[pt] O mercado internacional tem sido o foco principal do estudo do convenience yield dos contratos de commodities agrícolas. Em geral, abordagens por meio de modelos de equilíbrio vêm sendo utilizadas para modelar o convenience yield. Esta dissertação propõe de forma pioneira, utilizar modelos de fatores, originalmente propostos por Nelson e Siegel (1987) para a taxa de juros, com o intuito de modelar uma proxy do convenience yield dos contratos futuros de boi gordo negociados na BMEF-Bovespa. Este trabalho também apresenta uma síntese dos modelos propostos na literatura para ativos financeiros e agropecuários bem como a estrutura de negociação dos contratos futuros de commodities agrícolas na BMEF. / [en] International Market has been the principal focus on the convenience yield study of the agricultural commodities contracts. In general, approaches using equilibrium models have been used to model the convenience yield. This paper proposes, for the first, using factor models, originally proposed by Nelson and Siegel (1987) for the in- terest rate, in order to model the a proxy of convenience yield of live cattle futures contracts traded on the Bovespa-BMEF. This work also presents a summary of the models proposed in the literature for financial assets and commodities as well as the structure of futures trading in agricultural commodities for BMEF.

<p>Bayesian nonparametric methods are useful for modeling data without having to define the complexity of the entire model <italic>a priori</italic>, but rather allowing for this complexity to be determined by the data. Two problems considered in this dissertation are the number of components in a mixture model, and the number of factors in a latent factor model, for which the Dirichlet process and the beta process are the two respective Bayesian nonparametric priors selected for handling these issues.</p> <p>The flexibility of Bayesian nonparametric priors arises from the prior's definition over an infinite dimensional parameter space. Therefore, there are theoretically an <italic>infinite</italic> number of latent components and an <italic>infinite</italic> number of latent factors. Nevertheless, draws from each respective prior will produce only a small number of components or factors that appear in a given data set. As mentioned, the number of these components and factors, and their corresponding parameter values, are left for the data to decide.</p> <p>This dissertation is split between novel practical applications and novel theoretical results for these priors. For the Dirichlet process, we investigate stick-breaking representations for the finite Dirichlet process and their application to novel sampling techniques, as well as a novel mixture modeling framework that incorporates multiple modalities within a data set. For the beta process, we present a new stick-breaking construction for the infinite-dimensional prior, and consider applications to image interpolation problems and dictionary learning for compressive sensing.</p> / Dissertation

This dissertation contains three applications of time series in finance and macroeconomics. The first essay compares the cumulative returns for stocks and bonds at investment horizons from one to ten years by using a test for spatial dominance. Spatial dominance is a variation of stochastic dominance for nonstationary variables. The results suggest that for investment horizons of one year, bonds spatially dominate stocks. In contrast, for investment horizons longer than five years, stocks spatially dominate bonds. This result is consistent with the advice given by practitioners to long term investors of allocating a higher proportion of stocks in their portfolio decisions. The second essay presents a method that allows testing of whether or not an asset stochastically dominates the other when the time horizon is uncertain. In this setup, the expected utility depends on the distribution of the value of the asset as well as the distribution of the time horizon, which together form the weighted spatial distribution. The testing procedure is based on the Kolmogorov Smirnov distance between the empirical weighted spatial distributions. An empirical application is presented assuming that the event of exit time follows an independent Poisson process with constant intensity. The last essay applies a dynamic factor model to generate out-of-sample forecasts for the inflation rate in Mexico. Factor models are useful to summarize the information contained in large datasets. We evaluate the role of using a wide range of macroeconomic variables to forecast inflation, with particular interest on the importance of using the consumer price index disaggregated data. The data set contains 54 macroeconomic series and 243 consumer price subcomponents from 1988 to 2008. The results indicate that factor models outperform the benchmark autoregressive model at horizons of one, two, four and six quarters. It is also found that using disaggregated price data improves forecasting performance.

