Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization
Ano de defesa: | 2016 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | eng |
Instituição de defesa: |
Não Informado pela instituição
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Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
|
Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/10438/17044 |
Resumo: | Multi-Period Stochastic Programming (MSP) offers an appealing approach to identity optimal portfolios, particularly over longer investment horizons, because it is inherently suited to handle uncertainty. Moreover, it provides flexibility to accommodate coherent risk measures, market frictions, and most importantly, major stylized facts as volatility clustering, heavy tails, leverage effects and tail co-dependence. However, to achieve satisfactory results a MSP model relies on representative and arbitrage-free scenarios of the pertaining multivariate financial series. Only after we have constructed such scenarios, we can exploit it using suitable risk measures to achieve robust portfolio allocations. In this thesis, we discuss a comprehensive framework to accomplish that. First, we construct joint scenarios based on a combined GJR-GARCH + EVT-GPD + t-Copula approach. Then, we reduce the original scenario tree and remove arbitrage opportunities using a method based on Optimal Discretization and Process Distances. Lastly, using the approximated scenario tree we perform a multi-period Mean-Variance-CVaR optimization taking into account market frictions such as transaction costs and regulatory restrictions. The proposed framework is particularly valuable to real applications because it handles various key features of real markets that are often dismissed by more common optimization approaches. |
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Chagas, Guido Marcelo BormaEscolas::EESPFernandes, MarceloPinto, Afonso de CamposHotta, Luiz KoodiLaurini, Márcio PolettiPereira, Pedro L. Valls2016-09-09T17:21:47Z2016-09-09T17:21:47Z2016-08-19CHAGAS, Guido Marcelo Borma. Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization. Tese (Doutorado em Economia de Empresas) - FGV - Fundação Getúlio Vargas, São Paulo, 2016.http://hdl.handle.net/10438/17044Multi-Period Stochastic Programming (MSP) offers an appealing approach to identity optimal portfolios, particularly over longer investment horizons, because it is inherently suited to handle uncertainty. Moreover, it provides flexibility to accommodate coherent risk measures, market frictions, and most importantly, major stylized facts as volatility clustering, heavy tails, leverage effects and tail co-dependence. However, to achieve satisfactory results a MSP model relies on representative and arbitrage-free scenarios of the pertaining multivariate financial series. Only after we have constructed such scenarios, we can exploit it using suitable risk measures to achieve robust portfolio allocations. In this thesis, we discuss a comprehensive framework to accomplish that. First, we construct joint scenarios based on a combined GJR-GARCH + EVT-GPD + t-Copula approach. Then, we reduce the original scenario tree and remove arbitrage opportunities using a method based on Optimal Discretization and Process Distances. Lastly, using the approximated scenario tree we perform a multi-period Mean-Variance-CVaR optimization taking into account market frictions such as transaction costs and regulatory restrictions. The proposed framework is particularly valuable to real applications because it handles various key features of real markets that are often dismissed by more common optimization approaches.Programação Estocástica Multi-Período (MSP) oferece uma abordagem conveniente para identificar carteiras ótimas, particularmente para horizontes de investimento mais longos, pois incorpora adequadamente a incerteza no processo de otimização. Adicionalmente, ela proporciona flexibilidade para acomodar medidas coerentes de risco, fricções de mercado e fatos estilizados relevantes como agrupamento de volatilidade, caudas pesadas, efeitos de alavancagem e co-dependência nas caudas. No entanto, para alcançar resultados satisfatórios, um modelo MSP depende de cenários representativos e livres de arbitragem. Somente após construídos esses cenários, podemos explorá-los usando medidas de risco adequadas para alcançar alocações ótimas. Nessa tese, discutimos uma metodologia completa para alcançar esse objetivo. Em primeiro lugar, construímos cenários conjuntos baseados numa abordagem conjunta GJR-GARCH + EVT-GPD + t-Copula. Posteriormente, reduzimos a árvore original de cenários e removemos oportunidades de arbitragem utilizando um método de discretização ótima baseado nas distâncias de processos estocásticos. Por último, usando a árvore aproximada de cenários, realizamos uma otimização multi-período de média-variância-CVaR considerando fricções de mercado, custos de transação e restrições regulamentares. A metodologia proposta é particularmente útil para aplicações reais, porque considera várias características relevantes dos mercados reais que muitas vezes são ignorados por abordagens mais simples de otimização.engAlocação de ativos multi-períodoGeração e aproximação de árvores de cenáriosDiscretização ótimaOtimização de média-variância-CVaREconomiaMercado financeiroProgramação estocásticaAlocação de ativosModelos econométricosLong-term asset allocation based on stochastic multistage multi-objective portfolio optimizationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessTEXTLong-Term Asset Allocation Based on Stochastic Multistage Multi-Objective Portfolio Optimization.pdf.txtLong-Term Asset Allocation Based on Stochastic Multistage Multi-Objective Portfolio Optimization.pdf.txtExtracted 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|
