Lee, Yongwoong and Roesch, Daniel and Scheule, Harald (2016) Accuracy of mortgage portfolio risk forecasts during financial crises. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 249 (2). pp. 440-456. ISSN 0377-2217, 1872-6860
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This paper explores whether factor based credit portfolio risk models are able to predict losses in severe economic downturns such as the recent Global Financial Crisis (GFC) within standard confidence levels. The paper analyzes (i) the accuracy of default rate forecasts, and (ii) whether forecast downturn percentiles (Value-at-Risk, VaR) are sufficient to cover default rate outcomes over a quarterly and an annual forecast horizon. Uninformative maximum likelihood and informative Bayesian techniques are compared as they imply different degrees of uncertainty. We find that quarterly VaR estimates are generally sufficient but annual VaR estimates may be insufficient during economic downturns. In addition, the paper develops and analyzes models based on auto-regressive adjustments of scores, which provide a higher forecast accuracy. The consideration of parameter uncertainty and auto-regressive error terms mitigates the shortfall. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | CREDIT RISK; DEFAULT; MODELS; LOANS; Bayesian estimation; Maximum likelihood estimation; Model risk; Mortgage; Value-at-risk |
| Subjects: | 300 Social sciences > 330 Economics 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: | 12 Mar 2019 07:02 |
| Last Modified: | 12 Mar 2019 07:02 |
| URI: | https://pred.uni-regensburg.de/id/eprint/2380 |
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