Originating in the theory of uniform distribution, Quasi-Monte
Carlo methods have become popular deterministic alternatives to classical Monte
Carlo for high-dimensional numerical integration. In this talk we will discuss
some attractive theoretical properties of Quasi-Monte Carlo integration, where
the notion of the discrepancy of a sequence plays an important role. Moreover,
advantages and limits of its implementation in practice are discussed and for
some applications in mathematical finance, the performance of the method is
illustrated.