is an associate professor at San Francisco State University's College of Business.This article examines the use of Monte Carlo simulation with low-discrepancy sequences (or quasi-Monte Carlo) for valuing complex derivatives contracts versus the more traditional Monte Carlo method using random sequences. Unlike the latter, low-discrepancy (or quasi-random) sequences are deterministic.Some research has hinted that low-discrepancy sequences improve the rate of convergence of Monte For a large sample of simulated price paths, the mean of the sample will closely approximate the derivative's true price [i.e., Equation (1)]. The rate of convergence is (J/ -iN, where (J is the standard deviation of the population, and N is the number of simulations (price paths).Unfortunately, the rate of convergence is 64