Operational Risk Bias Quanti fication and Correction

12 Pages Posted: 30 Dec 2014

See all articles by Roberto Torresetti

Roberto Torresetti

Università degli Studi di Milano; Intesa SanPaolo

Giacomo Le Pera

illimity Bank

Date Written: December 30, 2014

Abstract

Identifying the Maximum Domain of Attraction (MDA) of a given (severity) distribution in Operational Risk is not an easy task with a significant impact on the Value at Risk (VaR). One could resort to the result of Pickands (1975) and select a suitably high threshold to model the excesses so that the Generalized Pareto Distribution (GPD) approximation holds and the shape parameter estimate belong to the correct MDA. On the other hand moving the threshold to the right leaves us with only a limited number of observations which in turn increases the statistical error of the (shape) parameter estimate resulting in an upward bias in the Value at Risk (VaR) calculation. We propose here a methodology to measure and correct this bias thus reducing this tradeoff. We finally present results showing the goodness of this correction.

Suggested Citation

Torresetti, Roberto and Le Pera, Giacomo, Operational Risk Bias Quanti fication and Correction (December 30, 2014). Available at SSRN: https://ssrn.com/abstract=2543787 or http://dx.doi.org/10.2139/ssrn.2543787

Roberto Torresetti (Contact Author)

Università degli Studi di Milano ( email )

via Festa del Perdono, 7
Milano
Italy

Intesa SanPaolo ( email )

Milan
Italy

Giacomo Le Pera

illimity Bank ( email )

Via Soperga
Milano
Italy

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