Wasserstein distance in terms of the comonotonicity Copula

The aim of this article is to write the -Wasserstein metric with the -norm, , on in terms of copula. In particular for the case of one-dimensional distributions, we get that the copula employed to get the optimal coupling of the Wasserstein distances is the comotonicity copula. We obtain the equivalent result also for -dimensional distributions under the sufficient and necessary condition that these have the same dependence structure of their one-dimensional marginals, i.e that the -dimensional distributions share the same copula. Assuming , and that the probability measures and are sharing the same copula, we also analyze the Wasserstein distance discussed in \cite{Alfonsi} and get an upper and lower bounds of in terms of , written in terms of comonotonicity copula. We show that as a consequence the lower and upper bound of can be written in terms of generalized inverse functions.
View on arXiv