Advanced Search
MyIDEAS: Login to save this paper or follow this series

Linking Global Economic Dynamics to a South African-Specific Credit Risk Correlation Model

Contents:

Author Info

  • Albert H. De Wet

    (First Rand Bank)

  • Renee´ Van Eyden

    ()
    (Department of Economics, University of Pretoria)

  • Rangan Gupta

    ()
    (Department of Economics, University of Pretoria)

Abstract

In order to address practical questions in credit portfolio management it is necessary to link the cyclical or systematic components of firm credit risk with the firm’s own idiosyncratic credit risk as well as the systematic credit risk component of every other exposure in the portfolio. This paper builds on the methodology proposed by Pesaran, Schuermann, and Weiner (2004) and supplemented by Pesaran, Schuermann, Treutler and Weiner (2006) which has made a significant advance in credit risk modelling in that it avoids the use of proprietary balance sheet and distance-to-default data, focusing on credit ratings which are more freely available. In this paper a country-specific macroeconometric risk driver engine which is compatible with and could feed into the GVAR model and framework of PSW (2004) is constructed, using vector error-correcting (VECM) techniques. This allows conditional loss estimation of a South African-specific credit portfolio but also opens the door for credit portfolio modelling on a global scale, as such a model can easily be linked to the GVAR model. The set of domestic factors are extended beyond those used in PSW (2004) in such a way that the risk driver model is applicable for both retail and corporate credit risk. As such, the model can be applied to a total bank balance sheet, incorporating the correlation and diversification between both retail and corporate credit exposures. Assuming statistical over-identification restrictions, the results indicate that it is possible to construct a South African component for the GVAR model that can easily be integrated into the global component. From a practical application perspective the framework and model is particularly appealing since it can be used as a theoretically consistent correlation model within a South African-specific credit portfolio management tool.

Download Info

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Bibliographic Info

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200719.

as in new window
Length: 31 pages
Date of creation: Sep 2007
Date of revision:
Handle: RePEc:pre:wpaper:200719

Contact details of provider:
Postal: PRETORIA, 0002
Phone: (+2712) 420 2413
Fax: (+2712) 362-5207
Web page: http://web.up.ac.za/default.asp?ipkCategoryID=677
More information through EDIRC

Related research

Keywords: Credit portfolio management; multifactor model; vector error correction model (VECM); credit correlations;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

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.:
as in new window
  1. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
  2. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780198774501, October.
  3. Dees, S. & di Mauro, F. & Pesaran, M.H. & Smith, L.V., 2005. "Exploring the International Linkages of the Euro Area: a Global VAR Analysis," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 0518, Faculty of Economics, University of Cambridge.
  4. M. Hashem Pesaran & Til Schuermann & Scott M. Weiner, 2001. "Modelling regional interdependencies using a global error-correcting macroeconometric model," 10th International Conference on Panel Data, Berlin, July 5-6, 2002, International Conferences on Panel Data B4-1, International Conferences on Panel Data.
  5. Michael B. Gordy, 2002. "A risk-factor model foundation for ratings-based bank capital rules," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2002-55, Board of Governors of the Federal Reserve System (U.S.).
  6. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, American Economic Association, vol. 41(3), pages 788-829, September.
  7. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 12(2-3), pages 231-254.
  8. Pesaran, M. H. & Smith, Ron P., 1998. "Structural Analysis of Cointegrating VARs," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 9811, Faculty of Economics, University of Cambridge.
  9. Johansen, Soren, 1992. "Cointegration in partial systems and the efficiency of single-equation analysis," Journal of Econometrics, Elsevier, Elsevier, vol. 52(3), pages 389-402, June.
  10. Mark Carey, 2002. "A guide to choosing absolute bank capital requirements," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.) 726, Board of Governors of the Federal Reserve System (U.S.).
  11. Pesaran, M. H. & Shin, Y. & Smith, R. J., 1997. "Structural Analysis of Vector Error Correction Models with Exogenous I(1) Variables," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 9706, Faculty of Economics, University of Cambridge.
  12. M. Hashem Pesaran & Ron P. Smith, 1998. "Structural Analysis of Cointegrating VARs," Journal of Economic Surveys, Wiley Blackwell, Wiley Blackwell, vol. 12(5), pages 471-505, December.
  13. Carey, Mark, 2002. "A guide to choosing absolute bank capital requirements," Journal of Banking & Finance, Elsevier, Elsevier, vol. 26(5), pages 929-951, May.
  14. Seth B. Carpenter & William Whitesell & Egon Zakrajsek, 2001. "Capital requirements, business loans, and business cycles: an empirical analysis of the standardized approach in the new Basel Capital Accord," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2001-48, Board of Governors of the Federal Reserve System (U.S.).
  15. Linda Allen & Anthony Saunders, 2004. "Incorporating Systemic Influences Into Risk Measurements: A Survey of the Literature," Journal of Financial Services Research, Springer, Springer, vol. 26(2), pages 161-191, October.
  16. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, Elsevier, vol. 58(1), pages 17-29, January.
  17. Stephen G. Hall & Jennifer V. Greenslade & S. G. Brian Henry, 1999. "On the Identification of Cointegrated Systems in Small Samples: Practical Procedures with an Application to UK Wages and Prices," Computing in Economics and Finance 1999, Society for Computational Economics 643, Society for Computational Economics.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Melisso Boschi, 2007. "Foreign capital in Latin America: A long-run structural Global VAR perspective," Economics Discussion Papers, University of Essex, Department of Economics 647, University of Essex, Department of Economics.
  2. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.
  3. Alexander Chudik & Hashem Pesaran, 2014. "Theory and Practice of GVAR Modeling," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 1408, Faculty of Economics, University of Cambridge.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:200719. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rangan Gupta).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.