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Is Firm Interdependence within Industries Important for Portfolio Credit Risk?

Author

Listed:
  • Carling, Kenneth

    () (IFAU, Uppsala and Dalarna University)

  • Rönnegård, Lars

    () (Dalarna University)

  • Roszbach, Kasper

    () (Research Department, Central Bank of Sweden)

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.

Suggested Citation

  • Carling, Kenneth & Rönnegård, Lars & Roszbach, Kasper, 2004. "Is Firm Interdependence within Industries Important for Portfolio Credit Risk?," Working Paper Series 168, Sveriges Riksbank (Central Bank of Sweden).
  • Handle: RePEc:hhs:rbnkwp:0168
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    References listed on IDEAS

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    1. 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.
    2. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    3. 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.
    4. Lucas, Andre & Klaassen, Pieter & Spreij, Peter & Straetmans, Stefan, 2001. "An analytic approach to credit risk of large corporate bond and loan portfolios," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1635-1664, September.
    5. Altman, Edward I, 1971. "Railroad Bankruptcy Propensity," Journal of Finance, American Finance Association, vol. 26(2), pages 333-345, May.
    6. James J. Heckman & Robert J. Willis, 1976. "Estimation of a Stochastic Model of Reproduction: An Econometric Approach," NBER Chapters,in: Household Production and Consumption, pages 99-146 National Bureau of Economic Research, Inc.
    7. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    8. Linda Allen & Anthony Saunders, 2004. "Incorporating Systemic Influences Into Risk Measurements: A Survey of the Literature," Journal of Financial Services Research, Springer;Western Finance Association, vol. 26(2), pages 161-191, October.
    9. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    10. 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.
    11. 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.
    12. 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.
    13. Edward I. Altman, 1973. "Predicting Railroad Bankruptcies in America," Bell Journal of Economics, The RAND Corporation, vol. 4(1), pages 184-211, Spring.
    14. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
    15. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
    16. Kasper Roszbach, 2004. "Bank Lending Policy, Credit Scoring, and the Survival of Loans," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 946-958, November.
    17. Mark Carey, 1998. "Credit Risk in Private Debt Portfolios," Journal of Finance, American Finance Association, vol. 53(4), pages 1363-1387, August.
    18. Giesecke, Kay, 2004. "Correlated default with incomplete information," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1521-1545, July.
    19. Viral V. Acharya & Iftekhar Hasan & Anthony Saunders, 2006. "Should Banks Be Diversified? Evidence from Individual Bank Loan Portfolios," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1355-1412, May.
    20. Manove, M. & Padilla, A.J. & Pagano, M., 1998. "Collateral vs. Project Screening: a Model of Lazy Banks," Papers 9807, Centro de Estudios Monetarios Y Financieros-.
    21. 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.
    22. 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.
    23. 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 761-764, May.
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    Citations

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    Cited by:

    1. Tor Jacobson & Jesper Lindé & Kasper Roszbach, 2013. "Firm Default And Aggregate Fluctuations," Journal of the European Economic Association, European Economic Association, vol. 11(4), pages 945-972, August.
    2. 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, Università Ca' Foscari Venezia.
    3. 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;Western Finance Association, vol. 28(1), pages 43-75, October.
    4. Barro, Diana & Basso, Antonella, 2010. "Credit contagion in a network of firms with spatial interaction," European Journal of Operational Research, Elsevier, vol. 205(2), pages 459-468, September.
    5. Carling, Kenneth & Alam, Moudud, 2007. "Computationally feasible estimation of the covariance structure in Generalized linear mixed models(GLMM)," Working Papers 2007:14, Örebro University, School of Business.
    6. Egloff, Daniel & Leippold, Markus & Vanini, Paolo, 2007. "A simple model of credit contagion," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2475-2492, August.

    More about this item

    Keywords

    value-at-risk; credit risk; portfolio credit risk; duration model; default correlation; industry dependency; cluster errors;

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • 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; Micro Finance Institutions; Mortgages

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