On high performance software development for the numerical simulation of life insurance policies

In this work we focus on the numerical issues involved in evaluating an important class of financial derivatives: participating life insurance contracts. We investigate the impact of different numerical methods on accuracy and efficiency in the solution of main computational kernels generally arising from mathematical models describing the financial problem. The main kernels involved in the evaluation of these financial derivatives are multidimensional integrals and stochastic differential equations. For this reasonweconsiderdifferentMonteCarlosimulationsandvariousstochasticdifferential-equationdiscretizationschemes.WehaveestablishedthatacombinationoftheMonteCarlomethodwiththeantitheticvariates(AV)variancereduction technique and the fully implicit Euler scheme developed by Brigo and Alfonsi (2005) provides high efficiency and good accuracy.