Análise de portfólio: uma perspectiva bayesiana
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | https://hdl.handle.net/10438/16637 |
Resumo: | This work has the objective to address the problem of asset allocation (portfolio analysis) under a Bayesian perspective. For this it was necessary to review all the theoretical analysis of the classical mean-variance model and following identify their deficiencies that compromise its effectiveness in real cases. Interestingly, its biggest deficiency this not related to the model itself, but by its input data in particular the expected return calculated on historical data. To overcome this deficiency the Bayesian approach (Black-Litterman model) treat the expected return as a random variable and after that builds a priori distribution (based on the CAPM model) and a likelihood distribution (based on market investor’s views) to finally apply Bayes theorem resulting in the posterior distribution. The expected value of the return of this posteriori distribution is to replace the estimated expected return calculated on historical data. The results showed that the Bayesian model presents conservative and intuitive results in relation to the classical model of mean-variance. |
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Tito, Edison Americo HuarsayaEscolas::EPGEFGVSantos, Rafael ChavesMartins, Bruno SilvaGonçalves, Edson Daniel Lopes2016-06-29T12:06:48Z2016-06-29T12:06:48Z2016-06-03TITO, Edison Americo Huarsaya. Análise de portfólio: uma perspectiva bayesiana. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2016.https://hdl.handle.net/10438/16637This work has the objective to address the problem of asset allocation (portfolio analysis) under a Bayesian perspective. For this it was necessary to review all the theoretical analysis of the classical mean-variance model and following identify their deficiencies that compromise its effectiveness in real cases. Interestingly, its biggest deficiency this not related to the model itself, but by its input data in particular the expected return calculated on historical data. To overcome this deficiency the Bayesian approach (Black-Litterman model) treat the expected return as a random variable and after that builds a priori distribution (based on the CAPM model) and a likelihood distribution (based on market investor’s views) to finally apply Bayes theorem resulting in the posterior distribution. The expected value of the return of this posteriori distribution is to replace the estimated expected return calculated on historical data. The results showed that the Bayesian model presents conservative and intuitive results in relation to the classical model of mean-variance.Este trabalho tem com objetivo abordar o problema de alocação de ativos (análise de portfólio) sob uma ótica Bayesiana. Para isto foi necessário revisar toda a análise teórica do modelo clássico de média-variância e na sequencia identificar suas deficiências que comprometem sua eficácia em casos reais. Curiosamente, sua maior deficiência não esta relacionado com o próprio modelo e sim pelos seus dados de entrada em especial ao retorno esperado calculado com dados históricos. Para superar esta deficiência a abordagem Bayesiana (modelo de Black-Litterman) trata o retorno esperado como uma variável aleatória e na sequência constrói uma distribuição a priori (baseado no modelo de CAPM) e uma distribuição de verossimilhança (baseado na visão de mercado sob a ótica do investidor) para finalmente aplicar o teorema de Bayes tendo como resultado a distribuição a posteriori. O novo valor esperado do retorno, que emerge da distribuição a posteriori, é que substituirá a estimativa anterior do retorno esperado calculado com dados históricos. Os resultados obtidos mostraram que o modelo Bayesiano apresenta resultados conservadores e intuitivos em relação ao modelo clássico de média-variância.porModern portfolio theoryBayesian statiticsBlack-Litterman modelCAPMTeoria moderna de portfólioEstatística bayesianaModelo Black-LittermanEconomiaInvestimentos - AnáliseTeoria bayesiana de decisão estatísticaAnálise estocásticaAlocação de ativosAvaliação de ativos – Modelo (CAPM)Análise de portfólio: uma perspectiva bayesianainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINALEdisonMscFGV(20160619).pdfEdisonMscFGV(20160619).pdfPDFapplication/pdf2366030https://repositorio.fgv.br/bitstreams/f80d2e72-8324-47c6-a29d-ea2e346714b7/download231be2cde1e7f8e01331fddff3f227a1MD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv |
Análise de portfólio: uma perspectiva bayesiana |
title |
Análise de portfólio: uma perspectiva bayesiana |
spellingShingle |
