Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 2014-2037 |
| Seitenumfang | 24 |
| Fachzeitschrift | Stochastic Processes and their Applications |
| Jahrgang | 126 |
| Ausgabenummer | 7 |
| Publikationsstatus | Veröffentlicht - Juli 2016 |
| Extern publiziert | Ja |
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.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Statistik und Wahrscheinlichkeit
- Mathematik (insg.)
- Modellierung und Simulation
- Mathematik (insg.)
- Angewandte Mathematik
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in: Stochastic Processes and their Applications, Jahrgang 126, Nr. 7, 07.2016, S. 2014-2037.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Risk-consistent conditional systemic risk measures
AU - Hoffmann, H.
AU - Meyer-Brandis, T.
AU - Svindland, G.
N1 - Publisher Copyright: © 2016 Elsevier B.V. All rights reserved.
PY - 2016/7
Y1 - 2016/7
N2 - 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.
AB - 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.
KW - Conditional aggregation
KW - Conditional expected short fall
KW - Conditional systemic risk measure
KW - Conditional value at risk
KW - Risk-consistent properties
UR - http://www.scopus.com/inward/record.url?scp=84956610197&partnerID=8YFLogxK
U2 - 10.1016/j.spa.2016.01.002
DO - 10.1016/j.spa.2016.01.002
M3 - Article
VL - 126
SP - 2014
EP - 2037
JO - Stochastic Processes and their Applications
JF - Stochastic Processes and their Applications
SN - 0304-4149
IS - 7
ER -