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Portfolio Allocation under Asymmetric Dependence in Asset Returns using Local Gaussian Correlations
Anders D. Sleire, Bård Støve, Håkon Otneim, Geir Drage Berentsen, Dag Tjøstheim, Sverre Hauso Haugen
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.
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