Vector autoregression (VAR) models are widely used in an attempt to identify and measure the effect of monetary policy shocks on an economy and to forecast economic times series. However, the sparse information sets used in the VAR approach have been subject to criticism and in recent decades, the use of factor models as a means of dimension reduction has been a subject of greater focus. The method of summarizing information contained in a large set of macroeconomic time series by principal components, and use these as regressors in VAR models, has been pointed out as a potential solution to the problems of limited information and estimation of too many parameters. This paper combines the standard VAR methodology with dynamic factor analysis on Swedish data for two purposes, to assess the effects of monetary policy shocks and to examine the forecasting properties. Latent factors estimated by the principal components method are in this study found to contribute to a more coherent picture in line with economic theory, when examining monetary policy shocks to the Swedish economy. The factor-augmented models can on the other hand not be shown to increase the forecasting accuracy to a great extent compared to standard models.

<p>Current frontiers in complex stochastic modeling of high-dimensional processes include major emphases on so-called functional data: problems in which the data are snapshots of curves and surfaces representing fundamentally important scientific quantities. This thesis explores new Bayesian methodologies for functional data analysis. </p><p>The first part of the thesis places emphasis on the role of factor models in functional data analysis. Data reduction becomes mandatory when dealing with such high-dimensional data, more so when data are available on a large number of individuals. In Chapter 2 we present a novel Bayesian framework which employs a latent factor construction to represent each variable by a low dimensional summary. Further, we explore the important issue of modeling and analyzing the relationship of functional data with other covariate and outcome variables simultaneously measured on the same subjects.</p><p>The second part of the thesis is concerned with the analysis of circadian data. The focus is on the identification of circadian genes that is, genes whose expression levels appear to be rhythmic through time with a period of approximately 24 hours. While addressing this goal, most of the current literature does not account for the potential dependence across genes. In Chapter 4, we propose a Bayesian approach which employs latent factors to accommodate dependence and verify patterns and relationships between genes, while representing the true gene expression trajectories in the Fourier domain allows for inference on period, phase, and amplitude of the signal.</p><p>The third part of the thesis is concerned with the statistical analysis of computer models (simulators). The heavy computational demand of these input-output maps calls for statistical techniques that quickly estimate the surface output at untried inputs given a few preliminary runs of the simulator at a set design points. In this regard, we propose a Bayesian methodology based on a non-stationary Gaussian process. Relying on a model-based assessment of uncertainty, we envision a sequential design technique which helps choosing input points where the simulator should be run to minimize the uncertainty in posterior surface estimation in an optimal way. The proposed non-stationary approach adapts well to output surfaces of unconstrained shape.</p> / Dissertation

This volume contains five essays on topics related to interest rate theory.The first essay, Affine Term Structures and Short-Rate Realizations of Forward Rate Models Driven by Jump-Diffusion Processes, examines the problem of determining when a given forward rate model has a short-rate realization, and when a short-rate model gives rise to an affine term structure.The second essay, On the Inversion of the Yield Curve, co-authored with Tomas Björk, considers a general benchmark short-rate factor model of the term structure of interest rates. It is showed that the benchmark model can be extended so that the implied theoretical term structure can be fitted exactly to an arbitrary initially observed yield curve. A general formula for pricing simple contingent claims in the extended model is also provided.The third essay, An Efficient Series Expansion Approach to a Two-Factor Model of the Term Structure of Interest Rates, presents a two-factor model where both factors follow CIR-type diffusion processes. A series expansion is used to solve for discount bond prices. The model is also compared with a corresponding Gaussian model, and no substantial differences are found between the two models regarding the flexibility and shapes of the yield curves and forward rate curves they generate.The fourth essay, An Efficient Series Expansion Approach to The Balduzzi, Das, Foresi and Sundaram Model of the Term Structure of Interest Rates, revisits the model by BDFS, and apart from giving an explicit solution to discount bond prices by using a series expansion, the model is extended so that the implied theoretical term structure can be fitted exactly to an arbitrary initially observed yield curve.The fifth essay, Quasi Arbitrage-Free Discount Bond Prices in the Cox, Ingersoll and Ross Model, offers an example of a less regular solution to the term structure equation in the CIR model. This new and different solution fails to meet one of the standard regularity conditions, but only at one particular point. Under additional conditions, the solution can be interpreted as a term structure, which is referred to as a "quasi arbitrage-free term structure." / Diss. Stockholm : Handelshögsk., 2001

