Genetic algorithms applied to asset & liability management

Detalhes bibliográficos
Autor(a) principal: Almeida, João Filipe Clérigo Ribeiro de
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/26410
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
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spelling Genetic algorithms applied to asset & liability managementGenetic AlgorithmsEvolutionary AlgorithmsPension FundsLife InsuranceAsset Liability ManagementDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementEffective asset liability management is at the core of what a life insurance company must do, particularly in what concerns defined benefits pension fund products. The life insurer faces a complex problem whereby multiple and sometimes conflicting objectives must be addressed at the same time, such as achieving higher returns while reducing the portfolio’s exposure to a plethora of risks. To achieve these goals, pension fund managers must then carefully choose asset allocation strategies for their portfolios from an infinite pool of asset combinations and weights. Given the nature of this problem, the use of genetic algorithms seems to be adequate, as this method is particularly well suited to deal with very large and multi-modal solution spaces. The main purpose of this dissertation is to assess how well the genetic algorithm method performs in solving this specific problem, and compare the results with other simpler methods. The results of Genetic Algorithms application were satisfactory and the results of this study suggests that Genetic Algorithms are a useful tool to solve ALM problems.Castelli, MauroBravo, Jorge Miguel VenturaRUNAlmeida, João Filipe Clérigo Ribeiro de2017-12-06T18:24:22Z2017-11-032017-11-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/26410TID:201751402enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:13:52Zoai:run.unl.pt:10362/26410Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:28:28.921656Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Genetic algorithms applied to asset & liability management
title Genetic algorithms applied to asset & liability management
spellingShingle Genetic algorithms applied to asset & liability management
Almeida, João Filipe Clérigo Ribeiro de
Genetic Algorithms
Evolutionary Algorithms
Pension Funds
Life Insurance
Asset Liability Management
title_short Genetic algorithms applied to asset & liability management
title_full Genetic algorithms applied to asset & liability management
title_fullStr Genetic algorithms applied to asset & liability management
title_full_unstemmed Genetic algorithms applied to asset & liability management
title_sort Genetic algorithms applied to asset & liability management
author Almeida, João Filipe Clérigo Ribeiro de
author_facet Almeida, João Filipe Clérigo Ribeiro de
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
Bravo, Jorge Miguel Ventura
RUN
dc.contributor.author.fl_str_mv Almeida, João Filipe Clérigo Ribeiro de
dc.subject.por.fl_str_mv Genetic Algorithms
Evolutionary Algorithms
Pension Funds
Life Insurance
Asset Liability Management
topic Genetic Algorithms
Evolutionary Algorithms
Pension Funds
Life Insurance
Asset Liability Management
description Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
publishDate 2017
dc.date.none.fl_str_mv 2017-12-06T18:24:22Z
2017-11-03
2017-11-03T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/26410
TID:201751402
url http://hdl.handle.net/10362/26410
identifier_str_mv TID:201751402
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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