Economic cycles and term structure: application to Brazil

The objective of this work is to describe the behavior of the economic cycle in Brazil through Markov processes which can jointly model the slope factor of the yield curve, obtained by the estimation of the Nelson-Siegel Dynamic Model by the Kalman filter and a proxy variable for economic performance, providing some forecasting measure for economic cycles

A taxa natural de juros no Brasil

Neste artigo, foi estimada a taxa natural de juros para a economia brasileira entre o final de 2001 e segundo trimestre de 2010 com base em dois modelos, sendo o primeiro deles o proposto por Laubach e Williams e o segundo proposto por Mes��nnier e Renne, que trata de uma vers��o alterada do primeiro, que segundo os autores perimite uma estima����o mais transparente e robusta. Em ambos os modelos, a taxa natural de juros �� estimada em conjunto com o produto potencial, atrav��s de filtro de Kalman, no formato de um modelo Espa��o de Estado. As estimativas provenientes dos dois modelos n��o apresentam diferen��as relevantes, o que gera maior confiabilidade nos resultados obtidos. Para o per��odo de maior interesse deste estudo (p��s-2005), dada a exist��ncia de outras an��lises para per��odo anterior, as estimativas mostram que a taxa natural de juros est�� em queda na economia brasileira desde 2006. A mensura����o da taxa natural de juros, adicionalmente, possibilitou que fosse feita uma avalia����o sobre a condu����o da pol��tica monet��ria implementada pelo Banco Central brasileiro nos ��ltimos anos atrav��s do conceito de hiato de juros. Em linhas gerais, a an��lise mostrou um Banco Central mais conservador entre o final de 2001 e 2005, e mais pr��ximo da neutralidade desde ent��o. Esta conclus��o difere da apontada por outros estudos, especialmente para o primeiro per��odo.

Estimating Brazilian Monthly GDP: a State-Space Approach

This paper has several original contributions. The first is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series- all coincident with GDP from a business-cycle dating point of view. Based on these results, we finally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil - the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, which may not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.

Previs��o de infla����o utilizando modelos de s��ries temporais

Este trabalho compara modelos de s��ries temporais para a proje����o de curto prazo da infla����o brasileira, medida pelo ��ndice de Pre��os ao Consumidor Amplo (IPCA). Foram considerados modelos SARIMA de Box e Jenkins e modelos estruturais em espa��o de estados, estimados pelo filtro de Kalman. Para a estima����o dos modelos, foi utilizada a s��rie do IPCA na base mensal, de mar��o de 2003 a mar��o de 2012. Os modelos SARIMA foram estimados no EVIEWS e os modelos estruturais no STAMP. Para a valida����o dos modelos para fora da amostra, foram consideradas as previs��es 1 passo �� frente para o per��odo de abril de 2012 a mar��o de 2013, tomando como base os principais crit��rios de avalia����o de capacidade preditiva propostos na literatura. A conclus��o do trabalho �� que, embora o modelo estrutural permita, decompor a s��rie em componentes com interpreta����o direta e estud��-las separadamente, al��m de incorporar vari��veis explicativas de forma simples, o desempenho do modelo SARIMA para prever a infla����o brasileira foi superior, no per��odo e horizonte considerados. Outro importante aspecto positivo �� que a implementa����o de um modelo SARIMA �� imediata, e previs��es a partir dele s��o obtidas de forma simples e direta.

Estima����o de pr��mio de risco de startup

Por defini����o as empresas startups est��o expostas a mais riscos e vulnerabilidades que empresas maduras e j�� estabelecidas no mercado. O objetivo do presente estudo �� identificar, aplicar e testar uma poss��vel metodologia para calcular pr��mio de risco adicional para startups. Para tanto este trabalho desenvolve um estudo de caso no qual a conhecida metodologia para c��lculo de pr��mio de risco de tamanho da Morningstar �� aplicada a uma startup americana. A ader��ncia da metodologia proposta neste estudo �� testada pela metodologia do filtro de Kalman, que calcula o pr��mio de risco por tamanho variando ao longo do tempo. Os resultados encontrados s��o similares em ambas as metodologias. De forma que �� poss��vel concluir que a metodologia da Morningstar, quando aplicada para calcular pr��mio por tamanho variante ao longo do tempo �� robusta.

