A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS
Ano de defesa: | 2019 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
Centro de Ciências Sociais e Humanas |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Administração
|
Departamento: |
Administração
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/17462 |
Resumo: | CAPM (Capital Asset Pricing Model) is one of the most widespread models for the anticipated consumption of return on a risky investment. Developed by Sharpe (1964) and Lintner (1965), through Markowitz (1952), this model relates the expected return of an asset with its non-diversifiable risk. Despite being a simple and intuitive, it is based on several restrictive factors on the functioning of the market, and so it has been modified. In this sense, many papers have sought to include factors to the CAPM model. Nevertheless, the main objective of this work was to investigate if a new factor - idiosyncratic volatility - could be able to improve the explanation of the priceless returns. For this, the CAPM model of Fama & French was used, and based on works such as Ang et al. (2006) and Leite et al. (2016), the volatility factor was included. The difference of this work is the inclusion of portfolio volatility as well as the calculation of this one, that was obtained using univariate GARCH as well as the score classes models, specifically the GAS model. The study scope was the Brazilian capital market, between the period of 2007 and 2017, with a set of 6 portfolios according to the book-to-market criteria and size of the companies. It was defined to make use of three empirical models: CAPM Fama & French, CAPM with market volatility and CAPM with idiosyncratic volatility, and thus to compare their capacity and explanation. In addition, superior moments were included as systemic control factors of the models, as well as the ability to explain the volatility modeled by GARCH and GAS separately. The empirical results showed that the inclusion of volatility improves the explanation of the CAPM model Fama & French, fact evidenced by the sensible increase of adjusted R² of the regressions. Notwithstanding, it was noted that volatility, when significant, had an opposite relationship with return., the volatilities modeled by the GARCH had superior performance in 5 of the 6 proposed portfolios when compared when modeled by GAS. When compared, it was noted that idiosyncratic volatility explained more the returns than with the addition of market volatility, indicating that the information on the montage of portfolios and their oscillations of individual returns seem to be more important than the movement of the market as itself, a result that becomes relevant both for hedging and for the search for maximization of returns by investors. |
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2019-07-16T15:27:09Z2019-07-16T15:27:09Z2019-03-29http://repositorio.ufsm.br/handle/1/17462CAPM (Capital Asset Pricing Model) is one of the most widespread models for the anticipated consumption of return on a risky investment. Developed by Sharpe (1964) and Lintner (1965), through Markowitz (1952), this model relates the expected return of an asset with its non-diversifiable risk. Despite being a simple and intuitive, it is based on several restrictive factors on the functioning of the market, and so it has been modified. In this sense, many papers have sought to include factors to the CAPM model. Nevertheless, the main objective of this work was to investigate if a new factor - idiosyncratic volatility - could be able to improve the explanation of the priceless returns. For this, the CAPM model of Fama & French was used, and based on works such as Ang et al. (2006) and Leite et al. (2016), the volatility factor was included. The difference of this work is the inclusion of portfolio volatility as well as the calculation of this one, that was obtained using univariate GARCH as well as the score classes models, specifically the GAS model. The study scope was the Brazilian capital market, between the period of 2007 and 2017, with a set of 6 portfolios according to the book-to-market criteria and size of the companies. It was defined to make use of three empirical models: CAPM Fama & French, CAPM with market volatility and CAPM with idiosyncratic volatility, and thus to compare their capacity and explanation. In addition, superior moments were included as systemic control factors of the models, as well as the ability to explain the volatility modeled by GARCH and GAS separately. The empirical results showed that the inclusion of volatility improves the explanation of the CAPM model Fama & French, fact evidenced by the sensible increase of adjusted R² of the regressions. Notwithstanding, it was noted that volatility, when significant, had an opposite relationship with return., the volatilities modeled by the GARCH had superior performance in 5 of the 6 proposed portfolios when compared when modeled by GAS. When compared, it was noted that idiosyncratic volatility explained more the returns than with the addition of market volatility, indicating that the information on the montage of portfolios and their oscillations of individual returns seem to be more important than the movement of the market as itself, a result that becomes relevant both for hedging and for the search for maximization of returns by investors.O CAPM (Capital Asset Pricing Model) é um dos modelos mais difundidos para o cômputo esperado do retorno de um investimento em condições de risco. Desenvolvido por Sharpe (1964) e Lintner (1965), por meio das conclusões do trabalho de Markowitz (1952), esse modelo relaciona o retorno esperado de um ativo, com o seu risco não diversificável. Apesar de ser um modelo simples e intuitivo, o mesmo está fundamentado em fatores muito restritivos sobre o funcionamento do mercado, e por isso foi modificado. Nesse sentido, muitos trabalhos buscaram incluir fatores ao modelo CAPM. Com isso, o objetivo desse trabalho foi de investigar se um novo fator - a volatilidade idiossincrática - poderia ter capacidade de aprimorar a explicação dos retornos precificáveis. Para tal, fez-se uso do modelo CAPM de Fama & French e, baseado em trabalhos como os de Ang et al. (2006) e Leite et al. (2016), incluiu-se o fator volatilidade. A diferença desse trabalho está na inclusão da volatilidade da carteira bem como no cálculo dessa que foi obtida fazendo uso de modelos das classes GARCH univariadas e de score, especificamente o modelo GAS. O escopo de estudo foi o mercado brasileiro de capitais, entre o período de 2007 e 2017, com montagem de 6 carteiras pelos critérios book-to-market e tamanho das empresas. Optou-se por fazer de modelos três modelos empíricos: o CAPM Fama & French, o CAPM com a volatilidade de