Parallel computing of a quasi-Monte Carlo algorithm for valuing derivatives

Abstract The performance of the standard Monte Carlo method is compared with the performance obtained through the use of ( t , m , s )-nets in base b in the approximation of several high dimensional integral problems in valuing derivatives and other securities. The ( t , m , s )-nets are generated by a parallel algorithm, where particular considerations are given to scalability of dynamic adaptive routing and load balancing in the design and implementation of the algorithm. From the numerical evidence it appears that such nets can be powerful tools for valuing such securities.