The purpose of this thesis is to examine how quantitative easing in the United States works through the transmission channels to establish a positive short-run effect on inflation. The research will be based on a time series analysis covering the period 2006-2015 with data collected on a monthly basis. As quantitative easing is a new unconventional monetary policy, we want to contribute to the understanding of its short-run effects on inflation. Using a distributed lag model, we conclude that quantitative easing is positively related to inflation in the short-run. The U.S. short-term interest rate, the federal funds rate, is included in the estimated model to see if it works when quantitative easing has been implemented. Furthermore, crude oil and the USD/EUR exchange rate is included as control variables to reduce the effects of exogenous factors in the estimated model. The regression results of quantitative easing and the federal funds rate showed statistical significance against inflation, however with a very small effect, respectively. In the final section we discuss the limitations of this thesis and future research possibilities.

Diversos são os benefícios e objetivos de um profundo entendimento técnico do comportamento das taxas de juros, tanto de uma economia madura como de uma emergente. Do planejamento à execução de política monetária e da criação de cenários econômicos para tomada de decisão à alocação de recursos baseada somente nesses cenários, esses agentes podem fazer uso do arcabouço teórico que embasa as diferentes hipóteses de mercados eficientes e expectativas racionais, bem como do prêmio de risco, entre outras. Diante desse contexto, faz-se necessário estar em constante contato com o que a comunidade acadêmica desenvolve de tecnologia no estudo de curvas de juros. Este trabalho abordará as relações de cointegração e a possibilidade de elaboração de estratégias de investimentos de recursos financeiros baseadas somente nas relações descobertas. As diferentes modalidades operacionais foram escolhidas buscando replicar empiricamente no mercado de derivativos os fatores mais utilizados nos modelos de estimação e previsão de curva de juros e taxas a termo de juros. Visto que tais estratégias demandam mais sofisticação por parte do investidor, tendem a ser implementadas mais comumente por gestores profissionais e profissionais de bancos, e tentar-se-á mensurar seu potencial de retorno e sua remuneração frente ao risco tomado. / Many benefits and objectives came from a deep understanding of interest rates behavior in developed countries and in emergent markets. From plan to execute monetary policy, to create economics scenarios, the decision that are made based in those scenarios, and for any kind of asset allocation, all market participants can use the theory that underlies the efficient market hypothesis, rational expectations and all kinds of risk premium. In this context, it is necessary to be in touch with academic literature technology about yield curves. This paper addresses the cointegration relations on interest rates and the trading opportunities that came from these relations. The strategies was chosen looking for apply in the markets the most usual models present on yield curve and forward rate estimation and prediction fields. Since these strategies demand a higher sophistication from investors, they tend to be used for professional asset managers and bankers. This work intends measure the potential profits and the return towards the risk of this investment approach.

We address the issue of market incompleteness in the time dimension. Specifically, we focus on interest rate markets and the yield curve extraction. The lack of information about interest rates manifest itself in a non-invertible linear system. The usual approach to circumvent this problem is by applying various curve fitting methods - both parametric and non-parametric. We argue in favor of a novel method relying on information theory, which reformulates the ill-posed linear algebra problem into a well-posed optimization problem, where the linear pricing equations are used as constraints. Local cross entropy is used to determine the optimal solution among the admissible solutions, while all the input prices reflected in constraints are perfectly matched. Large-scale optimization package called AMPL is used extensively throughout this work to obtain the optimal solution as well as to demonstrate the implementation details.

U.S. Treasury Securities are crucially important in many areas of finance. However, zero-coupon yields are not observable in the market. Even though published zero- coupon yields exist, they are sometimes not available for certain research topics or for high frequency. Recently, high frequency data analysis has become popular, and the GovPX database is a good source of tick data for U.S. Treasury securities from which we can construct zero-coupon yield curves. Therefore, we try to t zero- coupon yield curves from low frequency and high frequency data from GovPX by three different methods: the Nelson-Siegel method, the Svensson method, and the cubic spline method. Then, we try to retest the expectations hypothesis (EH) with new zero-coupon yields that are made from GovPX data by three methods using the Campbell and Shiller regression, the Fama and Bliss regression, and the Cochrane and Piazzesi regression. Regardless of the method used (the Nelson-Siegel method, the Svensson method, or the cubic spline method), the expectations hypothesis cannot be rejected in the period from June 1991 to December 2006 for most maturities in many cases. We suggest the possible explanation for the test result of the EH. Based on the overreaction hypothesis, the degree of the overreaction of spread falls over time. Thus, our result supports that the evidence of rejection of the EH has weaken over time. Also, we introduce a new estimation method for the stochastic volatility model of the short-term interest rates. Then, we compare our method with the existing method. The results suggest that our new method works well for the stochastic volatility model of short-term interest rates.

