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Estimation of Probabilities for Ordered Sets and Application to Calibration of Rating Models

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  • Gustavo F. Serenelli
  • Emiliano Delfau

Abstract

The goal of this document is to present a methodology for estimating probabilities for ordered sets. This may have several practical applications such as calibration of Rating Models, estimation of Mortality Tables or measurement of side effects related to different doze sizes. In order to do this, an Objective / Non Informative Bayesian approach is applied, through which, using a multidimensional Jeffreys prior, a posterior distribution may be inferred for each of the probabilities being estimated

Suggested Citation

  • Gustavo F. Serenelli & Emiliano Delfau, 2023. "Estimation of Probabilities for Ordered Sets and Application to Calibration of Rating Models," CEMA Working Papers: Serie Documentos de Trabajo. 849, Universidad del CEMA.
    • Handle: RePEc:cem:doctra:849
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    File URL: https://ucema.edu.ar/publicaciones/download/documentos/849.pdf
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    References listed on IDEAS

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    1. Katja Pluto & Dirk Tasche, 2006. "Estimating Probabilities of Default for Low Default Portfolios," Springer Books, in: Bernd Engelmann & Robert Rauhmeier (ed.), The Basel II Risk Parameters, chapter 0, pages 79-103, Springer.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Bayesian estimation; probability estimation; uninformative prior; rating calibration; low default; ordered sets; jeffreys prior.;
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