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A surrogate similarity measure for the mean-variance frontier optimisation problem under bound and cardinality constraints
2019
Journal of the Operational Research Society
This paper deals with the mean-variance optimization frontier problem when realistic constraints are considered. Our proposed methodology hybridizes a heuristic algorithm with an exact solution approach. A genetic algorithm is applied for the identification of the assets in the portfolio, whilst the asset weights in the portfolios are obtained by a quadratic programming model. The proposed algorithmic framework produces a constrained frontier that actually fulfils the bound and cardinality
doi:10.1080/01605682.2019.1657367
fatcat:e7zrzzurcveyzfvjdub7rddch4