英文标题：
《Strongly Consistent Multivariate Conditional Risk Measures》
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作者：
Hannes Hoffmann, Thilo Meyer-Brandis, Gregor Svindland
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最新提交年份：
2016
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英文摘要：
We consider families of strongly consistent multivariate conditional risk measures. We show that under strong consistency these families admit a decomposition into a conditional aggregation function and a univariate conditional risk measure as introduced Hoffmann et al. (2016). Further, in analogy to the univariate case in F\\\"ollmer (2014), we prove that under law-invariance strong consistency implies that multivariate conditional risk measures are necessarily multivariate conditional certainty equivalents.
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中文摘要：
我们考虑强一致的多元条件风险测度族。我们表明，在强一致性条件下，这些族允许分解为条件聚集函数和一元条件风险度量，如Hoffmann et al.（2016）所述。此外，与F“ollmer（2014）中的单变量情况类似，我们证明了在法律不变性下，强一致性意味着多元条件风险度量必然是多元条件确定性等价物。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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