6 resultados para information content

em Repositório digital da Fundação Getúlio Vargas - FGV


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O objetivo desse trabalho é avaliar a capacidade de previsão do mercado sobre a volatilidade futura a partir das informações obtidas nas opções de Petrobras e Vale, além de fazer uma comparação com modelos do tipo GARCH e EWMA. Estudos semelhantes foram realizados no mercado de ações americano: Seja com uma cesta de ações selecionadas ou com relação ao índice S&P 100, as conclusões foram diversas. Se Canina e Figlewski (1993) a “volatilidade implícita tem virtualmente nenhuma correlação com a volatilidade futura”, Christensen e Prabhala (1998) concluem que a volatilidade implícita é um bom preditor da volatilidade futura. No mercado brasileiro, Andrade e Tabak (2001) utilizam opções de dólar para estudar o conteúdo da informação no mercado de opções. Além disso, comparam o poder de previsão da volatilidade implícita com modelos de média móvel e do tipo GARCH. Os autores concluem que a volatilidade implícita é um estimador viesado da volatilidade futura mas de desempenho superior se comparada com modelos estatísticos. Gabe e Portugal (2003) comparam a volatilidade implícita das opções de Telemar (TNLP4) com modelos estatísticos do tipo GARCH. Nesse caso, volatilidade implícita tambem é um estimador viesado, mas os modelos estatísticos além de serem bons preditores, não apresentaram viés. Os dados desse trabalho foram obtidos ao longo de 2008 e início de 2009, optando-se por observações intradiárias das volatilidades implícitas das opções “no dinheiro” de Petrobrás e Vale dos dois primeiros vencimentos. A volatidade implícita observada no mercado para ambos os ativos contém informação relevante sobre a volatilidade futura, mas da mesma forma que em estudos anteriores, mostou-se viesada. No caso específico de Petrobrás, o modelo GARCH se mostrou um previsor eficiente da volatilidade futura

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We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

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We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

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We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We compare the performance of our index with other currently popular coincident indices of economic activity.

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In this paper we analyze the optimality of allowing firms to observe signals of workers’ characteristics in an optimal taxation framework. We show that it is always optimal to prohibit signals that disclose information about differences in the intrinsic productivities of workers like mandatory health exams and IQ tests, for example. On the other hand, it is never optimal to forbid signals that reveal information about the comparative advantages of workers like their specialization and profession. When signals are mixed (they disclose both types of information), there is a trade-off between efficiency and equity. It is optimal to prohibit signals with sufficiently low comparative advantage content.

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This thesis was written as part of a Double-Degree Masters program in Management, with focus in Marketing. Aligned with the nature of the degree, this study aims to be a useful tool for managers and marketers, which conduct business online. This thesis is a study of Content Marketing in the content of online commercial product pages. Its aim is to understand how to use content marketing to drive conversion, by understanding consumer attitudes and purchase intention towards content. A in-depth study of existing theories and exploratory primary research was developed in other to attain these objectives. Business-to-consumer electronic commerce (B2C e-commerce) has provided consumers and online retailers with a more effective medium to perform online transactions through commercial websites. Although consumers have realized that the benefits of online shopping; such as time saving, minimizing effort, convenience, broader selection, and wider access to information, they are still greatly unwilling to shop online. Consumers shop essentially for two motives, to meet experiential (fun) or goal-oriented (efficiency) needs (Wolfinbarger & Gilly, 2001). The information provided by content marketing seeks to focus on consumers need for information and entertainment, instead of focusing on the brand. Thus, it is expected that the type of content format will have different effects on the attitudes and purchase intention on the online shopper, depending on the online shopping purpose. Concretely, a goal-oriented shopper should find user generated content (UGC) to be more valuable content formats, since they decrease the amount of search effort. While on the other hand, videos & tutorials (VT) might be perceived as more valuable for a consumer looking to spend time and being entertained through online shopping. The exploratory research was characterized by a survey experiment with online consumers. Participants were exposed to stimuli of content marketing tested according to their attitudes and purchase intention. The focus was to understand the impact of two different content marketing tactics—User-generated content and Videos & Tutorials—on attitudes and purchase intentions and how they interact with content complexity. The results indicate that content marketing in commercial product pages is relevant in driving consumer attitudes and purchase intentions. Consumers are not motivated by a specific content marketing tactic, unless that content has a certain level of complexity. In that case, Ur-Generated Content becomes a relevant tactic in product pages, however VT is not.