |
| Estimated Model Plots | plot.tsgarch.estimate |
| News Impact Plot | plot.tsgarch.newsimpact |
| Model Prediction | predict predict.tsgarch.estimate |
| Model Estimation Summary Print method | print.summary.tsgarch.estimate |
| Profile Summary Print method | print.summary.tsgarch.profile |
| Extract Model Residuals | residuals residuals.tsgarch.estimate residuals.tsgarch.multi_estimate |
| Extract Volatility (Conditional Standard Deviation) | sigma sigma.tsgarch.estimate sigma.tsgarch.multi_estimate |
| Model Simulation | simulate simulate.tsgarch.spec |
| GARCH Model Estimation Summary | summary summary.tsgarch.estimate |
| GARCH Profile Summary | summary.tsgarch.profile |
| Convert a list of tsgarch.estimate objects to a multi_estimate object | to_multi_estimate |
| Walk Forward Rolling Backtest | tsbacktest tsbacktest.tsgarch.spec |
| Model Equation (LaTeX) | tsequation tsequation.tsgarch.estimate |
| Model Filtering | tsfilter tsfilter.tsgarch.estimate tsfilter.tsgarch.spec |
| Model Parameter Profiling | tsprofile tsprofile.tsgarch.spec |
| Unconditional Value | unconditional unconditional.tsgarch.estimate unconditional.tsgarch.spec |
| The Covariance Matrix of the Estimated Parameters | vcov vcov.tsgarch.estimate |
