Package: portvine 1.0.3.9000

Emanuel Sommer

portvine: Vine Based (Un)Conditional Portfolio Risk Measure Estimation

Following Sommer (2022) <https://mediatum.ub.tum.de/1658240> portfolio level risk estimates (e.g. Value at Risk, Expected Shortfall) are estimated by modeling each asset univariately by an ARMA-GARCH model and then their cross dependence via a Vine Copula model in a rolling window fashion. One can even condition on variables/time series at certain quantile levels to stress test the risk measure estimates.

Authors:Emanuel Sommer [cre, aut]

portvine_1.0.3.9000.tar.gz
portvine_1.0.3.9000.zip(r-4.5)portvine_1.0.3.9000.zip(r-4.4)portvine_1.0.3.9000.zip(r-4.3)
portvine_1.0.3.9000.tgz(r-4.4-x86_64)portvine_1.0.3.9000.tgz(r-4.4-arm64)portvine_1.0.3.9000.tgz(r-4.3-x86_64)portvine_1.0.3.9000.tgz(r-4.3-arm64)
portvine_1.0.3.9000.tar.gz(r-4.5-noble)portvine_1.0.3.9000.tar.gz(r-4.4-noble)
portvine_1.0.3.9000.tgz(r-4.4-emscripten)portvine_1.0.3.9000.tgz(r-4.3-emscripten)
portvine.pdf |portvine.html
portvine/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/emanuelsommer/portvine/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

expected-shortfallgarch-modelsvalue-at-riskvine-copulas

5.34 score 22 stars 6 scripts 227 downloads 12 exports 70 dependencies

Last updated 10 months agofrom:f1e58e717c. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-win-x86_64OKNov 17 2024
R-4.5-linux-x86_64OKNov 17 2024
R-4.4-win-x86_64OKNov 17 2024
R-4.4-mac-x86_64OKNov 17 2024
R-4.4-mac-aarch64OKNov 17 2024
R-4.3-win-x86_64OKNov 17 2024
R-4.3-mac-x86_64OKNov 17 2024
R-4.3-mac-aarch64OKNov 17 2024

Exports:default_garch_specest_esest_varestimate_risk_rollfitted_marginalsfitted_vinesmarginal_settingsrisk_estimatesroll_residualsshowsummaryvine_settings

Dependencies:assertthatbackportsBHcheckmatechronclicodetoolscpp11data.tabledigestDistributionUtilsdplyrdtplyrfansiFNNfracdifffuturefuture.applyGeneralizedHyperbolicgenericsglobalsgluekde1dkernlabKernSmoothkslatticelifecyclelistenvmagrittrMASSMatrixmclustmgcvmulticoolmvtnormnlmenloptrnumDerivparallellypillarpkgconfigppcorpracmapurrrR6randtoolboxRcppRcppArmadilloRcppEigenRcppThreadrlangrngWELLRsolnprugarchrvinecopulibSkewHyperbolicspdstringistringrtibbletidyrtidyselecttruncnormutf8vctrswdmwithrxtszoo

Get started

Rendered fromget_started.Rmdusingknitr::rmarkdownon Nov 17 2024.

Last update: 2022-05-26
Started: 2021-11-07

Readme and manuals

Help Manual

Help pageTopics
Default specifications for ARMA-GARCH modelsdefault_garch_spec
Estimate the Expected Shortfall (ES)est_es
Estimate the Value at Risk (VaR)est_var
(Un-)conditional rolling risk estimation using vine copulasestimate_risk_roll
Accessor method for the fitted marginal models of (cond_)portvine_roll objectsfitted_marginals fitted_marginals,portvine_roll-method
Accessor method for the fitted vine copula models of (cond_)portvine_roll objectsfitted_vines fitted_vines,portvine_roll-method
S4 class for the marginal settingsmarginal_settings marginal_settings-class show,marginal_settings-method
S4 output class for the function 'estimate_risk_roll()'cond_portvine_roll-class portvine_roll-class show,cond_portvine_roll-method show,portvine_roll-method summary,cond_portvine_roll-method summary,portvine_roll-method
Accessor methods for the risk estimates of (cond_)portvine_roll objectsrisk_estimates risk_estimates,cond_portvine_roll-method risk_estimates,portvine_roll-method
Extract fitted standardized residuals from a uGARCHroll objectroll_residuals
A sample of log returns for 3 assets.sample_returns_small
S4 class for the vine settingsshow,vine_settings-method vine_settings vine_settings-class