Análise de portfólio: uma perspectiva bayesiana Tito, Edison Americo Huarsaya Modern portfolio theory Bayesian statitics Black-Litterman model CAPM Teoria moderna de portfólio Estatística bayesiana Modelo Black-Litterman Economia Investimentos - Análise Teoria bayesiana de decisão estatística Análise estocástica Alocação de ativos Avaliação de ativos – Modelo (CAPM) |
title_short |
Análise de portfólio: uma perspectiva bayesiana |
title_full |
Análise de portfólio: uma perspectiva bayesiana |
title_fullStr |
Análise de portfólio: uma perspectiva bayesiana |
title_full_unstemmed |
Análise de portfólio: uma perspectiva bayesiana |
title_sort |
Análise de portfólio: uma perspectiva bayesiana |
author |
Tito, Edison Americo Huarsaya |
author_facet |
Tito, Edison Americo Huarsaya |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EPGE |
dc.contributor.affiliation.none.fl_str_mv |
FGV |
dc.contributor.member.none.fl_str_mv |
Santos, Rafael Chaves Martins, Bruno Silva |
dc.contributor.author.fl_str_mv |
Tito, Edison Americo Huarsaya |
dc.contributor.advisor1.fl_str_mv |
Gonçalves, Edson Daniel Lopes |
contributor_str_mv |
Gonçalves, Edson Daniel Lopes |
dc.subject.eng.fl_str_mv |
Modern portfolio theory Bayesian statitics Black-Litterman model CAPM |
topic |
Modern portfolio theory Bayesian statitics Black-Litterman model CAPM Teoria moderna de portfólio Estatística bayesiana Modelo Black-Litterman Economia Investimentos - Análise Teoria bayesiana de decisão estatística Análise estocástica Alocação de ativos Avaliação de ativos – Modelo (CAPM) |
dc.subject.por.fl_str_mv |
Teoria moderna de portfólio Estatística bayesiana Modelo Black-Litterman |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Investimentos - Análise Teoria bayesiana de decisão estatística Análise estocástica Alocação de ativos Avaliação de ativos – Modelo (CAPM) |
description |
This work has the objective to address the problem of asset allocation (portfolio analysis) under a Bayesian perspective. For this it was necessary to review all the theoretical analysis of the classical mean-variance model and following identify their deficiencies that compromise its effectiveness in real cases. Interestingly, its biggest deficiency this not related to the model itself, but by its input data in particular the expected return calculated on historical data. To overcome this deficiency the Bayesian approach (Black-Litterman model) treat the expected return as a random variable and after that builds a priori distribution (based on the CAPM model) and a likelihood distribution (based on market investor’s views) to finally apply Bayes theorem resulting in the posterior distribution. The expected value of the return of this posteriori distribution is to replace the estimated expected return calculated on historical data. The results showed that the Bayesian model presents conservative and intuitive results in relation to the classical model of mean-variance. |
publishDate |
2016 |
dc.date.accessioned.fl_str_mv |
2016-06-29T12:06:48Z |
dc.date.available.fl_str_mv |
2016-06-29T12:06:48Z |
dc.date.issued.fl_str_mv |
2016-06-03 |
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.citation.fl_str_mv |
TITO, Edison Americo Huarsaya. Análise de portfólio: uma perspectiva bayesiana. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2016. |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10438/16637 |
identifier_str_mv |
TITO, Edison Americo Huarsaya. Análise de portfólio: uma perspectiva bayesiana. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2016. |
url |
https://hdl.handle.net/10438/16637 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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) instname:Fundação Getulio Vargas (FGV) instacron:FGV |
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Fundação Getulio Vargas (FGV) |
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FGV |
institution |
FGV |
reponame_str |
Repositório Institucional do FGV (FGV Repositório Digital) |
collection |
Repositório Institucional do FGV (FGV Repositório Digital) |
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https://repositorio.fgv.br/bitstreams/f80d2e72-8324-47c6-a29d-ea2e346714b7/download https://repositorio.fgv.br/bitstreams/3e4afdaa-0960-4e76-bceb-72dbbbc143dc/download https://repositorio.fgv.br/bitstreams/64044a54-c5dc-4176-83e0-3375091954a9/download https://repositorio.fgv.br/bitstreams/0af55016-b438-4952-8812-b0fcab8b79e6/download |
bitstream.checksum.fl_str_mv |
231be2cde1e7f8e01331fddff3f227a1 dfb340242cced38a6cca06c627998fa1 4e5be064fa34b31d854763b40ff91599 d211e7cb9af97d6d962c17034d3afd2a |
bitstream.checksumAlgorithm.fl_str_mv |
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 |
|
_version_ |
1813797710028865536 |