Modelo Nelson-Siegel din��mico da estrutura a termo da taxa de juros com fatores ex��genos macroecon��micos: uma aplica����o ao mercado brasileiro

A tradicional representa����o da estrutura a termo das taxas de juros em tr��s fatores latentes (n��vel, inclina����o e curvatura) teve sua formula����o original desenvolvida por Charles R. Nelson e Andrew F. Siegel em 1987. Desde ent��o, diversas aplica����es v��m sendo desenvolvidas por acad��micos e profissionais de mercado tendo como base esta classe de modelos, sobretudo com a inten����o de antecipar movimentos nas curvas de juros. Ao mesmo tempo, estudos recentes como os de Diebold, Piazzesi e Rudebusch (2010), Diebold, Rudebusch e Aruoba (2006), Pooter, Ravazallo e van Dijk (2010) e Li, Niu e Zeng (2012) sugerem que a incorpora����o de informa����o macroecon��mica aos modelos da ETTJ pode proporcionar um maior poder preditivo. Neste trabalho, a vers��o din��mica do modelo Nelson-Siegel, conforme proposta por Diebold e Li (2006), foi comparada a um modelo an��logo, em que s��o inclu��das vari��veis ex��genas macroecon��micas. Em paralelo, foram testados dois m��todos diferentes para a estima����o dos par��metros: a tradicional abordagem em dois passos (Two-Step DNS), e a estima����o com o Filtro de Kalman Estendido, que permite que os par��metros sejam estimados recursivamente, a cada vez que uma nova informa����o �� adicionada ao sistema. Em rela����o aos modelos testados, os resultados encontrados mostram-se pouco conclusivos, apontando uma melhora apenas marginal nas estimativas dentro e fora da amostra quando as vari��veis ex��genas s��o inclu��das. J�� a utiliza����o do Filtro de Kalman Estendido mostrou resultados mais consistentes quando comparados ao m��todo em dois passos para praticamente todos os horizontes de tempo estudados.

Estimating brazilian monthly GDP: a state-space approach

This paper has several original contributions. The rst is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we nally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil - the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, which may not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.

A monthly indicator of Brazilian GDP. The Brazilian business cycle and growth cycle

This paper constructs an indicator of Brazilian GDP at the monthly ftequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle were explicitly modeled within nonlinear ftameworks. In particular, a Markov switching dynarnic factor model was used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict ali recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined. The estimated indicator displays a better in-sample and out-of-sample predictive performance in forecasting growth rates of real GDP, compared to a linear autoregressive model for GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.

Taylor rule with hidden states

This work evaluates empirically the Taylor rule for the US and Brazil using Kalman Filter and Markov-Switching Regimes. We show that the parameters of the rule change significantly with variations in both output and output gap proxies, considering hidden variables and states. Such conclusions call naturally for robust optimal monetary rules. We also show that Brazil and US have very contrasting parameters, first because Brazil presents time-varying intercept, second because of the rigidity in the parameters of the Brazilian Taylor rule, regardless the output gap proxy, data frequency or sample data. Finally, we show that the long-run inflation parameter of the US Taylor rule is less than one in many periods, contrasting strongly with Orphanides (forthcoming) and Clarida, Gal��i and Gertler (2000), and the same happens with Brazilian monthly data.

Price discovery using a regime-sensitive cointegration approach

This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.

Estimating Brazilian monthly GDP: a state-space approach

This paper has several original contributions. The rst is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we nally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil- the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, whichmay not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.

Estimating Brazilian monthly GDP: a state-space approach

The first contribution of this paper is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). The second contribution, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), is to propose and test a myriad of inter-polation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we finally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil - the Brazilian Economic Activity Index - (IBC-Br). We found that our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, which may not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. The third contribution is to illustrate, in a nowcasting and forecasting exercise, the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.

Balance-bot

Research on inverted pendulum has gained momentum over the last decade on a number of robotic laboratories over the world; due to its unstable proprieties is a good example for control engineers to verify a control theory. To verify that the pendulum can balance we can make some simulations using a closed-loop controller method such as the linear quadratic regulator or the proportional���integral���derivative method. Also the idea of robotic teleoperation is gaining ground. Controlling a robot at a distance and doing that precisely. However, designing the tool to takes the best benefit of the human skills while keeping the error minimal is interesting, and due to the fact that the inverted pendulum is an unstable system it makes a compelling test case for exploring dynamic teleoperation. Therefore this thesis focuses on the construction of a two-wheel inverted pendulum robot, which sensor we can use to do that, how they must be integrated in the system and how we can use a human to control an inverted pendulum. The inverted pendulum robot developed employs technology like sensors, actuators and controllers. This Master thesis starts by presenting an introduction to inverted pendulums and some information about related areas such as control theory. It continues by describing related work in this area. Then we describe the mathematical model of a two-wheel inverted pendulum and a simulation made in Matlab. We also focus in the construction of this type of robot and its working theory. Because this is a mobile robot we address the theme of the teleoperation and finally this thesis finishes with a general conclusion and ideas of future work.

Real-Time Visual SLAM Using Pre - Existing Floor Lines as Landmarks and a Single Camera

SANTANA, Andr�� M.; SANTIAGO, Gutemberg S.; MEDEIROS, Adelardo A. D. Real-Time Visual SLAM Using Pre-Existing Floor Lines as Landmarks and a Single Camera. In: CONGRESSO BRASILEIRO DE AUTOM��TICA, 2008, Juiz de Fora, MG. Anais... Juiz de Fora: CBA, 2008.

Sistema de detec����o e isolamento de falhas em sistemas din��micos baseado em identifica����o param��trica

The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text