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Modelling macroeconomic effects and expert judgements in operational risk : a Bayesian approach

Author

Listed:
  • Holger Capa Santos

    (Departamento de Geologia [Quito] - EPN - Escuela Politécnica Nacional)

  • Marie Kratz

    (MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5 - UPD5 - Université Paris Descartes - Paris 5 - INSMI-CNRS - Institut National des Sciences Mathématiques et de leurs Interactions - CNRS Mathématiques - CNRS - Centre National de la Recherche Scientifique, ESSEC Business School)

  • Franklin Mosquera Munoz

    (Departamento de Geologia [Quito] - EPN - Escuela Politécnica Nacional)

Abstract

This work presents a contribution on operational risk under a general Bayesian context incorporating information on market risk pro le, experts and operational losses, taking into account the general macroeconomic environment as well. It aims at estimating a characteristic parameter of the distributions of the sources, market risk pro le, experts and operational losses, chosen here at a location parameter. It generalizes under more realistic conditions a study realized by Lambrigger, Shevchenko and Wuthrich, and analyses macroeconomic e ects on operational risk. It appears that severities of operational losses are more related to the macroeconomics environment than usually assumed.

Suggested Citation

  • Holger Capa Santos & Marie Kratz & Franklin Mosquera Munoz, 2012. "Modelling macroeconomic effects and expert judgements in operational risk : a Bayesian approach," Working Papers hal-00690448, HAL.
    • Handle: RePEc:hal:wpaper:hal-00690448
    Note: View the original document on HAL open archive server: https://essec.hal.science/hal-00690448
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    Cited by:

    1. Irina Vinogradova-Zinkevič, 2021. "Application of Bayesian Approach to Reduce the Uncertainty in Expert Judgments by Using a Posteriori Mean Function," Mathematics, MDPI, vol. 9(19), pages 1-23, October.

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