  We study robust mean-variance optimization in multiperiod portfolio selection
by allowing the true probability measure to be inside a Wasserstein ball
centered at the empirical probability measure. Given the confidence level, the
radius of the Wasserstein ball is determined by the empirical data. The
numerical simulations of the US stock market provide a promising result
compared to other popular strategies.
