Expected Shortfall Estimation for Apparently Infinite-Mean Models of Operational Risk

Quantitative Finance, Volume 16, 2016 - Issue 10

23 Pages Posted: 27 Oct 2015 Last revised: 12 Jan 2017

See all articles by Pasquale Cirillo

Pasquale Cirillo

ZHAW School of Management and Law

Nassim Nicholas Taleb

New York University (NYU) - NYU Tandon School of Engineering

Date Written: October 27, 2015

Abstract

Statistical analyses on actual data depict operational risk as an extremely heavy-tailed phenomenon, able to generate losses so extreme as to suggest the use of infinite-mean models. But no loss can actually destroy more than the entire value of a bank or of a company, and this upper bound should be considered when dealing with tail-risk assessment.

Introducing what we call the dual distribution, we show how to deal with heavy-tailed phenomena with a remote yet finite upper bound. We provide methods to compute relevant tail quantities such as the Expected Shortfall (ES), which is not available under infinite-mean models, allowing adequate provisioning and capital allocation. This also permits a measurement of fragility.

The main difference between our approach and a simple truncation is in the smoothness of the transformation between the original and the dual distribution.

Our methodology is useful with apparently infinite-mean phenomena, as in the case of operational risk, but it can be applied in all those situations involving extreme fat-tails and bounded support.

Keywords: Operational risk, Expected Shortfall, Infinite Mean, VaR

Suggested Citation

Cirillo, Pasquale and Taleb, Nassim Nicholas, Expected Shortfall Estimation for Apparently Infinite-Mean Models of Operational Risk (October 27, 2015). Quantitative Finance, Volume 16, 2016 - Issue 10, Available at SSRN: https://ssrn.com/abstract=2681006 or http://dx.doi.org/10.2139/ssrn.2681006

Pasquale Cirillo

ZHAW School of Management and Law ( email )

St.-Georgen-Platz 2
Winterthur, 8401
Switzerland

Nassim Nicholas Taleb (Contact Author)

New York University (NYU) - NYU Tandon School of Engineering ( email )

6 MetroTech Center
Brooklyn, NY 11201
United States

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