Review of Quantitative Finance and Accounting

, Volume 49, Issue 4, pp 949–971 | Cite as

Copula-based factor model for credit risk analysis

  • Meng-Jou LuEmail author
  • Cathy Yi-Hsuan Chen
  • Wolfgang Karl Härdle
Original Research


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.


Factor model Conditional factor loading State-dependent recovery rate 

JEL classification

C38 C53 F34 G11 G17 


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Information Management and FinanceNational Chiao Tung UniversityHsinchu CityTaiwan
  2. 2.Ladislaus von Bortkiewicz Chair of Statistics, C.A.S.E. – Center for Applied Statistics and EconomicsHumboldt–Universität zu BerlinBerlinGermany
  3. 3.Department of FinanceChung Hua UniversityHsinchuTaiwan
  4. 4.School of Business, Singapore Management UniversitySingaporeSingapore

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