A volatilidade idiossincrática melhora o desempenho dos retornos precificáveis? Aplicações dos modelos GARCH e GAS

• Ano de defesa: 2019
• Autor(a) principal: Conte, Bruno Pereira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Administração; UFSM; Programa de Pós-Graduação em Administração; Centro de Ciências Sociais e Humanas
• Palavras-chave em Português: CAPM; GARCH; GAS; Montagem de portóflios; Portfolio assembly; CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/17462

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.