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Multi-objective Basic Variable Neighborhood Search for Portfolio Selection

de Queiroz, Thiago Alves ; Mundim, Leandro Resende ; de Carvalho, André Carlos Ponce de Leon Ferreira

Variable Neighborhood Search, 2020, Vol.12010, p.67-80 [Periódico revisado por pares]

Switzerland: Springer International Publishing AG

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  • Título:
    Multi-objective Basic Variable Neighborhood Search for Portfolio Selection
  • Autor: de Queiroz, Thiago Alves ; Mundim, Leandro Resende ; de Carvalho, André Carlos Ponce de Leon Ferreira
  • Assuntos: Basic variable neighborhood search ; Mean-variance model ; Multiobjective optimization ; Portfolio optimization
  • É parte de: Variable Neighborhood Search, 2020, Vol.12010, p.67-80
  • Descrição: The Portfolio Selection Problem looks for a set of assets with the best trade-off between return and risk, that is, with the maximum expected return and the minimum risk (e.g., the variance of returns). As these objectives are conflicting, it is a difficult multi-objective problem. Different models and algorithms have been proposed to obtain the (optimal) Pareto front. However, exact approaches take days for a large set of points to the Pareto front. Within this perspective, we develop a basic variable neighborhood search heuristic to solve the bi-objective portfolio selection problem. The proposed heuristic considers ten neighborhood structures that are mainly based on swap moves and has a local improvement based on averaging the proportions that are invested in consecutive assets. The proposed heuristic was experimentally compared with the Mean-Variance model of Markowitz, using benchmark instances from the OR-Library. The number of assets in these instances ranges from 31 to 225. According to the experimental results, the proposed heuristic performed well in the construction of different Pareto fronts.
  • Títulos relacionados: Lecture Notes in Computer Science
  • Editor: Switzerland: Springer International Publishing AG
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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