2016/09/26 by Hannes Hoffmann, Thilo Meyer-Brandis, Gregor Svindland
Economics, Econometrics and Finance · #q-fin.RM
published as Stochastic Processes and their Applications, Vol. 126, No. 7, pp. 2014-2037
arxiv created 2016/09/26 · arxiv updated 2016/09/27
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.