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.