A survey on financial applications of metaheuristics

Modern heuristics or metaheuristics are optimization algorithms that have been increasingly used during the last decades to support complex decision-making in a number of fields, such as logistics and transportation, telecommunication networks, bioinformatics, finance, and the like. The continuous i...

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Detalles Bibliográficos
Autores: Soler Dominguez, Amparo, Juan, Angel A., Kizys, Renatas
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Institución:Universitat Oberta de Catalunya (UOC)
Repositorio:O2, repositorio institucional de la UOC
OAI Identifier:oai:openaccess.uoc.edu:10609/93081
Acceso en línea:http://hdl.handle.net/10609/93081
Access Level:acceso abierto
Palabra clave:metaheuristics
finance
combinatorial optimization
metaheurística
finances
optimització combinatòria
finanzas
optimización combinatoria
Heuristic
Heurística
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spelling A survey on financial applications of metaheuristicsSoler Dominguez, AmparoJuan, Angel A.Kizys, Renatasmetaheuristicsfinancecombinatorial optimizationmetaheurísticafinancesoptimització combinatòriametaheurísticafinanzasoptimización combinatoriaHeuristicHeurísticaHeurísticaModern heuristics or metaheuristics are optimization algorithms that have been increasingly used during the last decades to support complex decision-making in a number of fields, such as logistics and transportation, telecommunication networks, bioinformatics, finance, and the like. The continuous increase in computing power, together with advancements in metaheuristics frameworks and parallelization strategies, are empowering these types of algorithms as one of the best alternatives to solve rich and real-life combinatorial optimization problems that arise in a number of financial and banking activities. This article reviews some of the works related to the use of metaheuristics in solving both classical and emergent problems in the finance arena. A non-exhaustive list of examples includes rich portfolio optimization, index tracking, enhanced indexation, credit risk, stock investments, financial project scheduling, option pricing, feature selection, bankruptcy and financial distress prediction, and credit risk assessment. This article also discusses some open opportunities for researchers in the field, and forecast the evolution of metaheuristics to include real-life uncertainty conditions into the optimization problems being considered.ACM Computing SurveysUniversitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)University of PortsmouthUniversitat Jaume I201920192017info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttp://hdl.handle.net/10609/93081reponame:O2, repositorio institucional de la UOCinstname:Universitat Oberta de Catalunya (UOC)InglésACM Computing Surveys, 2017, 50(1)https://doi.org/10.1145/3054133CC BYhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:openaccess.uoc.edu:10609/930812026-05-28T12:42:01Z
dc.title.none.fl_str_mv A survey on financial applications of metaheuristics
title A survey on financial applications of metaheuristics
spellingShingle A survey on financial applications of metaheuristics
Soler Dominguez, Amparo
metaheuristics
finance
combinatorial optimization
metaheurística
finances
optimització combinatòria
metaheurística
finanzas
optimización combinatoria
Heuristic
Heurística
Heurística
title_short A survey on financial applications of metaheuristics
title_full A survey on financial applications of metaheuristics
title_fullStr A survey on financial applications of metaheuristics
title_full_unstemmed A survey on financial applications of metaheuristics
title_sort A survey on financial applications of metaheuristics
dc.creator.none.fl_str_mv Soler Dominguez, Amparo
Juan, Angel A.
Kizys, Renatas
author Soler Dominguez, Amparo
author_facet Soler Dominguez, Amparo
Juan, Angel A.
Kizys, Renatas
author_role author
author2 Juan, Angel A.
Kizys, Renatas
author2_role author
author
dc.contributor.none.fl_str_mv Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
University of Portsmouth
Universitat Jaume I
dc.subject.none.fl_str_mv metaheuristics
finance
combinatorial optimization
metaheurística
finances
optimització combinatòria
metaheurística
finanzas
optimización combinatoria
Heuristic
Heurística
Heurística
topic metaheuristics
finance
combinatorial optimization
metaheurística
finances
optimització combinatòria
metaheurística
finanzas
optimización combinatoria
Heuristic
Heurística
Heurística
description Modern heuristics or metaheuristics are optimization algorithms that have been increasingly used during the last decades to support complex decision-making in a number of fields, such as logistics and transportation, telecommunication networks, bioinformatics, finance, and the like. The continuous increase in computing power, together with advancements in metaheuristics frameworks and parallelization strategies, are empowering these types of algorithms as one of the best alternatives to solve rich and real-life combinatorial optimization problems that arise in a number of financial and banking activities. This article reviews some of the works related to the use of metaheuristics in solving both classical and emergent problems in the finance arena. A non-exhaustive list of examples includes rich portfolio optimization, index tracking, enhanced indexation, credit risk, stock investments, financial project scheduling, option pricing, feature selection, bankruptcy and financial distress prediction, and credit risk assessment. This article also discusses some open opportunities for researchers in the field, and forecast the evolution of metaheuristics to include real-life uncertainty conditions into the optimization problems being considered.
publishDate 2017
dc.date.none.fl_str_mv 2017
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10609/93081
url http://hdl.handle.net/10609/93081
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv ACM Computing Surveys, 2017, 50(1)
https://doi.org/10.1145/3054133
dc.rights.none.fl_str_mv CC BY
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv CC BY
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv ACM Computing Surveys
publisher.none.fl_str_mv ACM Computing Surveys
dc.source.none.fl_str_mv reponame:O2, repositorio institucional de la UOC
instname:Universitat Oberta de Catalunya (UOC)
instname_str Universitat Oberta de Catalunya (UOC)
reponame_str O2, repositorio institucional de la UOC
collection O2, repositorio institucional de la UOC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300724

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