O objetivo deste trabalho é a construção de um indicador coincidente (IC) para a atividade econômica do segmento de Comércio Varejista dentro da economia do estado do Rio Grande do Sul. A utilização de variáveis que apresentem comportamento comum entre si e altamente correlacionado com as Vendas do Varejo é o ponto de partida para a investigação a seguir. A metodologia adotada é a dos modelos de Fator Dinâmico de Stock e Watson (1988, 1989, 1991, 1993). Os resultados encontrados apontam um indicador final satisfatório, em termos de MAPE (erro absoluto percentual médio, em inglês) com relação às séries de Vendas do Varejo, especificamente a série da FEE/Fecomércio-RS – que tratava-se de uma pesquisa censitária. Em termos de fundamentos econômicos o IC é composto por variáveis que sabidamente afetam o consumo de bens: renda, crédito e confiança do consumidor. Um destaque está para o alto peso das variáveis de Crédito e Sentimento sobre a Situação Presente, o que sugere que o fluxo de renda futuro e a confiança para assumir endividamentos longos são determinantes para o segmento. Considerando um horizonte maior para a ampliação dessa pesquisa, postula-se que a construção de novos dados regionalizados para crédito, renda pela PNAD Contínua, séries mais longas para índices de confiança, e indicadores sobre estoques no Comércio podem melhorar os resultados encontrados. / The following research intends to build a coincident indicator to the Retail sector’s economic activity within the regional economy of Rio Grande do Sul. The starting point to reach this objective is to use variables which present common cyclical behavior with each other, as well as with Retail Trade indices. The investigation will be carried on using Stock and Watson’s (1988, 1989, 1991, 1993) Dynamic Factor models methodology. The research returned a result a final index which can be classified as satisfactory, when evaluated by the mean absolute percentage error with Retail Trade indices, specially the FEE/Fecomércio-RS’ index – which was a censitary research. The built Coincident Indicator is composed by variables correlated with consumption, according to the economic theory: income, credit and consumer’s confidence. Variables such as Consumer Credit and Consumer’s Sentiment towards Present Economic Situation presented high weight in the indicator, which suggests that future income flows and confidence to take long term debt are crucial for the sector’s economic activity. Considering an expanded horizon for this research, one believes that new regional data for Household Credit, income through PNAD Contínua, a longer sample for Consumer’s Confidence indices, and indicators measuring stock levels in Retail might improve the coincident indicator.

abstract: This dissertation comprises three chapters. In chapter one, using a rich dataset for the United States, I estimate a series of models to document the birth order effects on cognitive outcomes, non-cognitive outcomes, and parental investments. I estimate a model that allows for heterogeneous birth order effects by unobservables to examine how birth order effects varies across households. I find that first-born children score 0.2 of a standard deviation higher on cognitive and non-cognitive outcomes than their later-born siblings. They also receive 10\% more in parental time, which accounts for more than half of the differences in outcomes. I document that birth order effects vary between 0.1 and 0.4 of a standard deviation across households with the effects being smaller in households with certain characteristics such as a high income. In chapter two, I build a model of intra-household resource allocation that endogenously generates the decreasing birth order effects in household income with the aim of using the model for counterfactual policy experiments. The model has a life-cycle framework in which a household with two children confronts a sequence of time constraints and a lifetime monetary constraint, and divides the available time and monetary resources between consumption and investment. The counterfactual experiment shows that an annual income transfer of 10,000 USD to low-income households decreases the birth order effects on cognitive and non-cognitive skills by one-sixth, which is five times bigger than the effect in high-income household. In chapter three, with Francesco Agostinelli and Matthew Wiswall, we examine the relative importance of investments at home and at school during an important transition for many children, entering formal schooling at kindergarten. Moreover, our framework allows for complementarities between children's skills and investments from schools. We find that investments from schools are an important determinant of children's skills at the end of kindergarten, whereas parental investments, although strongly correlated with end-of-kindergarten outcomes, have smaller effects. In addition, we document a negative complementarity between children's skills at kindergarten entry and investments from schools, implying that low-skill children benefit the most from an increase in the quality of schools. / Dissertation/Thesis / Doctoral Dissertation Economics 2018

