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An examination of the cross-sectional relationship of beta and return in international stock returns: evidence from emerging and developed marketsSpierts, Joshua Patrick 16 January 2018 (has links)
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Please, correct just 2 things in your thesis:
Page 2: Please, put the full name of your adviser;
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Previous issue date: 2018-01-16 / This paper will follow Pettengill et al.’s (1995) approach to examine the unconditional and conditional relationship between beta and returns from January 1995 to May 2017 in a well globally diversified sample of 22 emerging markets and 23 developed markets. Additionally, Pettengill et al.’s (1995) methodology is adjusted to take into account 1-year time-varying beta values to supplement and check the robustness of the initial results. The empirical results for the full sample as well as both sub-samples indicate that there is no significant unconditional relationship between beta and returns, however, when differentiating between up- and down-markets a significant conditional relationship is found. This paper adds to the existing literature by examining and comparing a large sample of both developed and emerging markets, as well as, confirming the results according to Pettengill et al.’s methodology with timevarying betas. / Este artigo seguirá a abordagem de Pettengill et al. (1995) para examinar a relação incondicional e condicional entre beta e retornos de janeiro de 1995 a maio de 2017 em uma amostra globalmente diversificada de 22 mercados emergentes e 23 mercados desenvolvidos. Além disso, a metodologia de Pettengill et al. (1995) é ajustada para levar em conta valores beta de variação do tempo de 1 ano para complementar e verificar a robustez dos resultados iniciais. Os resultados empíricos para a amostra completa, bem como as duas sub-amostras, indicam que não existe uma relação incondicional significativa entre beta e retorno, no entanto, quando se diferencia entre os mercados ascendentes e descendentes, é encontrada uma relação condicional significativa. Este artigo acrescenta-se à literatura existente, examinando e comparando uma grande amostra de mercados desenvolvidos e emergentes, bem como, confirmando os resultados de acordo com a metodologia de Pettengill et al., Com betas variáveis no tempo.
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[en] FACTOR MODELS WITH TIME-VARYING BETAS / [pt] MODELOS DE FATORES COM BETAS VARIANTES NO TEMPOFRANCES FISCHBERG BLANK 12 May 2015 (has links)
[pt] Diversos estudos envolvendo modelos de fatores para apreçamento de ativos contestam a validade do CAPM. Ao longo do tempo, para explicar as chamadas anomalias dos retornos das ações, os trabalhos se voltaram tanto para a busca de novos fatores de risco – os modelos multifatores – bem como para o tratamento dinâmico das sensibilidades relacionadas aos fatores de risco – os modelos condicionais de apreçamento de ativos. Os modelos condicionais, de um ou mais fatores, explicitam o valor esperado do retorno de um ativo de forma condicional a um conjunto de informação disponível no período anterior. As sensibilidades aos fatores de risco, os betas, são estimados como parâmetros dinâmicos a partir de diferentes abordagens na literatura. Nesta tese, o objetivo é o estudo de modelos condicionais na forma espaço-estado, em que os betas seguem processos estocásticos e são estimados a partir do filtro de Kalman, de forma a verificar o ganho na capacidade explicativa dos modelos. Dois estudos empíricos são realizados, um para o CAPM condicional no mercado brasileiro e outro para o modelo de três fatores condicional de Fama e French no mercado norte-americano. De modo geral, os resultados ao se considerar a variação temporal das sensibilidades aos fatores são melhores do que os obtidos a partir dos modelos incondicionais correspondentes, tanto no que se refere ao ajuste aos dados quanto à redução proporcionada nos erros de apreçamento. / [en] The validity of CAPM is contested by several studies based on factor models. During the last decades, aiming to explain the known financial anomalies of stock returns, two major lines of research emerged: the use of asset pricing models that allow for multiple sources of risk – the multifactor models – as well as the dynamic approach to model the sensitivities of returns in respect to the risk factors – the conditional models. The conditional models, based on one or more risk factors, explicit the expected return conditional to the information set available in the previous period. The factor sensitivities, or the betas, are estimated as dynamic parameters according to different approaches in the literature. The main objective in this thesis is to study conditional pricing models based on state-space approach. The betas dynamics are described as stochastic processes and estimated through the Kalman filter in order to verify the models ability to explain the returns and related financial anomalies, such as size and value effects. Two empirical applications are presented: one for Conditional CAPM in the Brazilian stock market and another for Conditional Fama and French (1993) three-factor model in the American stock market. In both cases, time-varying sensitivities treatment provides better model adjustment as well as smaller pricing errors compared to correspondent unconditional models.
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