Using irregularly spaced returns to estimate multi-factor models: application to Brazilian equity data

Multi-factor models constitute a useful tool to explain cross-sectional covariance in equities returns. We propose in this paper the use of irregularly spaced returns in the multi-factor model estimation and provide an empirical example with the 389 most liquid equities in the Brazilian Market. The market index shows itself significant to explain equity returns while the US$/Brazilian Real exchange rate and the Brazilian standard interest rate does not. This example shows the usefulness of the estimation method in further using the model to fill in missing values and to provide interval forecasts.

Using irregularly spaced returns to estimate multi-factor models : application to Brazilian equity data

Multi-factor models constitute a use fui tool to explain cross-sectional covariance in equities retums. We propose in this paper the use of irregularly spaced returns in the multi-factor model estimation and provide an empirical example with the 389 most liquid equities in the Brazilian Market. The market index shows itself significant to explain equity returns while the US$/Brazilian Real exchange rate and the Brazilian standard interest rate does not. This example shows the usefulness of the estimation method in further using the model to fill in missing values and to provide intervaI forecasts.

Estrutura a termo da taxa de juros no Brasil e previsibilidade de ciclos econômicos

O objetivo deste trabalho é caracterizar a Curva de Juros Mensal para o Brasil através de três fatores, comparando dois tipos de métodos de estimação: Através da Representação em Espaço de Estado é possível estimá-lo por dois Métodos: Filtro de Kalman e Mínimos Quadrados em Dois Passos. Os fatores têm sua dinâmica representada por um Modelo Autorregressivo Vetorial, VAR(1), e para o segundo método de estimação, atribui-se uma estrutura para a Variância Condicional. Para a comparação dos métodos empregados, propõe-se uma forma alternativa de compará-los: através de Processos de Markov que possam modelar conjuntamente o Fator de Inclinação da Curva de Juros, obtido pelos métodos empregados neste trabalho, e uma váriavel proxy para Desempenho Econômico, fornecendo alguma medida de previsão para os Ciclos Econômicos.

Hope, risk perception and propensity to indebtedness

Hope is an important construct in marketing, once it is an antecedent of important marketing variables, such as trust, expectation and satisfaction (MacInnis & de Mello, 2005, Almeida, Mazzon & Botelho, 2007). Specifically, the literature suggests that hope can play an important influence on risk perception (Almeida, 2010, Almeida et al., 2007, Fleming, 2008, MacInnis & de Mello, 2005) and propensity to indebtedness (Fleming, 2008). Thus, this thesis aims to investigate the relations among hope, risk perception related to purchasing and consumption and propensity to indebtedness, by reviewing the existing literature and conducting two empirical researches. The first of them is a laboratory experiment, which accessed hope and risk perception of getting a mortgage loan. The second is a survey, investigating university students’ propensity to get indebted to pay for their university tuition, analyzed through the method of Structural Equations Modeling (SEM). These studies found that hope seems to play an important role on propensity to indebtedness, as higher levels of hope predicted an increase in the propensity to accept the mortgage loan, independent of actual risks, and an increase in the propensity of college students to get indebted to pay for their studies. In addition, the first study suggests that hope may lead to a decrease in risk perception, which, however, has not been confirmed by the second study. Finally, this research offers some methodological contributions, due to the fact that it is the first study using an experimental method to study hope in Brazil and, worldwide, it is the first study investigating the relation among hope, risk perception and propensity to indebtedness, which proved to be important influences in consumer behavior

Estimation of DSGE Models: A Monte Carlo Analysis

Neste trabalho investigamos as propriedades em pequena amostra e a robustez das estimativas dos parâmetros de modelos DSGE. Tomamos o modelo de Smets and Wouters (2007) como base e avaliamos a performance de dois procedimentos de estimação: Método dos Momentos Simulados (MMS) e Máxima Verossimilhança (MV). Examinamos a distribuição empírica das estimativas dos parâmetros e sua implicação para as análises de impulso-resposta e decomposição de variância nos casos de especificação correta e má especificação. Nossos resultados apontam para um desempenho ruim de MMS e alguns padrões de viés nas análises de impulso-resposta e decomposição de variância com estimativas de MV nos casos de má especificação considerados.