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Modeling operational risk data reported above a time-varying threshold

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  • Pavel V. Shevchenko
  • Grigory Temnov
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    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.

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    File URL: http://arxiv.org/pdf/0904.4075
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 0904.4075.

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    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
    Handle: RePEc:arx:papers:0904.4075

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    Web page: http://arxiv.org/

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    1. Chavez-Demoulin, V. & Embrechts, P. & Neslehova, J., 2006. "Quantitative models for operational risk: Extremes, dependence and aggregation," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2635-2658, October.
    2. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    3. Pavel V. Shevchenko, 2009. "Implementing Loss Distribution Approach for Operational Risk," Papers 0904.1805, arXiv.org, revised Jul 2009.
    4. Gareth W. Peters & Pavel V. Shevchenko & Mario V. W\"uthrich, 2009. "Dynamic operational risk: modeling dependence and combining different sources of information," Papers 0904.4074, arXiv.org, revised Jul 2009.
    5. Xiaolin Luo & Pavel V. Shevchenko, 2009. "Computing Tails of Compound Distributions Using Direct Numerical Integration," Papers 0904.0830, arXiv.org, revised Feb 2010.
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    Cited by:
    1. Dominique Guegan & Bertrand Hassani & Cédric Naud, 2011. "An efficient threshold choice for operational risk capital computation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00790217, HAL.

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