An extreme value approach for modeling Operational Risk losses depending on covariates

By V. Chavez‐Demoulin, Paul Embrechts, Marius Hofert. 2016

132 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b0697996d8e264ba2562698cf2acfaf4f7853f91

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Marius Hofert
2. Jianxi Su
3. Paul Embrechts
4. Edward Furman
5. Andrew J. Patton
6. Eike C. Brechmann
7. Claudia Czado
8. Kjersti Aas

In Global and Planetary Change

1. Marius Hofert
2. Paul Embrechts

In Statistics and Probability

1. Marius Hofert
2. Jianxi Su
3. Paul Embrechts
4. Edward Furman
5. Toshinao Yoshiba

Citations in the corpus

• Statistics and Quantitative Risk Management for Banking and Insurance (2014, methodology): “More recent statistical techniques in use are for instance extreme quantile estimation based on regime-switching models and lasso-technology, see Chavez-Demoulin et al. (2013a).”
• A FORM OF MULTIVARIATE PARETO DISTRIBUTION WITH APPLICATIONS TO FINANCIAL RISK MEASUREMENT (2016, background): “; Koedijk et al. (1990), Longin (1996), Gabaix et al. (2003) for applications in general 6 financial phenomena; Cebri´an et al. (2003) for applications in insurance pricing; and Soprano et al. (2010), Chavez-Demoulin et al. (2015) for applications in risk management. Specifically, the probability law ”