Package: matrisk 0.1.0
Quentin Lajaunie
matrisk: Macroeconomic-at-Risk
The Macroeconomics-at-Risk (MaR) approach is based on a two-step semi-parametric estimation procedure that allows to forecast the full conditional distribution of an economic variable at a given horizon, as a function of a set of factors. These density forecasts are then be used to produce coherent forecasts for any downside risk measure, e.g., value-at-risk, expected shortfall, downside entropy. Initially introduced by Adrian et al. (2019) <doi:10.1257/aer.20161923> to reveal the vulnerability of economic growth to financial conditions, the MaR approach is currently extensively used by international financial institutions to provide Value-at-Risk (VaR) type forecasts for GDP growth (Growth-at-Risk) or inflation (Inflation-at-Risk). This package provides methods for estimating these models. Datasets for the US and the Eurozone are available to allow testing of the Adrian et al (2019) model. This package constitutes a useful toolbox (data and functions) for private practitioners, scholars as well as policymakers.
Authors:
matrisk_0.1.0.tar.gz
matrisk_0.1.0.tar.gz(r-4.5-noble)matrisk_0.1.0.tar.gz(r-4.4-noble)
matrisk_0.1.0.tgz(r-4.4-emscripten)matrisk_0.1.0.tgz(r-4.3-emscripten)
matrisk.pdf |matrisk.html✨
matrisk/json (API)
# Install 'matrisk' in R: |
install.packages('matrisk', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:6869e9e5cc. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 18 2024 |
R-4.5-linux | OK | Dec 18 2024 |
Exports:f_compile_quantilef_distribf_distrib_histof_ESf_VaR
Dependencies:dfoptimlatticeMASSMatrixMatrixModelsmisc3dmnormtnumDerivplot3DquantregsnSparseMsurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Historical data for the eurozone (GDP and Financial Conditions) from 2008:Q4 to 2022:Q3 | data_euro |
Historical data for the US (GDP and Financial Conditions) from 1973:Q1 to 2022:Q3 | data_US |
Estimation of quantiles | f_compile_quantile |
Distribution | f_distrib |
Historical distributions | f_distrib_histo |
Expected Shortfall | f_ES |
Value-at-Risk | f_VaR |