Do, Hung Xuan and Rosch, Daniel and Scheule, Harald (2018) Predicting loss severities for residential mortgage loans: A three-step selection approach. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 270 (1). pp. 246-259. ISSN 0377-2217, 1872-6860
Full text not available from this repository. (Request a copy)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. (C) 2018 Elsevier B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | SUPPORT VECTOR MACHINES; CREDIT RISK-ASSESSMENT; EMPIRICAL-EVIDENCE; DEFAULT EVIDENCE; PROPERTY-VALUES; MODELS; FORECLOSURES; CLASSIFIER; BEHAVIOR; PRICES; Analytics; Default; Loss given default; Residential mortgage; Selection model |
| Subjects: | 600 Technology > 650 Management & auxiliary services |
| Divisions: | Business, Economics and Information Systems > Institut für Betriebswirtschaftslehre > Lehrstuhl für Statistik und Risikomanagement (Prof. Dr. Rösch) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 11 Dec 2019 10:46 |
| Last Modified: | 11 Dec 2019 10:46 |
| URI: | https://pred.uni-regensburg.de/id/eprint/13820 |
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