Quasi-Monte Carlo for finance applications

Monte Carlo methods are used extensively in computational finance to estimate the price of financial derivative options. In this paper we review the use of quasi-Monte Carlo methods to obtain the same accuracy at a much lower computational cost, and focus on these key ingredients: i) the generation of Sobol and lattice points; ii) reduction of effective dimension using the principal component analysis approach at full potential; and iii) randomization by shifting or digital shifting to give an unbiased estimator with a confidence interval.