This dissertation consists of four papers in structural empirics that can be broadly categorized into two areas. The first three papers revolve around the structural estimation of demand for differentiated products and several applications thereof (Berry (1994), Berry, Levinsohn and Pakes (1995), Nevo (2000)), while the fourth paper examines the U.S. Treasury yield curve by estimating yields as linear functions of observable state variables (Ang and Piazzesi (2003), Ang et al. (2006)). The central focus of each paper are the underlying economics. Nevertheless, all papers share a common empirical approach. Be it prices of beers in Sweden or yields of U.S. Treasury bonds, it is assumed throughout that the economic variables of interest can be modeled by imposing specific parametric functional forms. The underlying structural parameters are then consistently estimated based on the variation in available data. Consistent estimation naturally hinges on the assumption that the assumed functional forms are correct. Another way of viewing this is that the imposed functions are flexible enough not to impose restrictive patterns on the data that ultimately lead to biased estimates of the structural parameters and thereby produce misleading conclusions regarding the underlying economics. In principle, the danger of misspecification could therefore be avoided by adopting sufficiently flexible functional forms. This, however, typically requires the estimation of a growing number of structural parameters that determine the underlying economic relationships. As an example, we can think of the estimation of differentiated product demand. The key object of interest here is the substitution patterns between the products. That is, we are interested in what happens to the demand of good X and all its rival products, as the price of good X increases. With N products in total, we could collect the product-specific changes in demand in a vector with N entries. It is also possible, however, that the price of any other good Y changes and thereby alters the demands for the remaining varieties. Thus, in total, we are interested in N2 price effects on product-specific demand. With few products, these effects could be estimated directly and the risk of functional misspecification could be excluded (Goolsbee and Petrin (2004)). With 100 products, however, we are required to estimate 10,000 parameters, which rarely, if ever, is feasible. This is the curse of dimensionality. Each estimation method employed in the four papers breaks this curse by imposing functions that depend on relatively few parameters and thereby tries to strike a balance between the necessity to rely on parsimonious structural frameworks and the risk of misspecification. This is a fundamental feature of empirical research in economics that makes it both interesting and challenging. / <p>Diss. Stockholm :  Stockholm School of Economics, 2012. Introduction together with 4 papers</p>

Random field models have provided a flexible environment in which the properties of the term structure of interest rates are captured almost as observed. In this study we provide an overview of the forward rate random fiield models and propose an extension in which the forward rates fluctuate along with a two parameter process represented by a random field. We then provide a mathematical expression of the yield curve under this model and sketch the prospective utilities and applications of this model for interest rate management.

Made available in DSpace on 2010-04-20T20:58:09Z (GMT). No. of bitstreams: 1 1_166956.pdf: 440067 bytes, checksum: 8342545d2c40f2fdb11a07cafe147bd9 (MD5) Previous issue date: 2007-12-18T00:00:00Z / This work extendes Diebold, Li and Yueís (2006) about global yield curve and proposes to extend the study by including emerging countries. The perception of emerging market su§ers ináuence of external factors or global factors, is the main argument of this work. We expect to obtain stylized facts.that obey similar pattern found by those authors. The results indicate the existence of global level and global slope factors. These factors represent an important fraction in the bond yield determination and show a decreasing trend of the global level factor low ináuence of global slope factor in these countries when they are compared with developed countries. Keywords: Kalman Filter, Emerging Markets, Yield Curve, and Bond.

