Modeling Operational Risk Depending on Covariates: An Empirical Investigation

30 Pages Posted: 19 Sep 2018

See all articles by Paul Embrechts

Paul Embrechts

Swiss Federal Institute of Technology Zurich; Swiss Finance Institute

Kamil Mizgier

ETH Zürich - Department of Management, Technology, and Economics (D-MTEC)

Xian Chen

University of Oregon

Date Written: September 11, 2018

Abstract

The importance of operational risk management in financial and commodity markets has increased significantly over the last few decades. This paper demonstrates the application of a nonhomogeneous Poisson model and dynamic extreme value theory (EVT) incorporating covariates on estimating frequency, severity and risk measures for operational risk. Compared with a classical EVT approach, the dynamic EVT gives a better performance with respect to the statistical fit and realism. It is also flexible enough to handle different types of empirical data. In our model, we include firm-specific covariates associated with internal control weaknesses (ICWs) and show empirically that firms with higher incidences of selected ICWs have higher time-varying severities for operational risk. Our methodology provides risk managers and regulators with a tool that uncovers the nonobvious patterns hidden in operational risk data.

Keywords: operational risk, dynamic extreme value theory (EVT), generalized additive models, covariates, internal control weaknesses.

Suggested Citation

Embrechts, Paul and Mizgier, Kamil and Chen, Xian, Modeling Operational Risk Depending on Covariates: An Empirical Investigation (September 11, 2018). Journal of Operational Risk, Vol. 13, No. 3, 2018. Available at SSRN: https://ssrn.com/abstract=3247538

Paul Embrechts

Swiss Federal Institute of Technology Zurich ( email )

ETH-Zentrum
CH-8092 Zurich
Switzerland

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Kamil Mizgier (Contact Author)

ETH Zürich - Department of Management, Technology, and Economics (D-MTEC) ( email )

Weinbergstrasse 56/58
Zurich, 8092
Switzerland

Xian Chen

University of Oregon ( email )

1280 University of Oregon
Eugene, OR 97403
United States

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