Model and estimation risk in credit risk stress tests:
This paper deals with stress tests for credit risk and shows how exploiting the discretion when setting up and implementing a model can drive the results of a quantitative stress test for default probabilities. For this purpose, we employ several variations of a CreditPortfolioView-style model using...
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| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English German |
| Veröffentlicht: |
Frankfurt am Main
Deutsche Bundesbank
[2019]
|
| Schriftenreihe: | Discussion paper / Deutsche Bundesbank
no 09/2019 |
| Online-Zugang: | kostenfrei Volltext |
| Zusammenfassung: | This paper deals with stress tests for credit risk and shows how exploiting the discretion when setting up and implementing a model can drive the results of a quantitative stress test for default probabilities. For this purpose, we employ several variations of a CreditPortfolioView-style model using US data ranging from 2004 to 2016. We show that seemingly only slightly differing specifications can lead to entirely different stress test results - in relative and absolute terms. That said, our findings reveal that the conversion of a shock (i.e., stress event) increases the (non-stress) default probability by 20% to 80% - depending on the stress test model selected. Interestingly, forecasts for non-stress default probabilities are less exposed to model and estimation risk. In addition, the risk horizon over which the stress default probabilities are forecasted and whether we consider mean stress default probabilities or quantiles seem to play only a minor role for the dispersion between the results of the different model specifications. Our findings emphasize the importance of extensive robustness checks for model-based credit risk stress tests |
| Beschreibung: | Zusammenfassung in deutsch und englisch |
| Beschreibung: | 39 Seiten Diagramme |
| ISBN: | 9783957295675 |
Internformat
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| 520 | 3 | |a This paper deals with stress tests for credit risk and shows how exploiting the discretion when setting up and implementing a model can drive the results of a quantitative stress test for default probabilities. For this purpose, we employ several variations of a CreditPortfolioView-style model using US data ranging from 2004 to 2016. We show that seemingly only slightly differing specifications can lead to entirely different stress test results - in relative and absolute terms. That said, our findings reveal that the conversion of a shock (i.e., stress event) increases the (non-stress) default probability by 20% to 80% - depending on the stress test model selected. Interestingly, forecasts for non-stress default probabilities are less exposed to model and estimation risk. In addition, the risk horizon over which the stress default probabilities are forecasted and whether we consider mean stress default probabilities or quantiles seem to play only a minor role for the dispersion between the results of the different model specifications. Our findings emphasize the importance of extensive robustness checks for model-based credit risk stress tests | |
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Datensatz im Suchindex
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| author | Grundke, Peter 1971- Pliszka, Kamil Tuchscherer, Michael |
| author_GND | (DE-588)134153421 (DE-588)1181206731 (DE-588)1181206812 |
| author_facet | Grundke, Peter 1971- Pliszka, Kamil Tuchscherer, Michael |
| author_role | aut aut aut |
| author_sort | Grundke, Peter 1971- |
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| building | Verbundindex |
| bvnumber | BV045517191 |
| classification_rvk | QB 910 |
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| discipline | Wirtschaftswissenschaften |
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| id | DE-604.BV045517191 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:20:18Z |
| institution | BVB |
| isbn | 9783957295675 |
| language | English German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030901546 |
| oclc_num | 1090780005 |
| open_access_boolean | 1 |
| owner | DE-12 DE-M382 DE-355 DE-BY-UBR |
| owner_facet | DE-12 DE-M382 DE-355 DE-BY-UBR |
| physical | 39 Seiten Diagramme |
| psigel | ebook |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Deutsche Bundesbank |
| record_format | marc |
| series2 | Discussion paper / Deutsche Bundesbank |
| spelling | Grundke, Peter 1971- Verfasser (DE-588)134153421 aut Model and estimation risk in credit risk stress tests Peter Grundke (Osnabrück University), Kamil Pliszka(Deutsche Bundesbank), Michael Tuchscherer (Osnabrück University) Frankfurt am Main Deutsche Bundesbank [2019] 39 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Discussion paper / Deutsche Bundesbank no 09/2019 Zusammenfassung in deutsch und englisch This paper deals with stress tests for credit risk and shows how exploiting the discretion when setting up and implementing a model can drive the results of a quantitative stress test for default probabilities. For this purpose, we employ several variations of a CreditPortfolioView-style model using US data ranging from 2004 to 2016. We show that seemingly only slightly differing specifications can lead to entirely different stress test results - in relative and absolute terms. That said, our findings reveal that the conversion of a shock (i.e., stress event) increases the (non-stress) default probability by 20% to 80% - depending on the stress test model selected. Interestingly, forecasts for non-stress default probabilities are less exposed to model and estimation risk. In addition, the risk horizon over which the stress default probabilities are forecasted and whether we consider mean stress default probabilities or quantiles seem to play only a minor role for the dispersion between the results of the different model specifications. Our findings emphasize the importance of extensive robustness checks for model-based credit risk stress tests Pliszka, Kamil Verfasser (DE-588)1181206731 aut Tuchscherer, Michael Verfasser (DE-588)1181206812 aut Erscheint auch als Online-Ausgabe 978-3-95729-568-2 Deutsche Bundesbank Discussion paper no 09/2019 (DE-604)BV040156046 2019,09 https://www.bundesbank.de/resource/blob/781380/19cd7353d3b8906d088fd3b662d2fd42/mL/2019-03-08-dkp-09-data.pdf kostenfrei https://www.bundesbank.de/resource/blob/781380/19cd7353d3b8906d088fd3b662d2fd42/mL/2019-03-08-dkp-09-data.pdf Verlag kostenfrei Volltext |
| spellingShingle | Grundke, Peter 1971- Pliszka, Kamil Tuchscherer, Michael Model and estimation risk in credit risk stress tests |
| title | Model and estimation risk in credit risk stress tests |
| title_auth | Model and estimation risk in credit risk stress tests |
| title_exact_search | Model and estimation risk in credit risk stress tests |
| title_full | Model and estimation risk in credit risk stress tests Peter Grundke (Osnabrück University), Kamil Pliszka(Deutsche Bundesbank), Michael Tuchscherer (Osnabrück University) |
| title_fullStr | Model and estimation risk in credit risk stress tests Peter Grundke (Osnabrück University), Kamil Pliszka(Deutsche Bundesbank), Michael Tuchscherer (Osnabrück University) |
| title_full_unstemmed | Model and estimation risk in credit risk stress tests Peter Grundke (Osnabrück University), Kamil Pliszka(Deutsche Bundesbank), Michael Tuchscherer (Osnabrück University) |
| title_short | Model and estimation risk in credit risk stress tests |
| title_sort | model and estimation risk in credit risk stress tests |
| url | https://www.bundesbank.de/resource/blob/781380/19cd7353d3b8906d088fd3b662d2fd42/mL/2019-03-08-dkp-09-data.pdf |
| volume_link | (DE-604)BV040156046 |
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