In this paper we investigate the ability of different models to produce useful var-estimates for exchange rate positions. Our analysis shows that it is important to take into account parameter uncertainty, since this leads to uncertainty in the predicted var. We make this uncertainty in the var explicit by means of simulation. Our empirical results suggest that more sophisticated tail-modeling approaches come at the cost of more uncertainty about the var-estimate itself. We show how to adjust var calculations in order to take the parameter uncertainty into account. This is accomplished through a data-driven method to deliver not just a point estimate of the var, but a region.