  We quantify model risk of a financial portfolio whereby a multi-period
mean-standard-deviation criterion is used as a selection criterion. In this
work, model risk is defined as the loss due to uncertainty of the underlying
distribution of the returns of the assets in the portfolio. The uncertainty is
measured by the Kullback-Leibler divergence, i.e., the relative entropy. In the
worst case scenario, the optimal robust strategy can be obtained in a
semi-analytical form as a solution of a system of nonlinear equations. Several
numerical results are presented which allow us to compare the performance of
this robust strategy with the optimal non-robust strategy. For illustration, we
also quantify the model risk associated with an empirical dataset.
