A Non-parametric Approach to Incorporating Incomplete Workouts Into Loss Given Default Estimates

Rapisarda, Grazia and Echeverry, David (2010): A Non-parametric Approach to Incorporating Incomplete Workouts Into Loss Given Default Estimates.

Abstract

When estimating Loss Given Default (LGD) parameters using a workout approach, i.e. discounting cash flows over the workout period, the problem arises of how to take into account partial recoveries from incomplete work-outs. The simplest approach would see LGD based on complete recovery profiles only. Whilst simple, this approach may lead to data selection bias, which may be at the basis of regulatory guidance requiring the assessment of the relevance of incomplete workouts to LGD estimation. Despite its importance, few academic contributions have covered this topic. We enhance this literature by developing a non-parametric estimator that -under certain distributional assumptions on the recovery profiles- aggregates complete and incomplete workout data to produce unbiased and more efficient estimates of mean LGD than those obtained from the estimator based on resolved cases only. Our estimator is appropriate in LGD estimation for wholesale portfolios, where the exposure-weighted LGD estimators available in the literature would not be applicable under Basel II regulatory guidance.

• Item Type: MPRA Paper
• Language: English
• Keywords: Credit risk; bank loans; loss-given-default; LGD; incomplete observations; mortality curves
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; G - Financial Economics > G3 - Corporate Finance and Governance > G32 - Financing Policy ; Financial Risk and Risk Management ; Capital and Ownership Structure ; Value of Firms ; Goodwill

References

[1] Altman, Edward. Measuring Corporate Bond Mortality and Performance. The Journal of Finance, Vol. 44, No. 4. Sept. 1989.

[2] Altman, Edward. Default Recovery Rates and LGD in Credit Risk Modeling and Practise. 2009.

[3] Altman, Edward I., Resti, Andrea and Sironi, Andrea. Default Recovery Rates: A Review of the Literature and Recent Empirical Evidence. Journal of Finance Literature, 21-45. Winter 2006.

[4] Altman, Edward. and Suggitt, Heather. Default Rates in the Syndicated Bank Loan Market: A Mortality Analysis. Journal of Banking and Finance, Vol. 24, pp. 229-253. 2008.

[5] Basel Committee on Banking Supervision, 2004. International Convergence on Capital Measurement and Capital Standards. Basel.

[6] Bastos, Joao. Forecasting bank loan loss-given-default. CEMAPRE. Technical University of Lisbon.

[7] Dermine, Jean and Neto de Carvalho, Cristina. Bank Loan Losses-Given-Default: a Case Study. Journal of Banking and Finance, Vol. 30, No. 4, pp. 1219-1243. Apr. 2006.

[8] Dhaene, Jan, Denuit, Michel, Goovaerts, Marc, Kaas, Rob and Vyncke, David. The Concept of Comonotonicity in Actuarial Science and Finance: Applications. Insurance: Mathematics and Economics, Vol. 31, No. 2, pp. 133-161. 2002

[9] Dhaene, Jan, Denuit, Michel, Goovaerts, Marc, Kaas, Rob and Vyncke, David. The Concept of Comonotonicity in Actuarial Science and Finance: Theory. Insurance: Mathematics and Economics, Vol. 31, No. 1, pp. 3-33. 2002

[10] Fuller, Russell J. and Kim, Sang-Hoon. Inter-Temporal Correlation of Cash Flows and the Risk of Multi-Period Investment Projects.The Journal of Financial and Quantitative Analysis, Vol. 15, No. 5, pp. 1149-1162. Dec. 1980.

[11] Kaplan, E. L. and Meier, Paul. Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, Vol. 53, No. 282, pp. 457-481. Jun. 1958.

[12] Moody's Investor Service, Special Comment. Measuring loss-given-default for structured nance securities: an update. Dec. 2006.

[13] Trück, Stefan, Harpaintner, Stefan and Rachev, Svetlozar. A Note on Forecasting Aggregate Recovery Rates with Macroeconomic Variables. Mar. 2005.