Risk aggregation with dependence uncertainty

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Combining p-values via averaging (2012, unknown): “To establish the main results in this paper, we will use many recent results in robust risk aggregation, in particular, many results in [6, 43, 1, 7, 42, 18].”
A New Approach to Assessing Model Risk in High Dimensions (2015, unknown): “…when d > 2, in most cases, the worst copula (under constraints) of a vector X does not give rise to the highest possible value of the risk measure at hand of S ¼ P ¼ 1 X i , because the marginal distributions also have an impact; see e.g., Bernard et al. (2014) for illustrations of this feature.”
An Academic Response to Basel 3.5 (2014, background): “As argued in Bernard et al. (2014), the numerical approximations obtained through the RA suggest that the bound, VaR, in Proposition 3.1 is sharp for all commonly used marginal distributions, and this is without the requirement of a tail-decreasing density. Up to now, we do not have a formal proof o”