Statistical Methods for Modeling 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) ) or spliced distributions using Maximum Likelihood estimation and Bayesian approaches (Ergashev et al. (2013) ). In particular, the parametrization of tail distributions includes the 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.


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install.packages("OpVaR")

1.0.5 by Christina Zou, a year ago


Browse source code at https://github.com/cran/OpVaR


Authors: 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]


Documentation:   PDF Manual  


GPL-3 license


Imports evmix, VineCopula, tea, actuar, vcd, goftest, truncnorm, ReIns, MASS, pracma

Suggests knitr, rmarkdown


See at CRAN