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.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: stats, quantreg, sn, dfoptim, plot3D
Published: 2023-05-02
Author: Quentin Lajaunie [aut, cre], Guillaume Flament [aut], Christophe Hurlin [aut]
Maintainer: Quentin Lajaunie <quentin_lajaunie at hotmail.fr>
License: GPL-3
NeedsCompilation: no
CRAN checks: matrisk results

Documentation:

Reference manual: matrisk.pdf

Downloads:

Package source: matrisk_0.1.0.tar.gz
Windows binaries: r-devel: matrisk_0.1.0.zip, r-release: matrisk_0.1.0.zip, r-oldrel: matrisk_0.1.0.zip
macOS binaries: r-release (arm64): matrisk_0.1.0.tgz, r-oldrel (arm64): matrisk_0.1.0.tgz, r-release (x86_64): matrisk_0.1.0.tgz

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