Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-06-14T13:10:24Z No. of bitstreams: 1 danielmoraisdesouza.pdf: 1277495 bytes, checksum: 7c2517a5b98a6f70aa787d954cd0c84a (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-06-27T15:04:32Z (GMT) No. of bitstreams: 1 danielmoraisdesouza.pdf: 1277495 bytes, checksum: 7c2517a5b98a6f70aa787d954cd0c84a (MD5) / Made available in DSpace on 2018-06-27T15:04:32Z (GMT). No. of bitstreams: 1 danielmoraisdesouza.pdf: 1277495 bytes, checksum: 7c2517a5b98a6f70aa787d954cd0c84a (MD5) Previous issue date: 2018-02-19 / Eletricidade é um insumo de uso generalizado nas economias modernas, penetrando nas mais variadas atividades produtivas e de consumo na sociedade. No entanto, as dificuldades de armazenamento em larga escala dessa forma de energia fazem com que a eletricidade seja muito sensível às condições de oferta, a ponto de que problemas de abastecimento rapidamente se convertem em apagões. Dentre vários dispositivos implementados na re-estrutuação do setor elétrico brasileiro (SEB) ao longo dos últimos 17 anos, estão sistemas de previsão de médio e longo-prazos usados por parte dos agentes públicos e privados do setor para reduzir as incertezas dos processos de abastecimento e expansão. A ANEEL chegou a recomendar na NT 292/2008-SER o uso de três metodologias multivariadas alternativas nesses sistemas de previsão, a saber: modelos VAR e VCE, modelos autorregressivos com defasagens distribuídas (ARDL) e modelos estruturais a espaço de estados. A literatura especializada, em que pese a presença de vários estudos propondo modelos de previsão do consumo de eletricidade para os três segmentos residencial, industrial e comercial, apresenta majoritariamente modelos de tipo VAR e VCE. Este estudo atualiza a literatura no que concerne ao uso de modelos VAR e VCE e ao mesmo tempo os compara em termos preditivos com os modelos ARDL e estruturais a espaço de estados. Os resultados encontrados na análise do desempenho preditivo dos modelos mostraram que para o segmento residencial, o modelo com melhor capacidade preditivo foi o modelo estrutural, enquanto que para o segmento comercial foi o modelo VCE e, para o segmento industrial, foi o modelo ARDL. Previsões de 2014 a 2025 foram feitas com o intuito de informar ao mercado brasileiro a demanda de energia para cada segmento. Foram usadas bases de dados disponíveis e atualizadas provenientes das mesmas fontes usadas nos estudos da literatura. / Electricity is an input of widespread use in modern economies, penetrating in the most varied productive and consumption activities in society. However, the difficulties of large-scale storage make electricity very sensitive to supply conditions, to the point that supply problems quickly turns into blackouts. Among several devices implemented in the re-structuring of the Brazilian electricity sector (SEB) over the last 17 years, medium and long-term forecasting systems are used by public and private sector agents to reduce the uncertainties of the supply processes and expansion. ANEEL recommend in NT 292/2008-SER the use of three alternative multivariate methodologies in these prediction systems, namely: VAR and VCE models, autoregressive models with distributed lags (ARDL), and state space structural models. The specialized literature, despite the presence of several studies proposing models of prediction of the consumption of electricity for the three residential, industrial and commercial segments, mainly presents models of type VAR and VCE. This study updates the literature regarding the use of VAR and VCE models and at the same time compares them in predictive terms with the ARDL and structural state space models. The results found in the predictive model analysis showed that for the residential segment, the model with the best predictive capacity was the structural model, while for the commercial segment it was the VCE model and, for the industrial segment, it was the ARDL model. Forecasts from 2014 to 2025 were made with the intention of informing the Brazilian market the energy demand for each segment. Available and updated databases from the same sources used in literature studies were used.

