Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Lee, Ho Don
Orientador(a): Chela, João Luiz, Marques, Alessandro Martim
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Link de acesso: https://hdl.handle.net/10438/28006
Resumo: Exponential growth of the complexity in the financial market requires more and more the use of computational quantitative approach in any products or services that investment banks offer, not only in the portfolio management. However, despite the huge improvement of the computational power up to date, the investment banks’ trading desks do not fully integrate the optimization process, still using primitive methods such as the manual calculation. The main reason is that the classical optimization process, originally proposed by Harry Markowitz in 1952 is very sensitive to the estimation error of inputs making the model limited to the real world application. Moreover, the classical model does not consider the stochastic characteristics of the real world. This work has two main proposes. The first, build and implement the robust quantitative investment framework and the second, modify and adapt a more robust model to the real world investment bank’s trading desk. We use the Black-Litterman model and the robust optimization process to accomplish the objective that may help to maximize the economic gain of the institution.
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spelling Lee, Ho DonEscolas::EESPRibeiro, Celma de OliveiraChela, João LuizMarques, Alessandro Martim2019-09-09T13:56:43Z2019-09-09T13:56:43Z2019-08-14https://hdl.handle.net/10438/28006Exponential growth of the complexity in the financial market requires more and more the use of computational quantitative approach in any products or services that investment banks offer, not only in the portfolio management. However, despite the huge improvement of the computational power up to date, the investment banks’ trading desks do not fully integrate the optimization process, still using primitive methods such as the manual calculation. The main reason is that the classical optimization process, originally proposed by Harry Markowitz in 1952 is very sensitive to the estimation error of inputs making the model limited to the real world application. Moreover, the classical model does not consider the stochastic characteristics of the real world. This work has two main proposes. The first, build and implement the robust quantitative investment framework and the second, modify and adapt a more robust model to the real world investment bank’s trading desk. We use the Black-Litterman model and the robust optimization process to accomplish the objective that may help to maximize the economic gain of the institution.O crescimento exponencial na complexidade do mecado financeiro exige o uso de abordagens quantitativas computacionais em qualquer produto ou serviço que um banco de investimento oferece, não somente no gerenciamento de portfolio. No entanto, apesar de um grande avanço computational, mesas de trading dos bancos de investimentos não incorporaram o processo de otimização completamente ao seu trabalho, ainda utilizando os métodos primitivos como cálculo manual. A razão principal é de que o processo de otimização clássico proposto pelo Henry Markowitz em 1952 é muito sensível aos erros de estimação de inputs fazendo com que a sua aplicação ao mundo real seja limitada. Além disso, o modelo clássico não considera a caraterística estocástica do mundo real. O trabalho possui dois propostas. A primeira, construir e implementar a estrutura de investmento quantitativo e robusto e a segunda, modificar e adaptar um modelo mais robusto para a mesa de trading de um banco de investimento no mundo real. Nós usamos o modelo de Black-Litterman e o processo de otimização robusta para realizar o objetivo que pode ajudar a maximizar o ganho econômico da instituição.engRobust optimizationBlack-litterman modelInvestment bankDelta-One trading deskP&L maximizationOtimização robustaModelo de Black-littermanBanco de investimentoMesa de trading Delta-OneMaximização de P&LEconomiaOtimização matemáticaModelos matemáticosBancos de investimentoInvestimentos - AnáliseInnovative approach for the equity trading desk management process with the black-litterman model and the robust optimizationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas 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dc.title.eng.fl_str_mv Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
title Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
spellingShingle Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
Lee, Ho Don
Robust optimization
Black-litterman model
Investment bank
Delta-One trading desk
P&L maximization
Otimização robusta
Modelo de Black-litterman
Banco de investimento
Mesa de trading Delta-One
Maximização de P&L
Economia
Otimização matemática
Modelos matemáticos
Bancos de investimento
Investimentos - Análise
title_short Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
title_full Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
title_fullStr Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
title_full_unstemmed Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
title_sort Innovative approach for the equity trading desk management process with the black-litterman model and the robust optimization
author Lee, Ho Don
author_facet Lee, Ho Don
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EESP
dc.contributor.member.none.fl_str_mv Ribeiro, Celma de Oliveira
dc.contributor.author.fl_str_mv Lee, Ho Don
dc.contributor.advisor1.fl_str_mv Chela, João Luiz
Marques, Alessandro Martim
contributor_str_mv Chela, João Luiz
Marques, Alessandro Martim
dc.subject.eng.fl_str_mv Robust optimization
Black-litterman model
Investment bank
Delta-One trading desk
P&L maximization
topic Robust optimization
Black-litterman model
Investment bank
Delta-One trading desk
P&L maximization
Otimização robusta
Modelo de Black-litterman
Banco de investimento
Mesa de trading Delta-One
Maximização de P&L
Economia
Otimização matemática
Modelos matemáticos
Bancos de investimento
Investimentos - Análise
dc.subject.por.fl_str_mv Otimização robusta
Modelo de Black-litterman
Banco de investimento
Mesa de trading Delta-One
Maximização de P&L
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Otimização matemática
Modelos matemáticos
Bancos de investimento
Investimentos - Análise
description Exponential growth of the complexity in the financial market requires more and more the use of computational quantitative approach in any products or services that investment banks offer, not only in the portfolio management. However, despite the huge improvement of the computational power up to date, the investment banks’ trading desks do not fully integrate the optimization process, still using primitive methods such as the manual calculation. The main reason is that the classical optimization process, originally proposed by Harry Markowitz in 1952 is very sensitive to the estimation error of inputs making the model limited to the real world application. Moreover, the classical model does not consider the stochastic characteristics of the real world. This work has two main proposes. The first, build and implement the robust quantitative investment framework and the second, modify and adapt a more robust model to the real world investment bank’s trading desk. We use the Black-Litterman model and the robust optimization process to accomplish the objective that may help to maximize the economic gain of the institution.
publishDate 2019
dc.date.accessioned.fl_str_mv 2019-09-09T13:56:43Z
dc.date.available.fl_str_mv 2019-09-09T13:56:43Z
dc.date.issued.fl_str_mv 2019-08-14
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 https://hdl.handle.net/10438/28006
url https://hdl.handle.net/10438/28006
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 reponame:Repositório Institucional do FGV (FGV Repositório Digital)
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institution FGV
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