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Comparing Australian and US Corporate Default Risk using Quantile Regression

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Author Info

  • David E Allen

    ()
    (School of Accounting Finance & Economics, Edith Cowan University)

  • Akhmad R. Kramadibrata

    ()
    (School of Accounting Finance & Economics, Edith Cowan University)

  • R. J. Powell

    ()
    (School of Accounting Finance & Economics, Edith Cowan University)

  • Abhay Kumar Singh

    ()
    (School of Accounting Finance & Economics, Edith Cowan University)

Abstract

The severe bank stresses of the Global Financial Crisis (GFC) have underlined the importance of understanding and measuring extreme credit risk. The Australian economy is widely considered to have fared much better than the US and most other major world economies. This paper applies quantile regression and Monte Carlo simulation to the Merton structural credit model to investigate the impact of extreme asset value fluctuations on default probabilities of Australian companies in comparison to the USA. Quantile regression allows modelling of the extreme quantiles of a distribution which allows measurement of capital and PDs at the most extreme points of an economic downturn, when companies are most likely to fail. Daily asset value fluctuations of over 600 Australian and US investment and speculative entities are examined over a ten year period spanning pre-GFC and GFC. The events of the GFC also showed how the capital of global banks was eroded as defaults increased. This paper therefore also examines the impact of these fluctuating default probabilities on the capital adequacy of Australian and US banks. The paper finds highly significant variances in default probabilities and capital between quantiles in both Australia and the US, and shows how these variances can assist banks and regulators in calculating capital buffers to sustain banks through volatile times.Classification-JEL:

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File URL: http://www.ecu.edu.au/__data/assets/pdf_file/0018/303606/Wp1104ak.pdf
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Bibliographic Info

Paper provided by Edith Cowan University, School of Business in its series Working papers with number 2011-04.

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Length: 11 pages
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:ecu:wpaper:2011-04

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Keywords: Probability of default; Quantile regression; Australian banks; United States banks.;

This paper has been announced in the following NEP Reports:

References

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  1. Patricia Jackson & David Maude & William Perraudin, 1998. "Bank Capital and Value at Risk," Bank of England working papers 79, Bank of England.
  2. Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
  3. Yannis Bilias & Roger Koenker, 2001. "Quantile regression for duration data: A reappraisal of the Pennsylvania Reemployment Bonus Experiments," Empirical Economics, Springer, vol. 26(1), pages 199-220.
  4. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
  5. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
  6. 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 449-70, May.
  7. Gupta, Anurag & Liang, Bing, 2005. "Do hedge funds have enough capital? A value-at-risk approach," Journal of Financial Economics, Elsevier, vol. 77(1), pages 219-253, July.
  8. Omar Arias & Kevin F. Hallock & Walter Sosa Escudero, 1999. "Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression using Twins Data," Department of Economics, Working Papers 016, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata.
  9. Maria Vassalou & Yuhang Xing, 2004. "Default Risk in Equity Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 831-868, 04.
  10. repec:ecu:wpaper:2009-05 is not listed on IDEAS
  11. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
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Cited by:
  1. David E Allen & R.R Boffey & R. J. Powell, 2011. "A Quantile Monte Carlo approach to measuring extreme credit risk," Working papers 2011-02, Edith Cowan University, School of Business.
  2. David E Allen & Akhmad R. Kramadibrata & R. J. Powell & Abhay Kumar Singh, 2011. "Tail Risk for Australian Emerging Market Entities," Working papers 2011-07, Edith Cowan University, School of Business.

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