Ordering risk bounds in factor models
Conditionally comonotonic risk vectors have been proved in [4] to yield worst case dependence structures maximizing the risk of the portfolio sum in partially specified risk factor models. In this paper we investigate the question how risk bounds depend on the specification of the pairwise copulas o...
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De Gruyter
2018-11-01
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| Series: | Dependence Modeling |
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| Online Access: | https://doi.org/10.1515/demo-2018-0015 |
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doaj-c92322be8d0c4a1fae5b2e8748e07d072021-10-02T19:14:53ZengDe GruyterDependence Modeling2300-22982018-11-016125928710.1515/demo-2018-0015demo-2018-0015Ordering risk bounds in factor modelsAnsari Jonathan0Rüschendorf Ludger1University of Freiburg, Freiburg,Baden-Württemberg, GermanyUniversity of Freiburg, Freiburg,Baden-Württemberg, GermanyConditionally comonotonic risk vectors have been proved in [4] to yield worst case dependence structures maximizing the risk of the portfolio sum in partially specified risk factor models. In this paper we investigate the question how risk bounds depend on the specification of the pairwise copulas of the risk components Xiwith the systemic risk factor. As basic toolwe introduce a new ordering based on sign changes of the derivatives of copulas. This together with discretization by n-grids and the theory of supermodular transfers allows us to derive concrete ordering criteria for the maximal risks.https://doi.org/10.1515/demo-2018-0015products of copulassupermodular orderingrisk boundsconditionally comonotonic distributionsmass transfer theoryelliptical distributionsarchimedean copulas |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Ansari Jonathan Rüschendorf Ludger |
| spellingShingle |
Ansari Jonathan Rüschendorf Ludger Ordering risk bounds in factor models Dependence Modeling products of copulas supermodular ordering risk bounds conditionally comonotonic distributions mass transfer theory elliptical distributions archimedean copulas |
| author_facet |
Ansari Jonathan Rüschendorf Ludger |
| author_sort |
Ansari Jonathan |
| title |
Ordering risk bounds in factor models |
| title_short |
Ordering risk bounds in factor models |
| title_full |
Ordering risk bounds in factor models |
| title_fullStr |
Ordering risk bounds in factor models |
| title_full_unstemmed |
Ordering risk bounds in factor models |
| title_sort |
ordering risk bounds in factor models |
| publisher |
De Gruyter |
| series |
Dependence Modeling |
| issn |
2300-2298 |
| publishDate |
2018-11-01 |
| description |
Conditionally comonotonic risk vectors have been proved in [4] to yield worst case dependence structures maximizing the risk of the portfolio sum in partially specified risk factor models. In this paper we investigate the question how risk bounds depend on the specification of the pairwise copulas of the risk components Xiwith the systemic risk factor. As basic toolwe introduce a new ordering based on sign changes of the derivatives of copulas. This together with discretization by n-grids and the theory of supermodular transfers allows us to derive concrete ordering criteria for the maximal risks. |
| topic |
products of copulas supermodular ordering risk bounds conditionally comonotonic distributions mass transfer theory elliptical distributions archimedean copulas |
| url |
https://doi.org/10.1515/demo-2018-0015 |
| work_keys_str_mv |
AT ansarijonathan orderingriskboundsinfactormodels AT ruschendorfludger orderingriskboundsinfactormodels |
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1716847613172514816 |