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Urn-based models for dependent credit risks and their calibration through EM algorithm

Author

Listed:
  • Riccardo Gusso

    (Department of Applied Mathematics, University of Venice)

  • Uwe Schmock

    (Institute for Mathematical Methods in Economics, Vienna University of Technology)

Abstract

In this contribution we analyze two models for the joint probability of defaults of dependent credit risks that are based on a generalisation of Polya urn scheme. In particular we focus our attention on the problems related to the maximum likelihood estimation of the parameters involved, and to this purpose we introduce an approach based on the use of the Expectation-Maximization algorithm. We show how to implement it in this context, and then we analyze the results obtained, comparing them with results obtained by other approaches.

Suggested Citation

  • Riccardo Gusso & Uwe Schmock, 2008. "Urn-based models for dependent credit risks and their calibration through EM algorithm," Working Papers 163, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:163
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    References listed on IDEAS

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    1. Iain D. Currie, 1995. "Maximum Likelihood Estimation and Mathematica," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(3), pages 379-394, September.
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      JEL classification:

      • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
      • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions

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