# Geometric insights into robust portfolio construction with gearing

@inproceedings{Dalmeyer2021GeometricII, title={Geometric insights into robust portfolio construction with gearing}, author={Lara Dalmeyer and T. Gebbie}, year={2021} }

We investigate and extend the results of Golts and Jones [18] that an alpha-weight angle resulting from unconstrained quadratic portfolio optimisations has an upper bound dependent on the condition number of the covariance matrix. This implies that better conditioned covariance matrices produce weights from unconstrained mean-variance optimisations that are better aligned with each assets expected return. We provide further clarity on the mathematical insights that relate the inequality between… Expand

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