Comparison of dependence in factor models with application to credit risk portfolios

Michel Denuit; Esther Frostig

doi:10.1017/S0269964808000090

Comparison of dependence in factor models with application to credit risk portfolios

Michel Denuit, Esther Frostig

Department of Statistics

Research output: Contribution to journal › Article › peer-review

Abstract

This article considers portfolio credit risk models of factor type. The dependence between the individual defaults is driven by a small number of systematic factors. The present work aims to investigate the effect of increasing the strength of the dependence between systematic factors on the default indicators in standard credit risk models. The intensity of the dependence is measured by means of appropriate multivariate stochastic orderings, based on the comparison of supermodular and ultramodular functions.

Original language	English
Pages (from-to)	151-160
Number of pages	10
Journal	Probability in the Engineering and Informational Sciences
Volume	22
Issue number	1
DOIs	https://doi.org/10.1017/S0269964808000090
State	Published - Jan 2008

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Management Science and Operations Research
Industrial and Manufacturing Engineering

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abstract = "This article considers portfolio credit risk models of factor type. The dependence between the individual defaults is driven by a small number of systematic factors. The present work aims to investigate the effect of increasing the strength of the dependence between systematic factors on the default indicators in standard credit risk models. The intensity of the dependence is measured by means of appropriate multivariate stochastic orderings, based on the comparison of supermodular and ultramodular functions.",

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Comparison of dependence in factor models with application to credit risk portfolios

Abstract

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