Publication

Sparsity penalized mean-variance portfolio selection: analysis and computation

Buse Sen
2024

Abstract

We consider the problem of mean-variance portfolio selection regularized with an & $\ell _0$ -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.

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Buse Sen
2024

Abstract

Official source

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Sparsity penalized mean-variance portfolio selection: analysis and computation

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