  It is well known that there are asymmetric dependence structures between
financial returns. In this paper we use a new nonparametric measure of local
dependence, the local Gaussian correlation, to improve portfolio allocation. We
extend the classical mean-variance framework, and show that the portfolio
optimization is straightforward using our new approach, only relying on a
tuning parameter (the bandwidth). The new method is shown to outperform the
equally weighted (1/N) portfolio and the classical Markowitz portfolio for
monthly asset returns data.
