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Is Firm Interdependence within Industries Important for Portfolio Credit Risk?

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Author Info
Carling, Kenneth () (IFAU, Uppsala and Dalarna University)
Rönnegård, Lars () (Dalarna University)
Roszbach, Kasper () (Research Department, Central Bank of Sweden)

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Abstract

A drawback of available portfolio credit risk models is that they fail to allow for default risk dependency across loans other than through common risk factors. Thereby, thesemodels ignore that close ties can exist between companies due to legal, financial and business relations. In this paper, we integrate the insights from theoretical models of default correlation into a commonly used model of default and portfolio credit risk by allowing for dependency between firm default risk through both common factors and industry specific errors in a duration model. An application using pooled data from two Swedish banks’ business loan portfolios over the period 1996-2000 shows that estimates of individual default risk are little affected by including industry specific errors. However, accounting for these industry effects increases VaR estimates by 50-200 percent. A traditional model with only systematic factors, although able to fit the broad trends in credit losses, cannot match these fluctuations because it fails to capture credit losses in bad times, when banks are typically hit by large unexpected credit losses. The model we propose manages to follow both the trend in credit losses and produce industry driven, time-varying, fluctuations in losses around that trend. Consequently, this model will better aid banks and regulators in determining the appropriate size of economic capital requirements. Capital buffers derived from our model will be larger for periods with large ”aggregate” disturbances and smaller in better times, and avoid both overcapitalization in good times and undercapitalization in bad times.

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Publisher Info
Paper provided by Sveriges Riksbank (Central Bank of Sweden) in its series Working Paper Series with number 168.

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Length: 36 pages
Date of creation: 01 Aug 2004
Date of revision:
Handle: RePEc:hhs:rbnkwp:0168

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Related research
Keywords: value-at-risk; credit risk; portfolio credit risk; duration model; default correlation; industry dependency; cluster errors;

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Find related papers by JEL classification:
C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models
C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models
D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January. [Downloadable!] (restricted)
  2. Platt, Harlan D. & Platt, Marjorie B., 1991. "A note on the use of industry-relative ratios in bankruptcy prediction," Journal of Banking & Finance, Elsevier, vol. 15(6), pages 1183-1194, December. [Downloadable!] (restricted)
  3. Narendranathan, W. & Stewart, M.B., 1989. "Modelling The Probability Of Leaving Unemployment: Competing Risks Models With Flexible Baseline Hazards," The Warwick Economics Research Paper Series (TWERPS) 331, University of Warwick, Department of Economics.
  4. Michael B. Gordy, 1998. "A comparative anatomy of credit risk models," Finance and Economics Discussion Series 1998-47, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  5. Carling, Kenneth & Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2007. "Corporate credit risk modeling and the macroeconomy," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 845-868, March. [Downloadable!] (restricted)
  6. Manove, Michael & Padilla, Atilano Jorge & Pagano, Marco, 2000. "Collateral Vs. Project Screening: A Model Of Lazy Banks," CEPR Discussion Papers 2439, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  7. Roszbach, Kasper, 2003. "Bank Lending Policy, Credit Scoring and the Survival of Loans," Working Paper Series 154, Sveriges Riksbank (Central Bank of Sweden). [Downloadable!]
    Other versions:
  8. Mark Carey, 1998. "Credit Risk in Private Debt Portfolios," Journal of Finance, American Finance Association, vol. 53(4), pages 1363-1387, 08. [Downloadable!] (restricted)
  9. Anil Bangia & Francis X. Diebold & Til Schuermann, 2000. "Ratings Migration and the Business Cycle, With Application to Credit Portfolio Stress Testing," Center for Financial Institutions Working Papers 00-26, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
    Other versions:
  10. Altman, Edward I, 1971. "Railroad Bankruptcy Propensity," Journal of Finance, American Finance Association, vol. 26(2), pages 333-45, May. [Downloadable!] (restricted)
  11. Acharya, Viral V & Bharath, Sreedhar T & Srinivasan, Anand, 2003. "Understanding the Recovery Rates on Defaulted Securities," CEPR Discussion Papers 4098, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  12. Giesecke, Kay, 2004. "Correlated default with incomplete information," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1521-1545, July. [Downloadable!] (restricted)
  13. James J. Heckman & Robert J. Willis, 1974. "Estimation of a Stochastic Model of Reproduction: An Econometric Approach," NBER Working Papers 0034, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  14. Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2006. "Internal ratings systems, implied credit risk and the consistency of banks' risk classification policies," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 1899-1926, July. [Downloadable!] (restricted)
    Other versions:
  15. Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management. [Downloadable!]
    Other versions:
  16. Iftekhar Hasan & Anthony Saunders & Viral V. Acharya, 2002. "Should banks be diversified? Evidence from individual bank loan portfolios," BIS Working Papers 118, Bank for International Settlements. [Downloadable!]
    Other versions:
  17. Michael B. Gordy, 2002. "A risk-factor model foundation for ratings-based bank capital rules," Finance and Economics Discussion Series 2002-55, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  18. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-64, May. [Downloadable!] (restricted)
  19. Linda Allen & Anthony Saunders, 2004. "Incorporating Systemic Influences Into Risk Measurements: A Survey of the Literature," Journal of Financial Services Research, Springer, vol. 26(2), pages 161-191, October. [Downloadable!] (restricted)
  20. Guilkey, David K. & Murphy, James L., 1993. "Estimation and testing in the random effects probit model," Journal of Econometrics, Elsevier, vol. 59(3), pages 301-317, October. [Downloadable!] (restricted)
  21. Pamela Nickell & William Perraudin & Simone Varotto, . "Stability of ratings transitions," Bank of England working papers 133, Bank of England. [Downloadable!]
    Other versions:
  22. Edward I. Altman, 1973. "Predicting Railroad Bankruptcies in America," Bell Journal of Economics, The RAND Corporation, vol. 4(1), pages 184-211, Spring. [Downloadable!] (restricted)
  23. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January. [Downloadable!] (restricted)
  24. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Diana Barro & Antonella Basso, 2006. "A credit contagion model for loan portfolios in a network of firms with spatial interaction," Working Papers 143, Department of Applied Mathematics, University of Venice. [Downloadable!]
  2. Tor Jacobson & Jesper Lindé & Kasper Roszbach, 2005. "Credit Risk Versus Capital Requirements under Basel II: Are SME Loans and Retail Credit Really Different?," Journal of Financial Services Research, Springer, vol. 28(1), pages 43-75, October. [Downloadable!] (restricted)
    Other versions:
  3. Carling, Kenneth & Alam, Moudud, 2007. "Computationally feasible estimation of the covariance structure in Generalized linear mixed models(GLMM)," Working Papers 2007:14, Örebro University, Swedish Business School. [Downloadable!]
  4. Diana Barro & Antonella Basso, 2008. "Credit contagion in a network of firms with spatial interaction," Working Papers 186, Department of Applied Mathematics, University of Venice. [Downloadable!]
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