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

Titolo Rivista STUDI ECONOMICI
Autori/Curatori Annalisa Di Clemente
Anno di pubblicazione 2014 Fascicolo 2013/109
Lingua Inglese Numero pagine 20 P. 5-24 Dimensione file 103 KB
DOI 10.3280/STE2013-109001
Il DOI è il codice a barre della proprietà intellettuale: per saperne di più clicca qui

Qui sotto puoi vedere in anteprima la prima pagina di questo articolo.

Se questo articolo ti interessa, lo puoi acquistare (e scaricare in formato pdf) seguendo le facili indicazioni per acquistare il download credit. Acquista Download Credits per scaricare questo Articolo in formato PDF

Anteprima articolo

FrancoAngeli è membro della Publishers International Linking Association, Inc (PILA)associazione indipendente e non profit per facilitare (attraverso i servizi tecnologici implementati da CrossRef.org) l’accesso degli studiosi ai contenuti digitali nelle pubblicazioni professionali e scientifiche

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).

Keywords:Loss Given Default, Probability of Default, Expected Shortfall, Value-at-Risk, Monte Carlo Simulation, Conditional Beta Function.

Jel codes:G15, G21, G28

  1. Acharya V.V., Bharath S.T. and Srinivasan A. (2003), Understanding the Recovery Rates on Defaulted Securities, Center for Economic Policy Research, London Business School, London.
  2. Acharya V.V., Bharath S.T. and Srinivasan A. (2007), Does Industry-Wide Distress Affect Defaulted Firms? Evidence from Creditor Recoveries, Journal of Financial Economics, vol. 85: 787-821.
  3. Altman E.I. and Ramayanam S. (2007), Defaults and Returns on High Yields Bonds: Analysis Through 2006, Special Report, NYU Salomon Center, February.
  4. Altman E.I., Brady B., Resti A. and Sironi A. (2001), Analyzing and Explaining Default Recovery Rates, ISDA, Research Report, London, December. Altman E.I., Brady B., Resti A. and Sironi A. (2004), Default Recovery Rates in Credit Risk Modelling: A Review of the Literature and Empirical Evidence, Economic Notes, vol. 33, 2: 183-208.
  5. Altman E.I., Brady B., Resti A. and Sironi A. (2005a), The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications. The Journal of Business, vol. 78, 6: 2203-2228.
  6. Altman E.I., Resti A. and Sironi A. (2005b), The PD/LGD Link: Implications for Credit Risk Modelling, in E. Altman, A. Resti, A. Sironi (eds.), Recovery Risk: the Next Challenge in Credit Risk Management, Risk Books, June.
  7. Bakshi G., Madan D. and Zhang F. (2001), Understanding the Role of Recovery in Default Risk Models: Empirical Comparisons and Implied Recovery Rates, Finance and Economics Discussion Series, 2001-37, Federal Reserve Board of Governors, Washington.
  8. Basel Committee on Banking Supervision (2004), Modifications to the Capital Treatment for Expected and Unexpected Credit Losses in New Basel Capital Accord, Bank of International Settlements, Basel, 30 January.
  9. Black F. and Cox J.C. (1976), Valuing Corporate Securities: Some Effects of Bond Indenture Provisions, Journal of Finance, vol. 31: 351-367.
  10. Carey M. and Gordy M. (2003), Systematic Risk in Recoveries on Defaulted Debt, mimeo, Federal Reserve Board, Washington.
  11. Chabaane A., Laurent J.-P. and Salomon J. (2004): Double Impact: Credit Risk Assessment and Collateral Value, Revue Finance, vol. 25: 157-178.
  12. Credit Suisse Financial Products (1997), CreditRisk+. A Credit Risk Management Framework, Technical Document.
  13. Crosbie P. and Bohn J.R. (2002), Modelling default risk, mimeo, KMV corporation.
