Modeling Catastrophic Operational Risk Using a Compound Neyman–Scott Clustering Model

25 Pages Posted: 26 Feb 2018

See all articles by Zied Gara

Zied Gara

University of Sousse - MaPReCoB Research Unit

Lotfi BelKacem

University of Sousse - Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ)

Date Written: February 23, 2018

Abstract

Within a loss distribution approach (LDA) framework, we propose to model catastrophic operational risk using a compound Neyman–Scott clustering model. The particularity of this compound model is that it relies on a Neyman–Scott process (the frequency component of the LDA) to model the occurrence behavior of catastrophic operational loss events. The motivation behind this is that catastrophic operational risk may be the manifestation of a two-level risk generation mechanism: on the first level, natural and human-made catastrophes (referred to as operational storms) occur and trigger, on the second level, clusters of catastrophic operational loss events. A graphical analysis based on a historical series of 334 extreme operational loss events supports the clustering structure of the event occurrences. The calibration of the Neyman–Scott process reveals a satisfactory model fitness and underlines the high vulnerability of financial organizations to eventual operational storms.

Keywords: loss distribution approach (LDA), human-made catastrophes, natural catastrophes, Neyman–Scott process, operational risk, temporal clustering

Suggested Citation

Gara, Zied and BelKacem, Lotfi, Modeling Catastrophic Operational Risk Using a Compound Neyman–Scott Clustering Model (February 23, 2018). Journal of Operational Risk, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3128806

Zied Gara (Contact Author)

University of Sousse - MaPReCoB Research Unit ( email )

Sousse
Tunisia

Lotfi BelKacem

University of Sousse - Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ) ( email )

Sousse
Tunisia

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