Akkaya, DenizPınar, Mustafa ÇelebiŞen, Buse2025-02-172025-02-172024-11-250025-5610https://hdl.handle.net/11693/116337We consider the problem of mean–variance portfolio selection regularized with an -penalty term to control the sparsity of the portfolio. We analyze the structure of local and global minimizers and use our results in the design of a Branch-and-Bound algorithm coupled with an advanced start heuristic. Extensive computational results with real data as well as comparisons with an off-the-shelf and state-of-the-art (MIQP) solver are reported.EnglishCC BY 4.0 DEED (Attribution 4.0 International)https://creativecommons.org/licenses/by/4.0/Mean-variance portfolioRegularizationSparsityL0-normBranch-and-BoundArticle10.1007/s10107-024-02161-51436-4646