Cette thèse porte sur la prévision de la demande des expéditeurs et des offres de capacité des transporteurs pour la planification opérationnelle des systèmes `Many-to-One-to-Many' (M1M). Un tel système agit comme un décideur intermédiaire entre les expéditeurs et les transporteurs en coordonnant le transport des marchandises des expéditeurs aux destinataires en utilisant les capacités offertes par les transporteurs. Le décideur prend ses décisions dans un horizon de planification opérationnelle, en optimisant ces décisions en tenant compte de l'incertitude sur les périodes futures. Pour accompagner les décisions du décideur, il est essentiel de prédire les nouvelles demandes des expéditeurs et les nouvelles capacités des transporteurs. Cela conduit à des problèmes de prévision de séries chronologiques à plusieurs variables et à plusieurs étapes. L'objectif de ce travail est d'analyser l'impact des erreurs de prévision sur la qualité de la solution pour un problème de planification opérationnelle M1M donné. Cette thèse présente d'abord la structure du système M1M, la planification opérationnelle et les tâches de prévision associées. Nous décrivons la caractérisation des demandes des expéditeurs et des offres des transporteurs ainsi que comment la prévision peut soutenir les décisions en définissant les informations nécessaires pour le décideur sur l'horizon opérationnel. Nous couvrons ensuite l’optimisation de l’affectation charge-transporteur en introduisant un modèle d'optimisation déterministe et les prévisions utilisées en entrée. En l'absence de données réelles, nous générons un ensemble de données synthétiques qui est ensuite utilisé pour estimer les modèles de prévision. L'objectif est de définir quelques modèles de prévision qui présentent des erreurs afin que nous puissions évaluer leur impact sur la qualité de la solution pour le problème de planification opérationnelle. Dans ce contexte, nous comparons plusieurs modèles ARIMA pour prédire les futures demandes et offres. Nous constatons que les modèles avec des erreurs de prévision relativement faibles peuvent conduire à des améliorations significatives de la qualité de la solution. Enfin, nous exposons quelques pistes de recherches futures. / This thesis is about forecasting new shipper-demand requests and carrier-capacity offers for operational planning of Many-to-One-to-Many (M1M) systems. Such a system acts as an intermediary decision-maker between shippers and carriers, coordinating the transportation of goods from shippers to consignees (shipment recipients) using capacity offered from carriers. The decision-maker makes the decisions within an operational planning horizon, optimizing these decisions accounting for uncertainty over future time periods. To support the decisions, forecasting new shipper-demands and carrier capacities is essential. This leads to multi-variate multi-step time series forecasting problems. The objective of this work is to analyze the impact of forecast errors on the solution quality for a given M1M operational planning optimisation method. This thesis first presents the M1M system structure, operational planning, and related forecasting tasks. It explains the characterization of the shipper requests and carrier offers. We describe how forecasting can support the decisions by defining the needed information for the decision-maker over the operational horizon. We then cover the optimization of load-to-carrier assignments introducing a deterministic formulation and the forecasts used as input. In the absence of real data, we generate a synthetic data set that is then used for estimating forecasting models. The aim is to define a few forecasting models that exhibit some errors so that we can assess their impact on the solution quality for the operational planning problem. In this context, we compare several ARIMA models to predict future requests and offers. We find that the models with relatively low forecast errors can lead to significant improvements in solution quality. Finally, we outline a few directions for future research.

The estimation and analysis of signals that have polynomial phase and constant or time-varying amplitudes with the addititve noise is considered in this dissertation.Much work has been undertaken on this problem over the last decade or so, and there are a number of estimation schemes available. The fundamental problem when trying to estimate the parameters of these type of signals is the nonlinear characterstics of the signal, which lead to computationally difficulties when applying standard techniques such as maximum likelihood and least squares. When considering only the phase data, we also encounter the well known problem of the unobservability of the true noise phase curve. The methods that are currently most popular involve differencing in phase followed by regression, or nonlinear transformations. Although these methods perform quite well at high signal to noise ratios, their performance worsens at low signal to noise, and there may be significant bias. One of the biggest problems to efficient estimation of these models is that the majority of methods rely on sequential estimation of the phase coefficients, in that the highest-order parameter is estimated first, its contribution removed via demodulation, and the same procedure applied to estimation of the next parameter and so on. This is clearly an issue in that errors in estimation of high order parameters affect the ability to estimate the lower order parameters correctly. As a result, stastical analysis of the parameters is also difficult. In thie dissertation, we aim to circumvent the issues of bias and sequential estiamtion by considering the issue of full parameter iterative refinement techniques. ie. given a possibly biased initial estimate of the phase coefficients, we aim to create computationally efficient iterative refinement techniques to produce stastically efficient estimators at low signal to noise ratios. Updating will be done in a multivariable manner to remove inaccuracies and biases due to sequential procedures. Stastical analysis and extensive simulations attest to the performance of the schemes that are presented, which include likelihood, least squares and bayesian estimation schemes. Other results of importance to the full estimatin problem, namely when there is error in the time variable, the amplitude is not constant, and when the model order is not known, are also condsidered.

