Kondor, I;
Papp, G;
Caccioli, F;
(2017)
Analytic solution to variance optimization with no short positions.
Journal of Statistical Mechanics: Theory and Experiment
, Article 123402. 10.1088/1742-5468/aa9684.
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Abstract
We consider the variance portfolio optimization problem with a ban on short selling. We provide an analytical solution by means of the replica method for the case of a portfolio of independent, but not identically distributed, assets. We study the behavior of the solution as a function of the ratio r between the number N of assets and the length T of the time series of returns used to estimate risk. The no-short-selling constraint acts as an asymmetric `1 regularizer, setting some of the portfolio weights to zero and keeping the out-of-sample estimator for the variance bounded, avoiding the divergence present in the non-regularized case. However, the ban on short positions does not prevent the phase transition in the optimization problem, only shifts the critical point from its non-regularized value of r = 1 to 2, and changes its character: at r = 2 the out-of-sample estimator for the portfolio variance stays finite and the estimated in-sample variance vanishes, while another critical parameter, related to the estimated portfolio weights and the condensate density, diverges at the critical value r = 2. We also calculate the distribution of the optimal weights over the random samples and show that the regularizer preferentially removes the assets with large variances, in accord with one’s natural expectation
| Type: | Article |
|---|---|
| Title: | Analytic solution to variance optimization with no short positions |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1088/1742-5468/aa9684 |
| Publisher version: | http://dx.doi.org/10.1088/1742-5468/aa9684 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Physical Sciences, Mechanics, Physics, Mathematical, Physics, cavity and replica method, quantitative finance, risk measure and management, Dimensional Covariance Matrices, Portfolio Optimization, Noise Sensitivity, Risk Measures, Selection, Constraints, Estimator, Shrinkage |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10044428 |
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