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Ensemble predictions of recovery rates

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Author Info

  • Joao A. Bastos

    (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)

Abstract

In many domains, the combined opinion of a committee of experts provides better decisions than the judgment of a single expert. This paper shows how to implement a successful ensemble strategy for predicting recovery rates on defaulted debts. Using data from Moody's Ultimate Recovery Database, it is shown that committees of models derived from the same regression method present better forecasts of recovery rates than a single model. More accurate predictions are observed whether we forecast bond or loan recoveries, and across the entire range of actual recovery values.

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File URL: http://cemapre.iseg.utl.pt/RePEc/papers/WP1301.pdf
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Bibliographic Info

Paper provided by Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon in its series CEMAPRE Working Papers with number 1301.

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Length: 26 pages
Date of creation: Mar 2013
Date of revision:
Handle: RePEc:cma:wpaper:1301

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Related research

Keywords: Recovery rate; Loss given default; Forecasting; Ensemble learning; Credit risk;

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References

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  1. Sanjiv Das, 2007. "Basel II: Correlation Related Issues," Journal of Financial Services Research, Springer, vol. 32(1), pages 17-38, October.
  2. Leslie E. Papke & Jeffrey M. Wooldridge, 1993. "Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates," NBER Technical Working Papers 0147, National Bureau of Economic Research, Inc.
  3. Joao A. Bastos, 2009. "Forecasting bank loans loss-given-default," CEMAPRE Working Papers 0901, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  4. Dermine, J. & de Carvalho, C. Neto, 2006. "Bank loan losses-given-default: A case study," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1219-1243, April.
  5. Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer, vol. 34(1), pages 1-34, August.
  6. Grunert, Jens & Weber, Martin, 2009. "Recovery rates of commercial lending: Empirical evidence for German companies," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 505-513, March.
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Cited by:
  1. Altman, Edward I. & Kalotay, Egon A., 2014. "Ultimate recovery mixtures," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 116-129.

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