Predicting loss severities for residential mortgage loans: A three-step selection approach

Hung Do, Daniel Rösch and Harald Scheule

European Journal of Operational Research, 2018, vol. 270, issue 1, 246-259

Abstract: This paper develops a novel framework to model the loss given default (LGD) of residential mortgage loans which is the dominant consumer loan category for many commercial banks. LGDs in mortgage lending are subject to two selection processes: default and cure, where the collateral value exceeds the outstanding loan amount. We propose a three-step selection approach with a joint probability framework for default, cure (i.e., zero-LGD) and non-zero loss severity information. The proposed methodology demonstrates improved performance in out-of-time predictions compared to widely used OLS regressions.

Keywords: Analytics; Default; Loss given default; Residential mortgage; Selection model (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:270:y:2018:i:1:p:246-259

DOI: 10.1016/j.ejor.2018.02.057

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