OpVaR: Statistical Methods for Modelling Operational Risk

Functions for computing the value-at-risk in compound Poisson models. 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 the 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.

Package details

AuthorChristina Zou [aut,cre], Marius Pfeuffer [aut], Matthias Fischer [aut], Nina Buoni [ctb], Kristina Dehler [ctb], Nicole Derfuss [ctb], Benedikt Graswald [ctb], Linda Moestel [ctb], Jixuan Wang [ctb], Leonie Wicht [ctb]
MaintainerChristina Zou <christina.zou@maths.ox.ac.uk>
LicenseGPL-3
Version1.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("OpVaR")

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OpVaR documentation built on Sept. 8, 2021, 5:07 p.m.