Modeling operational risk data reported above a time-varying threshold

Pavel Shevchenko, Grigory Temnov

Research output: Contribution to journalArticle

Abstract

Typically, 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.
Original languageEnglish
Pages (from-to)19-42
Number of pages24
JournalJournal of Operational Risk
Volume4
Issue number2
DOIs
Publication statusPublished - 2009
Externally publishedYes

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