Model-Based Measurement of Sector Concentration Risk in Credit Portfolios

  • Martin Hibbeln
Part of the Contributions to Economics book series (CE)


The focus of this chapter is on sector concentrations. This type of concentration risk can occur if there is more than one systematic risk factor that influences credit defaults. The main research questions that are analyzed in this chapter are:
  • How can existing approaches for measuring sector concentration risk be modified and adjusted to be consistent with the Basel framework? Is the risk measure Value at Risk problematic when dealing with sector concentration risk?

  • Which methods are capable of measuring concentration risk and how good do they perform in comparison? What are the advantages and disadvantages of these methods?

In order to deal with these questions, it is initially determined how a multi-factor model can be parameterized to obtain a capital requirement which is consistent with Basel II. Furthermore, the models of Pykhtin (Risk 17(3):85–90, 2004), Cespedes et al. (J Credit Risk, 2(3):57–85, 2006), and Düllmann (Measuring business sector concentration by an infection model. Discussion Paper, Series 2: Banking and Financial Studies, Deutsche Bundesbank, (3), 2006), which have been developed to approximate the risk in the presence of sector concentrations, are presented and modified. Then, the accuracy of these models concerning their ability to measure sector concentration risk is compared.


Capital Requirement Credit Portfolio Sector Concentration Portfolio Loss Default Correlation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Acharya VV, Hasan I, Saunders A (2006) Should banks be diversified? Evidence from individual bank loan portfolios. J Bus 79(3):1355–1412CrossRefGoogle Scholar
  2. Basel Committee on Banking Supervision (2005a) International convergence of capital measurement and capital standards – a revised framework, Updated November 2005, Bank for International Settlements, BaselGoogle Scholar
  3. Basel Committee on Banking Supervision (2006) Studies on credit risk concentration: an overview of the issues and a synopsis of the results from the research task force project. BCBS Working Paper No. 15, Bank for International Settlements, BaselGoogle Scholar
  4. Cespedes J, de Juan Herrero J, Kreinin A, Rosen D (2006) A simple multi-factor “factor adjustment” for the treatment of diversification in credit capital rules. J Credit Risk 2(3):57–85Google Scholar
  5. Cifuentes A, O’Connor G (1996) The binomial expansion method applied to CBO/CLO analysis, Special report. Moody’s Investor Service, New YorkGoogle Scholar
  6. Cifuentes A, Wilcox C (1998) The double binomial method and its application to a special case of CDO structures, Special report. Moody’s Investor Service, New YorkGoogle Scholar
  7. Cifuentes A, Murphy E, O’Connor G (1996) Emerging market collateralized bond obligations: an overview, Special report. Moody’s Investor Service, New YorkGoogle Scholar
  8. Davis M, Lo V (2001) Infectious defaults. Quant Fin 1(4):382–387CrossRefGoogle Scholar
  9. Düllmann K (2006). Measuring business sector concentration by an infection model. Discussion Paper, Series 2: Banking and financial studies. Deutsche Bundesbank (3)Google Scholar
  10. Düllmann K (2007) Measuring concentration risk in credit portfolios. In: Christodoulakis G, Satchell S (eds) The analytics of risk model validation. Academic Press, Amsterdam, pp 59–78Google Scholar
  11. Düllmann K, Masschelein N (2007) A tractable model to measure sector concentration risk in credit portfolios. J Fin Serv Res 32(1):55–79CrossRefGoogle Scholar
  12. Düllmann K, Küll J, Kunisch M (2008) Estimating asset correlations from stock prices or default rates – Which method is superior? Discussion Paper, Series 2: Banking and financial studies, Deutsche Bundesbank (4)Google Scholar
  13. Gordy MB (2003) A risk-factor model foundation for rating-based capital rules. J Fin Intermediation 12(3):199–232CrossRefGoogle Scholar
  14. Grundke P (2008) Regulatory treatment of the double default effect under the New Basel accord: how conservative is it? Rev Manag Sci 2(1):37–59CrossRefGoogle Scholar
  15. Gürtler M, Hibbeln M, Vöhringer C (2010) Measuring concentration risk for regulatory purposes. J Risk 12(3):69–104Google Scholar
  16. Heitfield E, Burton S, Chomsisengphet S (2006) Systematic and idiosyncratic risk in syndicated loan portfolios. J Credit Risk 2(3):3–31Google Scholar
  17. Lopez J (2004) The empirical relationship between average asset correlation, firm probability of default, and asset size. J Fin Intermediation 13(2):265–283CrossRefGoogle Scholar
  18. Martin R, Wilde T (2002) Unsystematic credit risk. Risk 15(11):123–128Google Scholar
  19. Morinaga S, Shiina Y (2005) Underestimation of sector concentration risk by mis-assignment of borrowers. Working Paper, TokyoGoogle Scholar
  20. Pykhtin M (2004) Multi-factor adjustment. Risk 17(3):85–90Google Scholar
  21. Tasche D (2006a) Anwendungen der Stochastik in der Bankenaufsicht. Lecture Notes, Frankfurt University. Accessed 18 Aug 2009
  22. Weiss NA (2005) A course in probability. Addison-Wesley, BostonGoogle Scholar
  23. Wilde T (2001) Probing granularity. Risk 14(8):103–106Google Scholar

Copyright information

© Physica-Verlag HD 2010

Authors and Affiliations

  1. 1.Institute of Finance Carl-Friedrich-Gauß-FacultyTechnische Universität BraunschweigBraunschweigGermany

Personalised recommendations