Portfolio selection is concerned with selecting from of a universe of assets the ones in which one wishes to invest and the amount of the investment. Several criteria can be used for portfolio selection, and the resulting approaches can be classified as being either active or passive. The two approaches are thought to be mutually exclusive, but some authors have suggested combining them in a unified framework. In this work, we define a multi-criteria optimisation problem in which the two types of approaches are combined, and we introduce a hybrid metaheuristic that combines local search and quadratic programming to obtain an approximation of the Pareto set. We experimentally analyse this approach on benchmarks from two different instance classes: these classes refer to the same indexes, but they use two different return representations. Results show that this metaheuristic can be effectively used to solve multi-criteria portfolio selection problems. Furthermore, with an experiment on a set of instances coming from a different financial scenario, we show that the results obtained by our metaheuristic are robust with respect to the return representation used.

A metaheuristic multi-criteria optimisation approach to portfolio selection

di Tollo, Giacomo;
In corso di stampa

Abstract

Portfolio selection is concerned with selecting from of a universe of assets the ones in which one wishes to invest and the amount of the investment. Several criteria can be used for portfolio selection, and the resulting approaches can be classified as being either active or passive. The two approaches are thought to be mutually exclusive, but some authors have suggested combining them in a unified framework. In this work, we define a multi-criteria optimisation problem in which the two types of approaches are combined, and we introduce a hybrid metaheuristic that combines local search and quadratic programming to obtain an approximation of the Pareto set. We experimentally analyse this approach on benchmarks from two different instance classes: these classes refer to the same indexes, but they use two different return representations. Results show that this metaheuristic can be effectively used to solve multi-criteria portfolio selection problems. Furthermore, with an experiment on a set of instances coming from a different financial scenario, we show that the results obtained by our metaheuristic are robust with respect to the return representation used.
In corso di stampa
6
File in questo prodotto:
File Dimensione Formato  
jaor060114_corrected_proof.pdf

Open Access dal 01/12/2015

Tipologia: Documento in Pre-print
Licenza: Accesso chiuso-personale
Dimensione 1.42 MB
Formato Adobe PDF
1.42 MB Adobe PDF Visualizza/Apri
10_ditollo_stuetzle_birattari.pdf

accesso aperto

Tipologia: Versione dell'editore
Licenza: Accesso gratuito (solo visione)
Dimensione 1.72 MB
Formato Adobe PDF
1.72 MB Adobe PDF Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/42255
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact