Modeling operational risk data reported above a time-varying threshold
AbstractTypically, operational risk losses are reported above a threshold. Fitting data reported above a constant threshold is a well known and studied problem. However, in practice, the losses are scaled for business and other factors before the fitting and thus the threshold is varying across the scaled data sample. A reporting level may also change when a bank changes its reporting policy. We present both the maximum likelihood and Bayesian Markov chain Monte Carlo approaches to fitting the frequency and severity loss distributions using data in the case of a time varying threshold. Estimation of the annual loss distribution accounting for parameter uncertainty is also presented.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 0904.4075.
Date of creation: Apr 2009
Date of revision: Jul 2009
Publication status: Published in The Journal of Operational Risk 4(2), pp. 19-42, 2009 www.journalofoperationalrisk.com
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Documents de travail du Centre d'Economie de la Sorbonne
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