證券市場和一般商品市場本質上有所不同; 一般商品市場的需求和供給者是截然劃分 的集團; 而證券市場是一個流通市場, 其參與者既是需求者亦是供給者, 以經濟學理 論來預測分析, 解釋證券市場行為是一種主流, 而價格和數量又是經濟學領域中最主 要兩個變數; 環視現代探討證券市場行為的文章, 大部份只偏重於價格或數量單方面 之探討; 或價格與數量間單方向因果關系的研究, 由這些研究所得結論來說明證券市 場價格和數量間關系顯然不夠, 例如在探討未來價格變動時除了前期價格因素外, 尚 有數量因素會影響未來價格因素的發展。 多元時間序列分析方法系直接使用多個變數數列資料間所顯示之自我相關特性及交叉 相關特性以設定出變數間可能存在的因果關系, 而且其具有以下之優點。(1) 序列與 序列之間可能存在領先、同時、及回饋等多種關系, 藉著MARMA 模型之設定即可顯示 多個序列間基本之動態關系。(2) 聯合多個數列來建立模型亦可利用其他數列所提供 情報提高預測之準確性。(3) 介之分析(Intervention Analysis) 或季節因素之調整 都可由MARMA 模型之建之得到更精確的結果。 本文即利用多元時間序列模式(Multiple Time Series Models簡稱MARMA)分析方法, 探討證券市場價格與數量同時對數量或同時對價格的影響。

明天股票的價格是會漲還是會跌呢? 明天到底會不會下雨? 下期樂透開獎會是哪些號碼呢? 未來不知道會發生哪些事情? 大家總是希望能夠未卜先知、洞悉未來! 可是我們要如何進行預測呢? 本文比較了不同時間序列模型的預測績效, 而且測試預測的結合是否能夠改進預測的準確度? 時間序列模型的研究在近年來非常蓬勃地發展, 所以本文簡單介紹了時間序列模型(Time series models)當中的線性AR模型、非線性TAR模型、非線性STAR模型, 以及這些模型該如何來進行在樣本外的預測。 同時本文說明了預測的結合(Combined forecast)該如何進行? 預測結合的目的是希望能夠達到截長補短的效果! 除了傳統迴歸(Regression-based)方法和變動係數(Time-varying coefficients)方法外, 本文提出了兩種非迴歸類型的預測結合方法, 績效權數(Fitness weight)和支向機(Support Vector Machine)。 其中主要的焦點放在支向機, 因為迴歸方法可能會有共線性的問題, 支向機則是沒有這個問題。 本文實證的結果顯示, 在時間序列模型方面, 非線性模型的預測能力, 在大多數的情形底下, 都不如簡單的線性AR模型; 在預測結合的方面, 支向機的績效是和迴歸方法的績效是差不多的, 這兩者都比變動係數方法的績效來得穩固, 可是如果基底模型的預測值存在共線性的問題或樣本數目過少的問題, 那麼支向機的績效是優於迴歸方法的績效。 最後, 時間序列模型的預測績效會受到資料性質的影響, 而有極大的改變, 或許我們可以考慮使用比較保險的預測策略-預測結合, 因為預測結合的預測誤差範圍是小於時間序列模型的預測誤差範圍!

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This thesis investigates the nature of joint dividend-and-earnings signalling in announcements to the New Zealand Stock Exchange in the 1990s. Initially the Market Model is used to compute expected returns, and the abnormal returns derived from these are subjected to restricted least squares regressions to separate out a putative dividend signal from the concurrent earnings signal. But with the Market Model, the zero-value company returns associated with an absence of trading in thinly traded stocks are over-represented in returns distributions leading to problems of bias. New models are developed that explicitly exploit zero returns. The first alternative methodology entails friction modelling, which uses a maximum likelihood estimation procedure to find the relationship coefficients and the range of returns that should be considered as zero, and then proceeds to treat them as a separate category. The second alternative methodology is that of state asset models, which take a fresh new look at investor perceptions of the connection between movements in company returns and those of the concurrent underlying market. Zero-value company returns cease to be zero in value, where a state model is rotated, or alternatively they can be modelled as an extra state. All three methodologies furnish some evidence of dividend signalling; but this evidence is highly dependent on small changes within the given methodology.

