Strongly Consistent Multivariate Conditional Risk Measures
Mathematical Finance
2016-09-27 v1
Abstract
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.
Keywords
Cite
@article{arxiv.1609.07903,
title = {Strongly Consistent Multivariate Conditional Risk Measures},
author = {Hannes Hoffmann and Thilo Meyer-Brandis and Gregor Svindland},
journal= {arXiv preprint arXiv:1609.07903},
year = {2016}
}