calculation worst-case Value-at-Risk prediction using empirical data under model uncertainty

Quantification of risk positions under model uncertainty is of crucial importance from both viewpoints of external regulation and internal management. The concept of model uncertainty, sometimes also referred to as model ambiguity. Although we know the family of models, we cannot precisely decide which one to use. Given the set $\mathcal{P}$, the value of the risk measure $ρ$ varies in a range over the set of all possible models. The largest value in such a range is referred to as a worst-case v...