Submitted by Antoanne Pontes (antoanne.pontes@fgv.br) on 2008-11-03T11:55:49Z No. of bitstreams: 1 Tese_Jose_Oswaldo.pdf: 3867161 bytes, checksum: 69d24eaada7645f7cb0e6361f9721f6d (MD5) / Approved for entry into archive by Antoanne Pontes(antoanne.pontes@fgv.br) on 2008-11-03T12:04:43Z (GMT) No. of bitstreams: 1 Tese_Jose_Oswaldo.pdf: 3867161 bytes, checksum: 69d24eaada7645f7cb0e6361f9721f6d (MD5) / Made available in DSpace on 2008-11-03T12:04:43Z (GMT). No. of bitstreams: 1 Tese_Jose_Oswaldo.pdf: 3867161 bytes, checksum: 69d24eaada7645f7cb0e6361f9721f6d (MD5) / Esta tese é composta por três ensaios que versam sobre os efeitos macroeconômicos da Política Fiscal, especialmente sobre os principais agregados, tais como Produto, Investimento, Consumo e a Produtividade Geral da Economia. A literatura econômica e os trabalhos empíricos não são consensuais com relação à natureza dos impactos produtivos da Política Fiscal, mesmo para o caso do capital público. O objetivo dessa Tese não é buscar esse consenso, mas acrescentar à literatura novas evidências sobre os países em desenvolvimento da América Latina. O primeiro ensaio investiga as relações dinâmicas (no curto e longo prazo) entre investimento público e produto e investimento público e a Produtividade Total dos Fatores (PTF) para a Argentina, Brasil e Chile. Os resultados encontrados para os três países foram unânimes quando se refere a uma relação de longo prazo positiva entre investimento público e produto. O mesmo não se pode afirmar com respeito aos impactos de longo prazo entre investimento público e produtividade total dos fatores. O segundo ensaio aperfeiçoa a discussão do artigo anterior ao inquirir os efeitos não somente do investimento público, mas também do consumo do governo. Além disso, os impactos são avaliados sobre o PIB e seus principais componentes, tais como consumo das famílias e investimento privado. Os resultados desse capítulo sugerem que, no longo prazo, os investimentos públicos tendem a afetar positivamente o produto e o consumo das famílias. O consumo do governo afeta negativamente o produto e os investimentos privados para a maioria dos países. No entanto, esse resultado não é absoluto e depende do nível relativo do consumo do governo. No curto prazo, os resultados de uma política de estabilização ativa baseados nos pressupostos keynesianos são bastante limitados em termos de magnitude e duração ao longo do tempo. O terceiro ensaio analisa a consistência da política fiscal no Brasil, a partir de 1999, sob a perspectiva da estabilidade acroeconômica e seus efeitos de longo prazo sobre a sustentabilidade da dívida pública. Vale ressaltar que a consistência da política fiscal no médio e no longo prazos é fundamental para se vislumbrar um crescimento econômico sustentado. Os resultados indicam que, na formação de suas expectativas, o mercado observa apenas o número do superávit primário e o nível da dívida pública, desconsiderando a consistência do superávit primário, o que sugere certo grau de miopia em relação à política fiscal brasileira.

