We propose a two-stage probit model (TPM) to predict recovery rates. By the ordinal nature of the three categories of recovery rates: total loss, total recovery, and lying between the two extremes, we first use the ordered probit model to predict the category that a given debt belongs to among the three ones. Then, for the debt that is classified as lying between the two extremes, we use the probit transformation regression to predict its recovery rate. We use real data sets to support TPM. Our empirical results show that macroeconomic-, debt-, firm-, and industry-specific variables are all important in determining recovery rates. Using an expanding rolling window approach, our empirical results confirm that TPM has better and more robust out-of-sample performance than its alternatives, in the sense of yielding more accurate predicted recovery rates.
Expanding rolling window approach Ordered probit model Probit transformation regression Two-stage probit model Recovery rate
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The authors thank the reviewers for their valuable comments and suggestions that have greatly improved the presentation of this paper. This research is supported by the Ministry of Science and Technology, Taiwan, Republic of China.
Acharya VV, Bharath ST, Srinivasan A (2007) Does industrywide distress affect defaulted firms? Evidence from creditor recoveries. J Financ Econ 85:787–821CrossRefGoogle Scholar
Ferrari SLP, Cribari-Neto F (2004) Beta regression for modeling rates and proportions. J Appl Stat 31:799–815CrossRefGoogle Scholar
Friedman CA, Sandow S (2005) Estimating conditional probability distributions of recovery rates: a utility-based approach. Available at http://ssrn.com/abstract=874754
Härdle W, Moro RA, Schäfer D (2008) Graphical data representation in bankruptcy analysis. In: Chen C, Härdle W, Unwin A (eds) Handbook of data visualization. Springer, Berlin, pp 853–873CrossRefGoogle Scholar
Hillegeist SA, Keating EK, Cram DP, Lundstedt KG (2004) Assessing the probability of bankruptcy. Rev Acc Stud 9:5–34CrossRefGoogle Scholar