Approximation of Pro t - and - Loss Distributions ( Part II )

Part I [13] introduces the application of the barycentric approximation methodology for evaluating pro t-and-loss distributions numerically. Although, convergence of the quantiles is ensured by the weak convergence of the discrete measures, as proclaimed in [13], recent numerical results have indicated that the approximations of the pro t-and-loss distribution are less practical when the portfolio gets a reasonable complexity. This experience has revealed that the weak convergence of the probability measures appears not to be strong enough for evaluating quantiles numerically in a satisfactory way.