Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1155411 | Stochastic Processes and their Applications | 2014 | 24 Pages |
Abstract
We axiomatically introduce risk-consistent conditional systemic risk measures defined on multidimensional risks. This class consists of those conditional systemic risk measures which can be decomposed into a state-wise conditional aggregation and a univariate conditional risk measure. Our studies extend known results for unconditional risk measures on finite state spaces. We argue in favor of a conditional framework on general probability spaces for assessing systemic risk. Mathematically, the problem reduces to selecting a realization of a random field with suitable properties. Moreover, our approach covers many prominent examples of systemic risk measures from the literature and used in practice.
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Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Hannes Hoffmann, Thilo Meyer-Brandis, Gregor Svindland,