A parallel wavelet-based pricing procedure for Asian options

In this paper, we present a parallel pricing algorithm for Asian options based on the Discrete Wavelet Transform. The computational kernel of the pricing model is the solution of integral equations. We obtain a sparse and accurate representation of the kernel of such equations in wavelet function bases. It is worth pointing out that the execution time of our procedure is almost constant with respect to the number of monitoring dates. Thus, our pricing procedure is particularly competitive when the number of monitoring dates is large. We moreover discuss the parallelization of the algorithm. Numerical results that show the accuracy and efficiency of the procedure are reported in the paper.