Este trabalho testa a validade da Hipótese das Expectativas, segundo a qual as taxas de juros de longo prazo são formadas pela média das expectativas sobre as taxas de curto prazo futuras. O estudo baseia-se em dois artigos reconhecidos internacionalmente: Fama e Bliss (1987) e Cochrane e Piazzesi (2005). Os testes são realizados utilizando-se retornos em excesso e taxas forward mensais para títulos com prazo de vencimento entre dois e cinco anos. A base de dados consiste em observações mensais da taxa à vista de contratos futuros de DI. Os resultados apontam para a rejeição da HE para o caso brasileiro. Uma combinação linear de taxas forward é capaz de explicar a variação dos retornos em excesso com R² de até 0,63 para um título com maturidade em dois anos. / This work tests the validity of Expectations Hypothesis (EH), which posts that the long-term rates are an average of future expectations of short-term rates. The study is based on two internationally recognized papers: Fama e Bliss (1987) and Cochrane e Piazzesi (2005). The tests are performed using monthly observations on excess returns and forward rates for 2 to 5 year bonds. The data consists in monthly observations of ID future contracts yields. The results suggest rejection the EH for the Brazilian case. A linear combination of forward rates is able to explain excess returns variation with R² up to 0.63 for 2-year bonds.

Neste trabalho, estudam-se métodos que consideram a natureza funcional da Estrutura a Termo da Taxa de Juros (ETTJ) para fazer previsões fora da amostra. São estimados modelos não-paramétricos para dados funcionais (NP-FDA) e séries temporais funcionais (FTS). O primeiro se baseia em um estimador de regressão proposto por Ferraty e Vieu (2006), que utiliza funções Kernel para atribuir pesos localmente às variáveis funcionais. Já o segundo se baseia no trabalho de Hays, Shen e Huang (2012), que estimam a ETTJ através de um modelo de fatores dinâmicos, que por sua vez são estimados através de análise de componentes principais funcional. Testa-se a capacidade de previsão dos modelos com a ETTJ americana, para os horizontes de 1, 3, 6 e 12 meses, e comparam-se os resultados com modelos benchmark, como Diebold e Li (2006) e o passeio aleatório. Principal foco deste trabalho, as estimações com métodos NP-FDA não tiveram resultado muito bons, obtendo sucesso apenas com maturidades e horizontes muito curtos. Já as estimações com FTS tiveram, no geral, desempenho melhor que os métodos escolhidos como benchmark. / This work studies methods that takes the Yield Curve's functional nature into account to produce out-of-sample forecasts. These methods are based in nonparametric functional data analysis (NP-FDA) and functional time series (FTS). The former are based in a functional regressor estimator proposed by Ferraty e Vieu (2006) that includes Kernel functions to do local weighting between the functional variables. The latter are based on the paper by Hays, Shen and Huang (2012), that forecasts the Yield Curve based in a dynamic factors model, in which the factors are determined by functional principal component analysis. Their forecasting capability is tested for the american's Yield Curve database for 1, 3, 6 and 12 months. The results from the functional methods models are then compared to benchmarks widely used in the literature, such as the random walk and the Diebold and Li (2006). Main focus on this work, the NP-FDA methods didn't produce very good forecasts, being successful only for very low maturities and short forecast horizons. The forecasts generated by the FTS methods were, in general, better than our chosen benchmarks.

O presente trabalho testa uma alternativa de ajuste da estrutura a termo da taxa de juros brasileira bem como a sua previsão através de uma variação do modelo Diebold e Li (2006) focando principalmente em seu fator de decaimento exponencial. Esta variação do fator de decaimento ocorre distintamente em dois momentos do trabalho, primeiramente no ajuste da curva e após quando da previsão desta. No ajuste, o encontro deste parâmetro é feito através de ferramenta computacional, buscando o fator de decaimento que reduz a diferença de mínimos quadrados em relação aos pontos originais capturados no mercado de juros futuro brasileiro em conjunto dos três outros fatores do modelo. A previsão da estrutura a termo utiliza modelos auto regressivos para estimar as próximas curvas no horizonte de um período. A importância deste estudo reside em conhecer a aderência do modelo proposto à curva de juros brasileira testando sua eficiência quando utilizados os pressupostos enunciados. / This study tests an alternative adjustment of the term structure of Brazilian interest rate and its prediction through a variation of the Diebold and Li (2006) model focusing mainly on his exponential decay factor. The variation of the decay factor occurs in two distinct moments of this work, in the curve fitting and after this in the forecasting. During the setting, this parameter is mesured through computational tool, seeking the decay factor that reduces the difference in least squares relative to the original points captured in the Brazilian market future interest together the other three factors of the model. To Forecast the term structure is used auto regressive models to estimate the upcoming curves. The importance of this study lies in knowing the adherence of the proposed to the Brazilian yield curve testing its efficiency when utilized the assumptions listed in the model.