Alocação da indústria de fundo de fundos em fundos multimercados no Brasil

Detalhes bibliográficos
Autor(a) principal: Castro, Jonatas Porto de
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: http://hdl.handle.net/10438/18450
Resumo: This paper’s purpose is to explain the allocations made by fund of funds managers in third-party hedge funds, through a model using public information. Public data such as returns, net inflows, assets under management, ANBIMA classification, administration fee, and others were used as explanatory variables to explain the amount allocated in each hedge fund as a percentage of total AUM allocated in third-party hedge funds. After testing several models, the conclusion is that funds with good 24 months performance, managed by independent firms, with positive net flows in the last 12 months and with high volume of assets under management may have better odds of allocation from fund of fund managers. Thus, variables mentioned above are significant for the estimation of fund of funds allocations in third-party hedge funds. The paper leaves room for further Model developments in order to identify omitted variables. As the information used was the available public data, a second stage is enhancing the Model with qualitative data collected from face-to-face Due Diligences.
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spelling Castro, Jonatas Porto deEscolas::EESPSampaio, Joelson OliveiraAraujo, Michael ViriatoRochman, Ricardo Ratner2017-07-11T13:44:29Z2017-07-11T13:44:29Z2017-06-19CASTRO, Jonatas Porto de. Alocação da indústria de fundo de fundos em fundos multimercados no Brasil. Dissertação (Mestrado Profissional em Finanças e Economia) - FGV - Fundação Getúlio Vargas, São Paulo, 2017.http://hdl.handle.net/10438/18450This paper’s purpose is to explain the allocations made by fund of funds managers in third-party hedge funds, through a model using public information. Public data such as returns, net inflows, assets under management, ANBIMA classification, administration fee, and others were used as explanatory variables to explain the amount allocated in each hedge fund as a percentage of total AUM allocated in third-party hedge funds. After testing several models, the conclusion is that funds with good 24 months performance, managed by independent firms, with positive net flows in the last 12 months and with high volume of assets under management may have better odds of allocation from fund of fund managers. Thus, variables mentioned above are significant for the estimation of fund of funds allocations in third-party hedge funds. The paper leaves room for further Model developments in order to identify omitted variables. As the information used was the available public data, a second stage is enhancing the Model with qualitative data collected from face-to-face Due Diligences.O objetivo deste trabalho é explicar as motivações por trás das alocações feitas por gestores de fundos de fundos em veículos multimercados de terceiros através de um Modelo que utiliza dados disponíveis para o público em geral. Dados públicos como: retorno, captação, patrimônio, classificação ANBIMA, taxa de administração etc. foram usados como variáveis explicativas do Modelo e a variável a ser explicada é o valor alocado em cada fundo multimercado em percentual do total de recursos alocados em fundos multimercados de terceiros. Depois de testados diversos Modelos, a conclusão é que fundos com bom desempenho em 24 meses, geridos por empresas independentes, com captação positiva em 12 meses e patrimônio elevado, podem ter melhores chances de receber recursos oriundos de alocadores ou gestores de fundos de fundos, em outras palavras, as variáveis citadas acima são significativas na estimação de alocação de fundos de fundos em fundos multimercados. O trabalho deixa espaço para avanços no Modelo e identificação de variáveis omitidas. 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dc.title.por.fl_str_mv Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
title Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
spellingShingle Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
Castro, Jonatas Porto de
Due diligence
Fundos
Multimercados
Alocação
Carteira
Economia
Fundos de investimento
Investimentos de capital
Mercado de capitais
title_short Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
title_full Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
title_fullStr Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
title_full_unstemmed Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
title_sort Alocação da indústria de fundo de fundos em fundos multimercados no Brasil
author Castro, Jonatas Porto de
author_facet Castro, Jonatas Porto de
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EESP
dc.contributor.member.none.fl_str_mv Sampaio, Joelson Oliveira
Araujo, Michael Viriato
dc.contributor.author.fl_str_mv Castro, Jonatas Porto de
dc.contributor.advisor1.fl_str_mv Rochman, Ricardo Ratner
contributor_str_mv Rochman, Ricardo Ratner
dc.subject.eng.fl_str_mv Due diligence
topic Due diligence
Fundos
Multimercados
Alocação
Carteira
Economia
Fundos de investimento
Investimentos de capital
Mercado de capitais
dc.subject.por.fl_str_mv Fundos
Multimercados
Alocação
Carteira
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Fundos de investimento
Investimentos de capital
Mercado de capitais
description This paper’s purpose is to explain the allocations made by fund of funds managers in third-party hedge funds, through a model using public information. Public data such as returns, net inflows, assets under management, ANBIMA classification, administration fee, and others were used as explanatory variables to explain the amount allocated in each hedge fund as a percentage of total AUM allocated in third-party hedge funds. After testing several models, the conclusion is that funds with good 24 months performance, managed by independent firms, with positive net flows in the last 12 months and with high volume of assets under management may have better odds of allocation from fund of fund managers. Thus, variables mentioned above are significant for the estimation of fund of funds allocations in third-party hedge funds. The paper leaves room for further Model developments in order to identify omitted variables. As the information used was the available public data, a second stage is enhancing the Model with qualitative data collected from face-to-face Due Diligences.
publishDate 2017
dc.date.accessioned.fl_str_mv 2017-07-11T13:44:29Z
dc.date.available.fl_str_mv 2017-07-11T13:44:29Z
dc.date.issued.fl_str_mv 2017-06-19
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv CASTRO, Jonatas Porto de. Alocação da indústria de fundo de fundos em fundos multimercados no Brasil. Dissertação (Mestrado Profissional em Finanças e Economia) - FGV - Fundação Getúlio Vargas, São Paulo, 2017.
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/18450
identifier_str_mv CASTRO, Jonatas Porto de. Alocação da indústria de fundo de fundos em fundos multimercados no Brasil. Dissertação (Mestrado Profissional em Finanças e Economia) - FGV - Fundação Getúlio Vargas, São Paulo, 2017.
url http://hdl.handle.net/10438/18450
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dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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