Aggregating Risks with Partial Dependence Information

Abstract

We consider the problem of aggregating dependent risks in the presence of partial dependence information. More concretely, we assume that the risks involved belong to independent subgroups and the dependence structure within each group is unknown. A sharp convex upper bound exists in this setting, and this constrained upper bound improves the existing, unconstrained, comonotonic upper bound in convex order. Moreover, we prove the uniqueness of this constrained upper bound and provide a characterization in terms of the distribution of its sum. Numerical illustrations are provided to show the improvement of the new upper bound.