Abstract:
We derive closed-form portfolio rules for robust mean-variance portfolio optimization where the return vector is uncertain or the mean return vector is subject to estimation errors, both uncertainties being confined to an ellipsoidal uncertainty set. We consider different mean-variance formulations allowing short sales, and derive closed-form optimal portfolio rules in static and dynamic settings. Keywords: Robust optimization, mean-variance portfolio theory, ellipsoidal uncertainty, adjustable robustness.