Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations

It is well known that there are asymmetric dependence structures between financial returns. This paper describes a portfolio selection method rooted in the classical mean–variance framework that incorporates such asymmetric dependency structures using a nonparametric measure of local dependence, the local Gaussian correlation (LGC). It is shown that the portfolio optimization process for financial returns with asymmetric dependence structures is straightforward using local covariance matrices. The new method is shown to outperform the equally weighted (“1/N”) portfolio and the classical Markowitz portfolio when applied to historical data on six assets.