Cambou, MathieuFilipovic, Damir2017-05-012017-05-012017-05-01201710.1111/mafi.12097https://infoscience.epfl.ch/handle/20.500.14299/136778WOS:000397560600008This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence minimization from a reference probability measure subject to scenario constraints. An example from regulatory practice motivates the definition of five fundamental criteria that serve as a basis for our method. Standard risk measures, such as value-at-risk and expected shortfall, are shown to be robust with respect to minimum divergence scenario aggregation. Various examples illustrate the tractability of our method.model uncertaintyscenario aggregationexpected shortfallvalue-at-riskstatistical divergenceSwiss Solvency Testtext::journal::journal article::research article