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Credit cycles and macro fundamentals

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Author Info

  • Koopman, Siem Jan
  • Kräussl, Roman
  • Lucas, André
  • Monteiro, André B.

Abstract

We use an intensity-based framework to study the relation between macroeconomic fundamentals and cycles in defaults and rating activity. Using Standard and Poor's U.S. corporate rating transition and default data over the period 1980-2005, we directly estimate the default and rating cycle from micro data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, the macro variables appear to explain part of the default cycle. However, we strongly reject the correct dynamic specification of these models. The problem is solved by adding an unobserved dynamic component to the model, which can be interpreted as an omitted systematic credit risk factor. By accounting for this latent factor, many of the observed macro variables loose their significance. There are a few exceptions, but the economic impact of the observed macro variables for credit risk remains low. We also show that systematic credit risk factors differ over transition types, with risk factors for downgrades being noticeably different from those for upgrades. We conclude that portfolio credit risk models based only on observable systematic risk factors omit one of the strongest determinants of credit risk at the portfolio level. This has obvious consequences for current modeling and risk management practices.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Empirical Finance.

Volume (Year): 16 (2009)
Issue (Month): 1 (January)
Pages: 42-54
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Handle: RePEc:eee:empfin:v:16:y:2009:i:1:p:42-54

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For corrections or technical questions regarding this item, or to correct its listing, contact: (Jeroen Loos).

Related research

Keywords: Defaults Ratings Business cycles Bank lending conditions Unobserved component models Intensity models Monte Carlo likelihood;

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References

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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. Lucas, Andre & Klaassen, Pieter, 2006. "Discrete versus continuous state switching models for portfolio credit risk," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 23-35, January.
  2. Siem Jan Koopman & André Lucas, 2003. "Business and Default Cycles for Credit Risk," Tinbergen Institute Discussion Papers 03-062/2, Tinbergen Institute, revised 09 Jan 2003.
  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. 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.
  6. Roman Kraeussl, 2003. "Sovereign Credit Ratings and Their Impact on Recent Financial Crises," Working Papers 0313, University of Crete, Department of Economics.
  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. Carling, Kenneth & Jacobson, Tor & Lindé, Jesper & Roszbach, Kasper, 2002. "Capital Charges under Basel II: Corporate Credit Risk Modelling and the Macro Economy," Working Paper Series 142, Sveriges Riksbank (Central Bank of Sweden).
  9. Darrell Duffie & Leandro Siata & Ke Wang, 2006. "Multi-Period Corporate Default Prediction With Stochastic Covariates," NBER Working Papers 11962, National Bureau of Economic Research, Inc.
  10. 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.
  11. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
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Citations

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Cited by:
  1. Konrad Banachewicz & Aad van der Vaart & André Lucas, 2006. "Modeling Portfolio Defaults using Hidden Markov Models with Covariates," Tinbergen Institute Discussion Papers 06-094/2, Tinbergen Institute.
  2. Narasimhan Jegadeesh & Roman Kräussl & Joshua Pollet, 2009. "Risk and Expected Returns of Private Equity Investments: Evidence Based on Market Prices," NBER Working Papers 15335, National Bureau of Economic Research, Inc.
  3. Kauko, Karlo, 2010. "The feasibility of through-the-cycle ratings," Research Discussion Papers 14/2010, Bank of Finland.
  4. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87, December.
  5. Konrad Banachewicz & André Lucas, 2007. "Quantile Forecasting for Credit Risk Management using possibly Mis-specified Hidden Markov Models," Tinbergen Institute Discussion Papers 07-046/2, Tinbergen Institute.
  6. Bezemer, Dirk J & Werner, RA, 2009. "Disaggregated Credit Flows and Growth in Central Europe," MPRA Paper 15896, University Library of Munich, Germany.
  7. Georges Dionne & Pascal François & Olfa Maalaoui, 2009. "Detecting Regime Shifts in Corporate Credit Spreads," Cahiers de recherche 0929, CIRPEE.
  8. Bezemer, Dirk J & Werner, Richard A, 2009. "Disaggregated Credit Flows and Growth in Central Europe," MPRA Paper 17456, University Library of Munich, Germany.

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