mercado e o CAPM com a volatilidade idiossincrática, e assim comparar sua capacidade e explicação. Além disso, foram incluídos momentos superiores como fatores sistêmicos de controle dos modelos, e também comparar a capacidade de explicação da volatilidade modelada pelo GARCH e pelo GAS separadamente. Os resultados empíricos mostraram que a inclusão da volatilidade aprimora a explicação do modelo CAPM Fama & French, fato evidenciado pelo sensível acréscimo do R² ajustado das regressões. Além disso, notou-se que a volatilidade, quando significativa, teve relação oposta com o retorno. Além disso, as volatilidades modeladas pelo GARCH tiveram desempenho superior em 5 das 6 carteiras propostas ao ser comparada quando modelada pelo GAS. Quando comparadas, notou-se que a volatilidade idiossincrática explicou mais os retornos do que com a adição da volatilidade de mercado, indicando que as informações da montagem de portfólios e suas oscilações de retornos individuais parecem ser mais importantes que o movimento do mercado como um todo, um resultado que se torna relevante tanto para hedge quanto para a busca de maximização de retornos pelos investidores.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de Ciências Sociais e HumanasPrograma de Pós-Graduação em AdministraçãoUFSMBrasilAdministraçãoAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessCAPMGARCHGASMontagem de portófliosPortfolio assemblyCNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAOA volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GASDoes idiosyncratic volatility improve the explanation of returnable prices? 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dc.title.por.fl_str_mv |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
dc.title.alternative.eng.fl_str_mv |
Does idiosyncratic volatility improve the explanation of returnable prices? GARCH and GAS models application |
title |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
spellingShingle |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS Conte, Bruno Pereira CAPM GARCH GAS Montagem de portóflios Portfolio assembly CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
title_short |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
title_full |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
title_fullStr |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
title_full_unstemmed |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
title_sort |
A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS |
author |
Conte, Bruno Pereira |
author_facet |
Conte, Bruno Pereira |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Ceretta, Paulo Sergio |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/3049029014914257 |
dc.contributor.referee1.fl_str_mv |
Denardin, Anderson Antonio |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/8520458665069378 |
dc.contributor.referee2.fl_str_mv |
Milani, Bruno |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/0005005751598450 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6967382475867011 |
dc.contributor.author.fl_str_mv |
Conte, Bruno Pereira |
contributor_str_mv |
Ceretta, Paulo Sergio Denardin, Anderson Antonio Milani, Bruno |
dc.subject.por.fl_str_mv |
CAPM GARCH GAS Montagem de portóflios |
topic |
CAPM GARCH GAS Montagem de portóflios Portfolio assembly CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
dc.subject.eng.fl_str_mv |
Portfolio assembly |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
description |
CAPM (Capital Asset Pricing Model) is one of the most widespread models for the anticipated consumption of return on a risky investment. Developed by Sharpe (1964) and Lintner (1965), through Markowitz (1952), this model relates the expected return of an asset with its non-diversifiable risk. Despite being a simple and intuitive, it is based on several restrictive factors on the functioning of the market, and so it has been modified. In this sense, many papers have sought to include factors to the CAPM model. Nevertheless, the main objective of this work was to investigate if a new factor - idiosyncratic volatility - could be able to improve the explanation of the priceless returns. For this, the CAPM model of Fama & French was used, and based on works such as Ang et al. (2006) and Leite et al. (2016), the volatility factor was included. The difference of this work is the inclusion of portfolio volatility as well as the calculation of this one, that was obtained using univariate GARCH as well as the score classes models, specifically the GAS model. The study scope was the Brazilian capital market, between the period of 2007 and 2017, with a set of 6 portfolios according to the book-to-market criteria and size of the companies. It was defined to make use of three empirical models: CAPM Fama & French, CAPM with market volatility and CAPM with idiosyncratic volatility, and thus to compare their capacity and explanation. In addition, superior moments were included as systemic control factors of the models, as well as the ability to explain the volatility modeled by GARCH and GAS separately. The empirical results showed that the inclusion of volatility improves the explanation of the CAPM model Fama & French, fact evidenced by the sensible increase of adjusted R² of the regressions. Notwithstanding, it was noted that volatility, when significant, had an opposite relationship with return., the volatilities modeled by the GARCH had superior performance in 5 of the 6 proposed portfolios when compared when modeled by GAS. When compared, it was noted that idiosyncratic volatility explained more the returns than with the addition of market volatility, indicating that the information on the montage of portfolios and their oscillations of individual returns seem to be more important than the movement of the market as itself, a result that becomes relevant both for hedging and for the search for maximization of returns by investors. |
publishDate |
2019 |
dc.date.accessioned.fl_str_mv |
2019-07-16T15:27:09Z |
dc.date.available.fl_str_mv |
2019-07-16T15:27:09Z |
dc.date.issued.fl_str_mv |
2019-03-29 |
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://repositorio.ufsm.br/handle/1/17462 |
url |
http://repositorio.ufsm.br/handle/1/17462 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.cnpq.fl_str_mv |
600200000006 |
dc.relation.confidence.fl_str_mv |
600 |
dc.relation.authority.fl_str_mv |
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dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Sociais e Humanas |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Administração |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Administração |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Sociais e Humanas |
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