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A Quantile Analysis of Default Risk for Speculative and Emerging Companies

  • 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)

Using quantile regression, this article examines default risk of emerging and speculative companies in Australia and the United States as compared to established investment entities. We use two datasets for each of the two countries, one speculative and one established. In the US we compare companies from the S&P 500 to those on the Speculative Grade Liquidity Ratings list (Moody's Investor Services, 2010). For Australia, we compare entities from the S&P/ASX 200 to those on the S&P/ASX Emerging Companies Index (EMCOX). We also divide the datasets into GFC and Pre-GFC periods to examine default risk over different economic circumstances. Quantile Regression splits the data into parts or quantiles, thus allowing default risk to be examined at different risk levels. This is especially useful in measuring extreme risk quantiles, when corporate failures are most likely. We apply Monte Carlo simulation to asset returns to calculate Distance to Default using a Merton structural credit model approach. In both countries, the analysis finds substantially higher default risk for speculative as compared to established companies. The spread between speculative company and established company default risk is found to remain constant in Australia through different economic circumstances, but to increase in the US during the GFC as compared to pre-GFC. These findings are important to lenders in understanding, and providing for, default risk for companies of different grades through varying economic cycles.Classification-JEL:

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Paper provided by Edith Cowan University, School of Business in its series Working papers with number 2011-05.

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Length: 7 pages
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:ecu:wpaper:2011-05
Contact details of provider: Postal: 270 Joondalup Drive, Joondalup, Western Australia, 6027
Web page: http://www.ecu.edu.au/schools/business/overview

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  1. Pederzoli, Chiara & Torricelli, Costanza, 2005. "Capital requirements and business cycle regimes: Forward-looking modelling of default probabilities," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3121-3140, December.
  2. 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.
  3. Maria Vassalou & Yuhang Xing, 2004. "Default Risk in Equity Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 831-868, 04.
  4. Daniel R÷Sch & Harald Scheule, 2010. "Downturn Credit Portfolio Risk, Regulatory Capital and Prudential Incentives-super-," International Review of Finance, International Review of Finance Ltd., vol. 10(Financial), pages 185-207.
  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. Inês Drumond, 2008. "Bank Capital Requirements, Business Cycle Fluctuations and the Basel Accords: A Synthesis," FEP Working Papers 277, Universidade do Porto, Faculdade de Economia do Porto.
  7. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
  8. Gordy, Michael B. & Howells, Bradley, 2006. "Procyclicality in Basel II: Can we treat the disease without killing the patient?," Journal of Financial Intermediation, Elsevier, vol. 15(3), pages 395-417, July.
  9. 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.
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