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Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis

Listed author(s):
  • Annalisa Di Clemente

In this paper a simple and innovative model for measuring more accurately the credit tail risk of a banking book is presented. This is a Monte Carlo simulation model in which the credit loss severity (LGD) is a stochastic variable and it is correlated to the default event. Specifically, LGD is assumed to be distributed as a conditional beta function and its two parameters a and b are estimated assuming a mean value of LGD linked to the value of the PD conditional to the value of the macro-economic risk factor generated in every Monte Carlo simulative scenario. The linkage between the average LGD and the conditional PD is obtained by a simple linear regression analysis calibrated by using the time series of easily available financial historical data (Moody’s, 2011; Standard & Poor’s, 2012).

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Article provided by FrancoAngeli Editore in its journal STUDI ECONOMICI.

Volume (Year): 2013/109 (2013)
Issue (Month): 109 ()
Pages: 5-24

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Handle: RePEc:fan:steste:v:html10.3280/ste2013-109001
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  1. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
  2. Dirk Tasche, 2004. "The single risk factor approach to capital charges in case of correlated loss given default rates," Papers cond-mat/0402390, arXiv.org, revised Feb 2004.
  3. Simone Farinelli & Mykhaylo Shkolnikov, 2012. "Two Models of Stochastic Loss Given Default," Papers 1205.5369, arXiv.org, revised May 2012.
  4. Jones, E Philip & Mason, Scott P & Rosenfeld, Eric, 1984. " Contingent Claims Analysis of Corporate Capital Structures: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 39(3), pages 611-625, July.
  5. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-367, May.
  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 449-470, May.
  7. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
  8. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
  9. Crouhy, Michel & Galai, Dan & Mark, Robert, 2000. "A comparative analysis of current credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 59-117, January.
  10. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
  11. 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.
  12. Geske, Robert, 1977. "The Valuation of Corporate Liabilities as Compound Options," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(04), pages 541-552, November.
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