O objetivo deste trabalho é a construção de um indicador coincidente (IC) para a atividade econômica do segmento de Comércio Varejista dentro da economia do estado do Rio Grande do Sul. A utilização de variáveis que apresentem comportamento comum entre si e altamente correlacionado com as Vendas do Varejo é o ponto de partida para a investigação a seguir. A metodologia adotada é a dos modelos de Fator Dinâmico de Stock e Watson (1988, 1989, 1991, 1993). Os resultados encontrados apontam um indicador final satisfatório, em termos de MAPE (erro absoluto percentual médio, em inglês) com relação às séries de Vendas do Varejo, especificamente a série da FEE/Fecomércio-RS – que tratava-se de uma pesquisa censitária. Em termos de fundamentos econômicos o IC é composto por variáveis que sabidamente afetam o consumo de bens: renda, crédito e confiança do consumidor. Um destaque está para o alto peso das variáveis de Crédito e Sentimento sobre a Situação Presente, o que sugere que o fluxo de renda futuro e a confiança para assumir endividamentos longos são determinantes para o segmento. Considerando um horizonte maior para a ampliação dessa pesquisa, postula-se que a construção de novos dados regionalizados para crédito, renda pela PNAD Contínua, séries mais longas para índices de confiança, e indicadores sobre estoques no Comércio podem melhorar os resultados encontrados. / The following research intends to build a coincident indicator to the Retail sector’s economic activity within the regional economy of Rio Grande do Sul. The starting point to reach this objective is to use variables which present common cyclical behavior with each other, as well as with Retail Trade indices. The investigation will be carried on using Stock and Watson’s (1988, 1989, 1991, 1993) Dynamic Factor models methodology. The research returned a result a final index which can be classified as satisfactory, when evaluated by the mean absolute percentage error with Retail Trade indices, specially the FEE/Fecomércio-RS’ index – which was a censitary research. The built Coincident Indicator is composed by variables correlated with consumption, according to the economic theory: income, credit and consumer’s confidence. Variables such as Consumer Credit and Consumer’s Sentiment towards Present Economic Situation presented high weight in the indicator, which suggests that future income flows and confidence to take long term debt are crucial for the sector’s economic activity. Considering an expanded horizon for this research, one believes that new regional data for Household Credit, income through PNAD Contínua, a longer sample for Consumer’s Confidence indices, and indicators measuring stock levels in Retail might improve the coincident indicator.

O objetivo deste trabalho é a construção de um indicador coincidente (IC) para a atividade econômica do segmento de Comércio Varejista dentro da economia do estado do Rio Grande do Sul. A utilização de variáveis que apresentem comportamento comum entre si e altamente correlacionado com as Vendas do Varejo é o ponto de partida para a investigação a seguir. A metodologia adotada é a dos modelos de Fator Dinâmico de Stock e Watson (1988, 1989, 1991, 1993). Os resultados encontrados apontam um indicador final satisfatório, em termos de MAPE (erro absoluto percentual médio, em inglês) com relação às séries de Vendas do Varejo, especificamente a série da FEE/Fecomércio-RS – que tratava-se de uma pesquisa censitária. Em termos de fundamentos econômicos o IC é composto por variáveis que sabidamente afetam o consumo de bens: renda, crédito e confiança do consumidor. Um destaque está para o alto peso das variáveis de Crédito e Sentimento sobre a Situação Presente, o que sugere que o fluxo de renda futuro e a confiança para assumir endividamentos longos são determinantes para o segmento. Considerando um horizonte maior para a ampliação dessa pesquisa, postula-se que a construção de novos dados regionalizados para crédito, renda pela PNAD Contínua, séries mais longas para índices de confiança, e indicadores sobre estoques no Comércio podem melhorar os resultados encontrados. / The following research intends to build a coincident indicator to the Retail sector’s economic activity within the regional economy of Rio Grande do Sul. The starting point to reach this objective is to use variables which present common cyclical behavior with each other, as well as with Retail Trade indices. The investigation will be carried on using Stock and Watson’s (1988, 1989, 1991, 1993) Dynamic Factor models methodology. The research returned a result a final index which can be classified as satisfactory, when evaluated by the mean absolute percentage error with Retail Trade indices, specially the FEE/Fecomércio-RS’ index – which was a censitary research. The built Coincident Indicator is composed by variables correlated with consumption, according to the economic theory: income, credit and consumer’s confidence. Variables such as Consumer Credit and Consumer’s Sentiment towards Present Economic Situation presented high weight in the indicator, which suggests that future income flows and confidence to take long term debt are crucial for the sector’s economic activity. Considering an expanded horizon for this research, one believes that new regional data for Household Credit, income through PNAD Contínua, a longer sample for Consumer’s Confidence indices, and indicators measuring stock levels in Retail might improve the coincident indicator.