Vine Based (Un)Conditional Portfolio Risk Measure Estimation R package portvine version 1.0.3 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. Software Depends: R (>= 2.10) Imports: checkmate, data.table, dplyr, dtplyr, future.apply, methods, ppcor, Rcpp (>= 0.12.12), rlang, rugarch, rvinecopulib, tidyr LinkingTo: BH, kde1d, Rcpp, RcppEigen, RcppThread, rvinecopulib, wdm Suggests: covr, future, ggplot2, ggtext, knitr, patchwork, rmarkdown, scales, testthat (>= 3.0.0) Emanuel Sommer <emanuel_sommer@gmx.de> Comprehensive R Archive Network (CRAN) Emanuel Sommer [cre, aut] MIT + file LICENSE (https://CRAN.R-project.org/package=portvine/LICENSE) 2024-01-18 application/tgz https://CRAN.R-project.org/package=portvine doi:10.32614/CRAN.package.portvine