  Copulas. We study the model risk of multivariate risk models in a
comprehensive empirical study on Copula-GARCH models used for forecasting
Value-at-Risk and Expected Shortfall. To determine whether model risk inherent
in the forecasting of portfolio risk is caused by the candidate marginal or
copula models, we analyze different groups of models in which we fix either the
marginals, the copula, or neither. Model risk is economically significant, is
especially high during periods of crisis, and is almost completely due to the
choice of the copula. We then propose the use of the model confidence set
procedure to narrow down the set of available models and reduce model risk for
Copula-GARCH risk models. Our proposed approach leads to a significant
improvement in the mean absolute deviation of one day ahead forecasts by our
various candidate risk models.
