Solving realistic portfolio optimization problems via metaheuristics: a survey and an example

Jana Doering, Angel A. Juan, Renatas Kizys, Angels Fito, Laura Calvet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Computational finance has become one of the emerging application fields of metaheuristic algorithms. In particular, these optimization methods are quickly becoming the solving approach alternative when dealing with realistic versions of financial problems, such as the popular portfolio optimization problem (POP). This paper reviews the scientific literature on the use of metaheuristics for solving rich versions of the POP and illustrates, with a numerical example, the capacity of these methods to provide high-quality solutions to complex POPs in short computing times, which might be a desirable property of solving methods that support real-time decision making.
Original languageEnglish
Title of host publicationModeling and Simulation in Engineering, Economics and Management
Subtitle of host publicationInternational Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings
PublisherSpringer International Publishing
Pages22-30
Volume254
ISBN (Electronic)978-3-319-40506-3
ISBN (Print)978-3-319-40505-6
DOIs
Publication statusPublished - 26 Jun 2016
EventInternational Conference on Modeling and Simulation in Engineering, Economics and Management: MS 2016 - Teruel, Spain
Duration: 4 Jul 20165 Jul 2016
http://amsemodelling.com/conferences/teruel2016.html

Publication series

NameLecture Notes in Business Information Processing
Volume254
ISSN (Print)1865-1348

Conference

ConferenceInternational Conference on Modeling and Simulation in Engineering, Economics and Management
CountrySpain
CityTeruel
Period4/07/165/07/16
Internet address

Keywords

  • Portfolio optimization
  • SimILS
  • Metaheuristics
  • Simulation

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