Ensemble Predictions of Recovery Rates
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...
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| Veröffentlicht in: | Journal of financial services research 2014-10, Vol.46 (2), p.177-193 |
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| container_title | Journal of financial services research |
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| creator | Bastos, João A. |
| description | 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. |
| doi_str_mv | 10.1007/s10693-013-0165-3 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 0920-8550 |
| ispartof | Journal of financial services research, 2014-10, Vol.46 (2), p.177-193 |
| issn | 0920-8550 1573-0735 |
| language | eng |
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| source | Business Source Complete; Springer Nature - Complete Springer Journals |
| subjects | Accuracy Collateral Committees Credit risk Datasets Default Economics and Finance External debt Finance Financial Services Forecasting Forecasting techniques Forecasts Judgement Loans Macroeconomics/Monetary Economics//Financial Economics Nonperforming loans Regression analysis Studies |
| title | Ensemble Predictions of Recovery Rates |
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