The bounds for risk measures of a portfolio when its components have known marginal distributions but the dependence among the risks is unknown are often too wide to be useful in practice. Moreover, availability of additional dependence information, such as knowledge of some higher-order...

We show that maximizing distortion risk measures over the set of distribution functions with given mean is equivalent to maximizing their concave counterpart. In the case of Value-at-Risk and Tail Value-at-Risk the equivalence also holds when adding information on higher moments

We study upper and lower bounds on the expectile risk measure of risky portfolios when the joint distribution of the risky components is not fully specified. First, we summarize methods for obtaining bounds when only the marginal distributions of the components are known, but not their...

In this paper, we assess the magnitude of model uncertainty of credit risk portfolio models, i.e., what is the maximum and minimum Value-at-Risk (VaR) of a portfolio of risky loans that can be justi ed given a certain amount of available information. Puccetti and Ruschendorf (2012a) and...

This paper unifies the work on multiple reinsurers, distortion risk measures, premium budgets,and heterogeneous beliefs. An insurer minimizes a distortion risk measure, while seekingreinsurance with finitely many reinsurers. The reinsurers use distortion premium principles, andthey are allowed...

The study of worst-case scenarios for risk measures (e.g., Value-at-Risk) when the underlying risk (or portfolio of risks) is not completely specified is a central topic in the literature on robust risk measurement. In this paper, we tackle the open problem of deriving upper bounds for strictly...

This paper introduces the family of Weighted Aumann-Shapley values for piecewise linear fuzzy games. The regular Aumann-Shapley value is not well-defined in case some differentiability condition is not satisfied. As an alternative, we introduce a family of allocation rules inspired by the...