  14. Crouhy M., Galai D. and Mark R. (2000), A Comparative Analysis of Current Credit Risk Models, Journal of Banking and Finance, vol. 24: 59-117.
  15. Farinelli S. and Shkolnikov M. (2012), Two models of stochastic loss given default, The Journal of Credit Risk, vol. 8, 2: 3-20.
  16. Finger C.C. (1999), Conditional Approaches for CreditMetrics Portfolio Distributions, CreditMetrics Monitor, April, pp. 14-33.
  17. Finger C.C., Gupton G.M. and Bathia M. (1997), CreditMetrics: The Benchmark for Understanding Credit Risk, Technical Document, JP Morgan, New York.
  18. Frye J. (2000a), Collateral damage: a source of systematic credit risk, Risk, vol. 13, 4: 91-94.
  19. Frye J. (2000b), Depressing recoveries, Risk, vol. 13, 11: 108-111.
  20. Geske R. (1977), The Valuation of Corporate Liabilities as Compound Options, Journal of Financial and Quantitative Analysis, vol. 12: 541-552.
  21. Gordy M. (2000), A Comparative Anatomy of Credit Risk Models, Journal of Banking and Finance, vol. 24, January: 119-149.
  22. Greening T., Oline M., Rosenthal E. and Verde M. (2009), Defaults Surge, Recoveries Sink in 2009: Understanding the Fundamental and Cyclical Drivers of Corporate Recovery Rates. Credit Market Research Report, FitchRatings, July.
  23. Hamerle A., Knapp M. and Wildenauer N. (2007), Default and Recovery Correlations: a Dynamic Econometric Approach, Risk. vol. 20, 1: 100-105.
  24. Hillebrand M. (2006), Modeling and estimating dependent loss given default, Risk, vol. 19, 9: 120-125.
  25. Hu Y.T. and Perraudin W. (2006), The Dependence of Recovery Rates and Defaults, Risk Control Research Paper, 6/1.
  26. Jarrow R.A. (2001), Default parameter estimation using market prices, Financial Analysts Journal, vol. 57, 5: 75-92. Jokivuolle E. and Peura S. (2003), Incorporating Collateral Value Uncertainty in Loss Given
  27. Default Estimates and Loan-to-Value Ratios, European Financial Management, vol. 9, 3: 299-314.
  28. Jones E., Mason S. and Rosenfeld E. (1984), Contingent Claims Analysis of Corporate Capital Structures: An Empirical Investigation, Journal of Finance, vol. 39: 611-627.
  29. Kealhofer S. and Bohn J.R. (1993), Portfolio management of default risk, mimeo, KMV Corporation.
  30. McQuown J. (1993), A comment on Market vs. Accounting measures of default risk, mimeo, KMV corporation.
  31. Merton R.C. (1974), On the pricing of corporate debt: the risk structure of interest rates, Journal of Finance, vol. 29: 449-470.
  32. Moody’s Investors Service (2011), Corporate Default and Recovery Rates, 1920-2010, Special Comment, February.
  33. Moody’s Investors Service (2006), Default and Recovery Rates of Corporate Bond Issuers, 1920-2005, Special Comment, January.
  34. Pykhtin M. (2003), Unexpected recovery risk, Risk, vol. 16, 8: 74-78.
  35. Standard & Poor’s (2012), Default, Transition, and Recovery, RatingsDirect on the Global Credit Portal, March.
  36. Tasche D. (2004), The single risk factor approach to capital charges in case of correlated loss given default rates, Quantitative Financial Paper, 01/2004.
  37. Vasicek O.A. (1984), Credit Valuation, KMV Corporation, March.
  38. Wilson T.C. (1997a), Portfolio credit risk I, Risk, vol. 10, 9, September.
  39. Wilson T.C. (1997b), Portfolio credit risk II, Risk, vol. 10, 10, October.
  40. Wilson T.C. (1998), Portfolio Credit Risk, Federal Reserve Board of New York, Economic Policy Review, vol. 4, October: 71-82.

Annalisa Di Clemente, Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis in "STUDI ECONOMICI " 109/2013, pp 5-24, DOI: 10.3280/STE2013-109001