dc.title.por.fl_str_mv |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
title |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
spellingShingle |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization Chagas, Guido Marcelo Borma Alocação de ativos multi-período Geração e aproximação de árvores de cenários Discretização ótima Otimização de média-variância-CVaR Economia Mercado financeiro Programação estocástica Alocação de ativos Modelos econométricos |
title_short |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
title_full |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
title_fullStr |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
title_full_unstemmed |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
title_sort |
Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization |
author |
Chagas, Guido Marcelo Borma |
author_facet |
Chagas, Guido Marcelo Borma |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EESP |
dc.contributor.member.none.fl_str_mv |
Fernandes, Marcelo Pinto, Afonso de Campos Hotta, Luiz Koodi Laurini, Márcio Poletti |
dc.contributor.author.fl_str_mv |
Chagas, Guido Marcelo Borma |
dc.contributor.advisor1.fl_str_mv |
Pereira, Pedro L. Valls |
contributor_str_mv |
Pereira, Pedro L. Valls |
dc.subject.por.fl_str_mv |
Alocação de ativos multi-período Geração e aproximação de árvores de cenários Discretização ótima Otimização de média-variância-CVaR |
topic |
Alocação de ativos multi-período Geração e aproximação de árvores de cenários Discretização ótima Otimização de média-variância-CVaR Economia Mercado financeiro Programação estocástica Alocação de ativos Modelos econométricos |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Mercado financeiro Programação estocástica Alocação de ativos Modelos econométricos |
description |
Multi-Period Stochastic Programming (MSP) offers an appealing approach to identity optimal portfolios, particularly over longer investment horizons, because it is inherently suited to handle uncertainty. Moreover, it provides flexibility to accommodate coherent risk measures, market frictions, and most importantly, major stylized facts as volatility clustering, heavy tails, leverage effects and tail co-dependence. However, to achieve satisfactory results a MSP model relies on representative and arbitrage-free scenarios of the pertaining multivariate financial series. Only after we have constructed such scenarios, we can exploit it using suitable risk measures to achieve robust portfolio allocations. In this thesis, we discuss a comprehensive framework to accomplish that. First, we construct joint scenarios based on a combined GJR-GARCH + EVT-GPD + t-Copula approach. Then, we reduce the original scenario tree and remove arbitrage opportunities using a method based on Optimal Discretization and Process Distances. Lastly, using the approximated scenario tree we perform a multi-period Mean-Variance-CVaR optimization taking into account market frictions such as transaction costs and regulatory restrictions. The proposed framework is particularly valuable to real applications because it handles various key features of real markets that are often dismissed by more common optimization approaches. |
publishDate |
2016 |
dc.date.accessioned.fl_str_mv |
2016-09-09T17:21:47Z |
dc.date.available.fl_str_mv |
2016-09-09T17:21:47Z |
dc.date.issued.fl_str_mv |
2016-08-19 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
CHAGAS, Guido Marcelo Borma. Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization. Tese (Doutorado em Economia de Empresas) - FGV - Fundação Getúlio Vargas, São Paulo, 2016. |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10438/17044 |
identifier_str_mv |
CHAGAS, Guido Marcelo Borma. Long-term asset allocation based on stochastic multistage multi-objective portfolio optimization. Tese (Doutorado em Economia de Empresas) - FGV - Fundação Getúlio Vargas, São Paulo, 2016. |
url |
http://hdl.handle.net/10438/17044 |
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.source.none.fl_str_mv |
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Fundação Getulio Vargas (FGV) |
instacron_str |
FGV |
institution |
FGV |
reponame_str |
Repositório Institucional do FGV (FGV Repositório Digital) |
collection |
Repositório Institucional do FGV (FGV Repositório Digital) |
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bitstream.checksum.fl_str_mv |
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MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV) |
repository.mail.fl_str_mv |
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