Predicting bank loan recovery rates with a mixed continuous‐discrete model

Raffaella Calabrese ()

Applied Stochastic Models in Business and Industry, 2014, vol. 30, issue 2, 99-114

Abstract: To represent the high concentration of recovery rates at the boundaries, we propose to consider the recovery rate as a mixed random variable, obtained as the mixture of a Bernoulli random variable and a beta random variable. We suggest to estimate the mixture weights and the Bernoulli parameter by two logistic regression models. For the recovery rates belonging to the interval (0,1), we model, jointly, the mean and the dispersion by using two link functions, so we propose the joint beta regression model that accommodates skewness and heteroscedastic errors. This methodological proposal is applied to a comprehensive survey on loan recovery process of Italian banks. In the regression model, we include some macroeconomic variables because they are relevant to explain the recovery rate and allow to estimate it in downturn conditions, as Basel II requires. Copyright © 2012 John Wiley & Sons, Ltd.

Date: 2014
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https://doi.org/10.1002/asmb.1932

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:30:y:2014:i:2:p:99-114

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