Corpus ID: 235829105

Geometric insights into robust portfolio construction with gearing

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

Figures and Tables from this paper


A Sharper Angle on Optimization
The classical mean-variance optimization takes expected returns and variances and produces portfolio positions. In this paper we discuss the direction and the magnitude of the positions vectorExpand
Robust Portfolio Optimization
This work shows that the risk of the estimated portfolio converges to the oracle optimal risk with parametric rate under weakly dependent asset returns, thus allowing for heavy-tailed asset returns. Expand
Mean--variance portfolio optimization when means and covariances are unknown
The root cause of the enigma is explained, the new approach shown to provide substantial improvements over previous methods, and flexible modeling to incorporate dynamic features and fundamental analysis of the training sample of historical data, as illustrated in simulation and empirical studies. Expand
Minimum-Variance Portfolios in the U.S. Equity Market
In the minimum-variance portfolio, far to the left on the efficient frontier, security weights are independent of expected security returns. Portfolios can be constructed using only the estimatedExpand
Optimal Portfolio Choice with Parameter Uncertainty
Abstract In this paper, we analytically derive the expected loss function associated with using sample means and the covariance matrix of returns to estimate the optimal portfolio. Our analyticalExpand
Robust Portfolio Selection Problems
This paper introduces "uncertainty structures" for the market parameters and shows that the robust portfolio selection problems corresponding to these uncertainty structures can be reformulated as second-order cone programs and, therefore, the computational effort required to solve them is comparable to that required for solving convex quadratic programs. Expand
Robust portfolio selection using linear-matrix inequalities
Abstract In this paper, we consider the problem of robust optimal portfolio selection for tracking error when the expected returns of the risky and risk-free assets as well as the covariance matrixExpand
Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps
Mean-variance efficient portfolios constructed using sample moments often involve taking extreme long and short positions. Hence practitioners often impose portfolio weight constraints whenExpand
On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results
This paper investigates the sensitivity of mean-variance(MV)-efficient portfolios to changes in the means of individual assets. When only a budget constraint is imposed on the investment problem, theExpand
Incorporating estimation errors into portfolio selection: Robust portfolio construction
The authors explore the negative effect that estimation error has on mean-variance optimal portfolios. It is shown that asset weights in mean-variance optimal portfolios are very sensitive to slightExpand