Copula-based factor model for credit risk analysis

Meng-Jou Lu (), Cathy Yi-Hsuan Chen () and Wolfgang Härdle
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Meng-Jou Lu: National Chiao Tung University
Cathy Yi-Hsuan Chen: Humboldt–Universität zu Berlin

Review of Quantitative Finance and Accounting, 2017, vol. 49, issue 4, No 3, 949-971

Abstract: Abstract A standard quantitative method to assess credit risk employs a factor model based on joint multivariate normal distribution properties. By extending the one-factor Gaussian copula model to produce a more accurate default forecast, this paper proposes the incorporation of a state-dependent recovery rate into the conditional factor loading and to model them sharing a unique common factor. The common factor governs the default rate and recovery rate simultaneously, implicitly creating their association. In accordance with Basel III, this paper shows that the tendency toward default during a hectic period is governed more by systematic risk than by idiosyncratic risk. Among those considered, the model with random factor loading and a state-dependent recovery rate is shown to be superior in terms of default prediction.

Keywords: Factor model; Conditional factor loading; State-dependent recovery rate (search for similar items in EconPapers)
JEL-codes: C38 C53 F34 G11 G17 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Working Paper: Copula-based factor model for credit risk analysis (2015)
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DOI: 10.1007/s11156-016-0613-x

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