English

Random matrix approach for primal-dual portfolio optimization problems

Portfolio Management 2018-01-17 v2 Disordered Systems and Neural Networks Computational Engineering, Finance, and Science Machine Learning Optimization and Control

Abstract

In this paper, we revisit the portfolio optimization problems of the minimization/maximization of investment risk under constraints of budget and investment concentration (primal problem) and the maximization/minimization of investment concentration under constraints of budget and investment risk (dual problem) for the case that the variances of the return rates of the assets are identical. We analyze both optimization problems by using the Lagrange multiplier method and the random matrix approach. Thereafter, we compare the results obtained from our proposed approach with the results obtained in previous work. Moreover, we use numerical experiments to validate the results obtained from the replica approach and the random matrix approach as methods for analyzing both the primal and dual portfolio optimization problems.

Keywords

Cite

@article{arxiv.1709.04620,
  title  = {Random matrix approach for primal-dual portfolio optimization problems},
  author = {Daichi Tada and Hisashi Yamamoto and Takashi Shinzato},
  journal= {arXiv preprint arXiv:1709.04620},
  year   = {2018}
}

Comments

24 pages, 4 figures

R2 v1 2026-06-22T21:42:42.990Z