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Small Sample Asymptotics for Credit Risk Portfolios

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2005

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Ocker, Dirk

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http://nbn-resolving.de/urn:nbn:de:bsz:352-275751
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https://doi.org/10.1198/106186005X48948
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Journal of Computational and Graphical Statistics. 2005, 14(2), pp. 339-351. ISSN 1061-8600. eISSN 1537-2715. Available under: doi: 10.1198/106186005X48948

Zusammenfassung

This article considers small sample asymptotics for the distribution of the total loss Sn of a credit risk portfolio. For portfolios with a few exceptionally high potential loss values, the distribution of Sn turns out to be bimodal. Direct approximation by Esscher tilting does not capture this feature. An improved recursive algorithm is proposed. The new approach leads to a more accurate small sample approximation that models bimodality in the presence of outliers. The results are illustrated by a simulated example as well as an example of an observed credit risk portfolio.

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510 Mathematik

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ISO 690BERAN, Jan, Dirk OCKER, 2005. Small Sample Asymptotics for Credit Risk Portfolios. In: Journal of Computational and Graphical Statistics. 2005, 14(2), pp. 339-351. ISSN 1061-8600. eISSN 1537-2715. Available under: doi: 10.1198/106186005X48948
BibTex
@article{Beran2005Small-27575,
  year={2005},
  doi={10.1198/106186005X48948},
  title={Small Sample Asymptotics for Credit Risk Portfolios},
  number={2},
  volume={14},
  issn={1061-8600},
  journal={Journal of Computational and Graphical Statistics},
  pages={339--351},
  author={Beran, Jan and Ocker, Dirk}
}
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