Enhanced quasi-Monte Carlo methods with dimension reduction

In recent years, the quasi-Monte Carlo approach for pricing high-dimensional derivative securities has been used widely relative to other competitive approaches such as the Monte Carlo methods. Such success can be, in part, attributed to the notion of effective dimension of the finance problems. In this paper, we provide additional insight on the connection between the effective dimension and the quasi-Monte Carlo method. We also propose a dimension reduction technique which further enhances the quasi-Monte Carlo method for derivative pricing. The efficiency of the proposed method is illustrated by applying it to high-dimensional multi-factor path-dependent derivative securities.