Functions for modeling operational (value-at-)risk. The implementation comprises functions for modeling loss frequencies and loss severities with plain, mixed (Frigessi et al. (2012) <doi:10.1023/A:1024072610684>) or spliced distributions using Maximum Likelihood estimation and Bayesian approaches (Ergashev et al. (2013) <doi:10.21314/JOP.2013.131>). In particular, the parametrization of tail distributions includes fitting of Tukey-type distributions (Kuo and Headrick (2014) <doi:10.1155/2014/645823>). Furthermore, the package contains the modeling of bivariate dependencies between loss severities and frequencies, Monte Carlo simulation for total loss estimation as well as a closed-form approximation based on Degen (2010) <doi:10.21314/JOP.2010.084> to determine the value-at-risk.
Version: | 1.0 |
Imports: | evmix, VineCopula, tea, actuar, vcd, goftest, truncnorm, ReIns, MASS |
Suggests: | knitr, rmarkdown |
Published: | 2018-01-09 |
Author: | Christina Zou [aut,cre], Marius Pfeuffer [aut], Matthias Fischer [aut], Kristina Dehler [ctb], Nicole Derfuss [ctb], Benedikt Graswald [ctb], Linda Moestel [ctb], Jixuan Wang [ctb], Leonie Wicht [ctb] |
Maintainer: | Christina Zou <christina.zou at maths.ox.ac.uk> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | OpVaR results |
Reference manual: | OpVaR.pdf |
Vignettes: |
OpVaR: Modeling Operational (Value-At-)Risk in R |
Package source: | OpVaR_1.0.tar.gz |
Windows binaries: | r-devel: OpVaR_1.0.zip, r-release: OpVaR_1.0.zip, r-oldrel: OpVaR_1.0.zip |
OS X El Capitan binaries: | r-release: OpVaR_1.0.tgz |
OS X Mavericks binaries: | r-oldrel: OpVaR_1.0.tgz |
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