Submitted by Andre Barbosa Oliveira (andre.boliveira@hotmail.com) on 2014-09-10T13:02:37Z No. of bitstreams: 1 EnsaiosPortfolioMudançaDeRegime.pdf: 2662067 bytes, checksum: af012615c3e200b24dcafe0ba45c563d (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2014-09-10T17:49:11Z (GMT) No. of bitstreams: 1 EnsaiosPortfolioMudançaDeRegime.pdf: 2662067 bytes, checksum: af012615c3e200b24dcafe0ba45c563d (MD5) / Made available in DSpace on 2014-09-10T18:01:56Z (GMT). No. of bitstreams: 1 EnsaiosPortfolioMudançaDeRegime.pdf: 2662067 bytes, checksum: af012615c3e200b24dcafe0ba45c563d (MD5) Previous issue date: 2014-08-15 / Uma das principais características dos ativos financeiros é a mudança de regime. Os preços dos ativos apresentam pouca variabilidade nos períodos de normalidade e possuem quedas inesperadas e são instáveis nos períodos de crise. Esta tese estuda alocação de portfólio com mudança de regime. O primeiro ensaio considera a decisão ótima de investimento entre os ativos de risco quando o mercado financeiro possui mudança de regime, definindo portfólios ótimos que dependem dos retornos esperados, risco e das crenças sobre o estado do mercado financeiro. O segundo ensaio estuda alocação de portfólio baseada em estimativas do modelo fatorial com mudança de regime e compara com alocações usando modelos fatoriais lineares e momentos amostrais. A mudança de regime tem maior efeito sobre o processo de escolha dos portfólios do que sobre as estimativas usadas para definir as carteiras. / Among the characteristics of the financial assets an important stylized fact is regime change. Asset prices show little variability in good times and have unexpected drops and are unstable in times of crisis. This thesis studies portfolio allocation with regime change. The first essay considers the optimal investment decision among risky assets when the financial market has regime switching. The optimal portfolio depend on expected returns and risk as well as on beliefs about the state of the financial market. The second essay studies asset allocation based on estimates of the factor model with regime change and compares with allocations using linear factor models and sample moments. The presence of multiple regimes has a greater effect on portfolio choice than on the estimates used to determine the portfolios.

Submitted by Rafael da Rocha Mendonça Bacciotti (rafael.bacciotti@gmail.com) on 2017-08-13T23:42:30Z No. of bitstreams: 1 Rafael Bacciotti_defesa.pdf: 1094193 bytes, checksum: 7a7f6313d22efa00eb4133077c507ec5 (MD5) / Rejected by Joana Martorini (joana.martorini@fgv.br), reason: Falta a ficha catalográfica. on 2017-08-14T13:23:19Z (GMT) / Submitted by Rafael da Rocha Mendonça Bacciotti (rafael.bacciotti@gmail.com) on 2017-08-21T18:34:28Z No. of bitstreams: 1 Rafael Bacciotti_final.pdf: 959318 bytes, checksum: a65761f39f40377669fe2d34280903ab (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2017-08-21T18:55:31Z (GMT) No. of bitstreams: 1 Rafael Bacciotti_final.pdf: 959318 bytes, checksum: a65761f39f40377669fe2d34280903ab (MD5) / Made available in DSpace on 2017-08-22T12:21:28Z (GMT). No. of bitstreams: 1 Rafael Bacciotti_final.pdf: 959318 bytes, checksum: a65761f39f40377669fe2d34280903ab (MD5) Previous issue date: 2017-08-11 / A análise do mercado de trabalho em perspectiva histórica com base em séries de alta frequência no Brasil é uma tarefa desafiadora, pois não há uma pesquisa longa, abrangente e ao mesmo tempo compatível em termos metodológicos e conceituais que permita acompanhar o desempenho das diversas variáveis de maneira adequada. Essas questões foram exacerbadas no início de 2016, quando a Pesquisa Mensal de Emprego (PME) foi interrompida pelo IBGE. Desde então, a Pesquisa Nacional por Amostra de Domicílios Contínua (PNAD Contínua) passou a ser a única referência do instituto sobre o mercado de trabalho em alta frequência. Nesse contexto, este trabalho tem como objetivo retroagir a taxa de desemprego trimestral da Pesquisa Nacional por Amostra de Domicílios Contínua (PNAD Contínua), iniciada em março de 2012. Duas séries foram geradas com base na metodologia de modelos de espaço de estados e o filtro de Kalman: a primeira iniciada em 1976 e outra em 1984, utilizando-se como referência, nos dois casos, as taxas de desemprego obtidas na PNAD anual e na Pesquisa de Emprego e Desemprego (PED - Dieese). / The analysis of the labor market in historical perspective in Brazil is a challenging task, since there is not a long, comprehensive and at the same time methodologically and conceptually compatible survey that allows monitoring the performance of the various variables in an appropriate manner. These issues were exacerbated in early 2016, when the Pesquisa Mensal de Emprego (PME) was interrupted by IBGE. Since then, the Pesquisa Nacional por Amostra de Domicílios Contínua (PNAD Contínua) has become the Institute's only reference to the high-frequency labor market monitoring. In this context, the objective of this study is to retropolate the unemployment rate from PNAD Contínua, begun in March 2012. Two series were produced from the state space model methodology, with the Kalman filter, one since 1976 and another since 1984, using as reference the annual PNAD and the Pesquisa de Emprego e Desemprego (PED-Dieese).