Abstract
The mean-variance portfolio allocation model is very sensitive to estimation errors in the model parameters. Robust optimization is a technique used to incorporate the uncertainty introduced by estimation errors directly into portfolio allocation. Practitioners are often faced with complex constraints on the portfolio structure such as limits on the number of securities in the portfolio, which are modelled with discrete variables, and introduce discontinuities in the efficient frontier. This article investigates the size of discontinuities in the efficient frontiers obtained by the classical and robust mean-variance models under such discrete asset choice constraints, as well as the impact of portfolio size on the discontinuity being considered. In addition, we analyse the effects of applying discrete asset choice restrictions to the portfolio selection problem, as well as using estimated and true parameters in the computation of the classical and robust mean-variance investment strategies under discrete asset choice constraints. Computational experiments reveal reduction of the size of discontinuity when using robust optimization mean-variance models.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
