Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression
Measuring interdependence between probabilities of default (PDs) in different industry sectors of an economy plays a crucial role in financial stress testing. Thereby, regression approaches may be employed to model the impact of stressed industry sectors as covariates on other response sectors. We i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-07-01
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| Series: | Risks |
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| Online Access: | https://www.mdpi.com/2227-9091/5/3/38 |
| _version_ | 1819131722429628416 |
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| author | Matthias Fischer Daniel Kraus Marius Pfeuffer Claudia Czado |
| author_facet | Matthias Fischer Daniel Kraus Marius Pfeuffer Claudia Czado |
| author_sort | Matthias Fischer |
| collection | DOAJ |
| description | Measuring interdependence between probabilities of default (PDs) in different industry sectors of an economy plays a crucial role in financial stress testing. Thereby, regression approaches may be employed to model the impact of stressed industry sectors as covariates on other response sectors. We identify vine copula based quantile regression as an eligible tool for conducting such stress tests as this method has good robustness properties, takes into account potential nonlinearities of conditional quantile functions and ensures that no quantile crossing effects occur. We illustrate its performance by a data set of sector specific PDs for the German economy. Empirical results are provided for a rough and a fine-grained industry sector classification scheme. Amongst others, we confirm that a stressed automobile industry has a severe impact on the German economy as a whole at different quantile levels whereas, e.g., for a stressed financial sector the impact is rather moderate. Moreover, the vine copula based quantile regression approach is benchmarked against both classical linear quantile regression and expectile regression in order to illustrate its methodological effectiveness in the scenarios evaluated. |
| first_indexed | 2024-12-22T09:20:01Z |
| format | Article |
| id | doaj.art-c457ef8fb060478b97e2ca2a6fe1eb96 |
| institution | Directory Open Access Journal |
| issn | 2227-9091 |
| language | English |
| last_indexed | 2024-12-22T09:20:01Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Risks |
| spelling | doaj.art-c457ef8fb060478b97e2ca2a6fe1eb962022-12-21T18:31:14ZengMDPI AGRisks2227-90912017-07-01533810.3390/risks5030038risks5030038Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile RegressionMatthias Fischer0Daniel Kraus1Marius Pfeuffer2Claudia Czado3Lehrstuhl für Statistik und Ökonometrie, Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, GermanyZentrum Mathematik, Technische Universität München, Boltzmanstraße 3, 85748 Garching, GermanyLehrstuhl für Statistik und Ökonometrie, Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, GermanyZentrum Mathematik, Technische Universität München, Boltzmanstraße 3, 85748 Garching, GermanyMeasuring interdependence between probabilities of default (PDs) in different industry sectors of an economy plays a crucial role in financial stress testing. Thereby, regression approaches may be employed to model the impact of stressed industry sectors as covariates on other response sectors. We identify vine copula based quantile regression as an eligible tool for conducting such stress tests as this method has good robustness properties, takes into account potential nonlinearities of conditional quantile functions and ensures that no quantile crossing effects occur. We illustrate its performance by a data set of sector specific PDs for the German economy. Empirical results are provided for a rough and a fine-grained industry sector classification scheme. Amongst others, we confirm that a stressed automobile industry has a severe impact on the German economy as a whole at different quantile levels whereas, e.g., for a stressed financial sector the impact is rather moderate. Moreover, the vine copula based quantile regression approach is benchmarked against both classical linear quantile regression and expectile regression in order to illustrate its methodological effectiveness in the scenarios evaluated.https://www.mdpi.com/2227-9091/5/3/38stress testingquantile regressionvine copulasexpectile regression |
| spellingShingle | Matthias Fischer Daniel Kraus Marius Pfeuffer Claudia Czado Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression Risks stress testing quantile regression vine copulas expectile regression |
| title | Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression |
| title_full | Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression |
| title_fullStr | Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression |
| title_full_unstemmed | Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression |
| title_short | Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression |
| title_sort | stress testing german industry sectors results from a vine copula based quantile regression |
| topic | stress testing quantile regression vine copulas expectile regression |
| url | https://www.mdpi.com/2227-9091/5/3/38 |
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