OpVaR: Statistical Methods for Modeling Operational Risk
Version 1.0

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) ) or spliced distributions using Maximum Likelihood estimation and Bayesian approaches (Ergashev et al. (2013) ). In particular, the parametrization of tail distributions includes fitting of Tukey-type distributions (Kuo and Headrick (2014) ). 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) to determine the value-at-risk.

Package details

AuthorChristina 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]
Date of publication2018-01-09 18:28:47 UTC
MaintainerChristina Zou <[email protected]>
Package repositoryView on CRAN
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OpVaR documentation built on Jan. 10, 2018, 1:07 a.m.