Alessandra de Ávila Montini

The Aftermarket Performance of Initial Public Offerings: The Brazilian Experience

ABSTRACT This article analyzes the behavior of share prices in the first aftermarket year at the moment the company goes public for the first time, specifically in the case of Brazil. First, we present evidence drawn from the international capital markets and how returns may be characterized. Next, we analyze current Brazilian capital markets and returns on shares for 30 companies that went public in the country between January 2004 and July 2006. We found that Brazilian initial public offerings averaged large positive returns both in the short-term and for a one-year period. RESUMEN. Este trabajo busca evidenciar cómo el precio de las acciones en IPOs tiende a comportarse en el mercado secundario durante el primero año de negociaciones, específicamente en el caso brasileño. En primer lugar, se presentan las evidencias en el mercado internacional de capitales y mostramos que tipo de retornos se suele obtener. Luego, se lleva a cabo un análisis del mercado de capitales brasileño y de la rentabilidad en 30 IPOs, ocurridos entre enero de 2004 y julio de 2006 en el país. Se nota que el desempeño de IPOs en Brasil tiene fuertes tendencias positivas, tanto para el corto plazo como para un año. RESUMEO. Este estudo analisa o comportamento dos preços de ações no primeiro ano após a abertura de capital de uma empresa, especificamente no caso do Brasil. Primeiramente, apresentamos dados do mercado de capitais internacionais e como os retornos tendem a ser. Depois disto, analisamos o mercado de capitais brasileiro e os retornos das ações de 30 empresas que abriram o capital no país entre janeiro de 2004 e julho de 2006. Constatamos que os lançamentos de ações (IPOs) brasileiros proporcionaram, em média, retornos positivos grandes a curto prazo e também por um período de um ano.

A Chi-Square Methodology Applied in Deviations Control of Project Plan to Support the RIMAM Model

This paper describes a Hybrid Chi-Squared methodology of Project Plan deviations identification, including those for multiple deviations in a Project Plan system. The sampling methodology was used to analyze similarity, together with a statistical optimization methodology for Chi-Squared, to improve the existing methodology used to forecast data in the Project Plan phase. The created sampling methodology was utilized for learning activities of Project Plan, in order to detect deviations. This Chi-Squared methodology was employed by empirical results. The results have shown that the selection strategy identify better forecasting approach between two different proposals, aiming to provide the forecasting process of Project Plan, presenting better precisions based on the diagnose deviations detection, within this Chi-Squared methodology.

A Sampling Diagnostics Model for Neural System Training Optimization

This paper describes a hybrid-sampling model for bank fraud diagnosis, including those for multiple frauds in a banking system. The Multi-Layer Perceptron (MLP) network was used to analyze similarity, together with a statistical optimization model for sampling, to reduce the volume of used data in the diagnostics phase. The created MLP was utilized for banking transactions learning, in order to detect frauds. This neural network was tested with different configurations to improve diagnosis. The hybrid-sampling model was also employed to improve training results. The results have shown that the optimization strategy reduced the database volume and improved the learning process, presenting similar precisions to diagnose frauds detection, within this hybrid-sampling model.

Service-Centered Operation Methodology (MOCA) Application Supported by Computer Science to Improve Continuously Care Quality in Public Services

The proposal of a Corporate Governance Model called Service-Focused Operation Methodology (MOCA) was carried out, applied in Public and Private Partnerships (PPP) to improve services quality offered by the Brazilian states. This PPP model enabled several Service Center (in portuguese Central de Atendimento—CA) implementation projects supported by several multidisciplinary knowledge areas that involve projects and governments. However, this article explored an aspect of how a MOCA’s use with new technologies embedded in projects provide continuous improvements in results. In this case, for example, a demand study was applied to Planning and Control of Operations (PCO) in a use of Research and Development (RD MOCA applied in PCO; obtained from stabilized proof of concepts; providing data collection and more accurate performance information in each CA, collected directly by an ERP used. From these data, the design of service production lines was performed using the following methodologies: (1) Descriptive Statistics, (2) Temporal Series and (3) Temporal Underground Neural Networks (ANNT). A Temporal Neural Networks (ANNT) was obtained, using recursive corrections in demand balancing by attendant performance. Using these technologies, a more accurate performance forecast to estimates attendants work was achieved in order to obtain a more realistic operational planning.

A Stratified Sampling Algorithm for Artificial Neural Networks

Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) are widely applied in a variety market segments to handle with real complex problems. The ability to deal with tasks in real time is essential in an environment that uses large volume do information available. In each new project, a decision-making system using ANN with time reduction and data processing is a key issue to test various learning algorithms; containing a variety of parameters when using this technology. From this starting point, the MLPs used data collected from a specific phenomenon and, based on statistical estimators, applied a data extraction algorithm for stratified sampling, aiming to reduce the time of ANN processing. In this context, this work proposes a Stratified Sampling algorithm (SSA), which was developed to minimize processing MLPs time without losing coverage and assertiveness, when comparing with training conducted on a population database. The case study consisted of a ANN performance influence with a population database and with its sample data obtained by the SSA model. This procedure with the RNAs aimed to evaluate the following properties: (1) meet the pre-established criteria of reliability of the model; (2) have a computer-automated procedure; (3) sort and select records more correlated, and (4) maintain sampling results within a track of assertiveness of total results obtained. From the realization of this case study, it was possible to identify the following gains made by the (1) reduction of ANN processing time by providing: (2) optimization of processing time; (3) automatic network selection; and (4) automatic parameters selection for training algorithms.

Tratamento de dados em alta frequência e estimação de medidas de volatilidade: um estudo de caso para petr4

O artigo tem objetivo de analisar o tratamento de dados em alta frequencia para a estimacao de medidas de volatilidade percebida (realized volatility - RV). Para atingir os objetivos, buscou-se analisar as metodologias para limpeza de outliers e agregacao dos precos. Para os metodos de agregacao, consideraram-se as seguintes formas de amostragem: ultimo preco negociado; preco ponderado pelo volume; preco ponderado pelo logaritmo do volume; preco ponderado pelo numero de negociacoes; mediana dos precos e precos de maior volume associado. Foram estudadas as metricas RCov (sensivel a problemas de microestrutura), rOWCov, medRV, minRV e rRTSCov, consideradas robustas a saltos e ruidos de microestrutura. Quanto aos resultados, observou-se que a remocao de outliers nao influenciou de maneira significativa o processo de estimacao da volatilidade percebida. Em relacao a analise de agregacao dos precos, por meio de uma simples mudanca na metodologia, observaram-se diferencas significativas nas estimativas das volatilidades percebidas. Para a analise dos metodos de agregacao, considerando as seis formas de amostragem, verificou-se que todas as medidas foram sensiveis as mudancas na forma de amostragem para agregar os precos. Do ponto de vista pratico, gerenciar dados em alta frequencia e um desafio devido a necessidade de manipulacao de grandes bases. Por esse motivo, a nao correcao de possiveis problemas nos bancos de dados pode gerar estimativas de variabilidade imprecisas para a gestao de riscos. O artigo contribui por realizar uma revisao dos estimadores da volatilidade percebida mais recentes, buscando comparar a consistencia em relacao as diferentes formas de agregacao e tratamento da serie de precos.

The cost of living in the best livable cities in the world: a brief predictive quantitative analysis

There are a lot of studies, papers, summaries, reports, and articles regarding the cost of living in different cities around the world. Although these studies are rich and robust, only the final results are published, like cities rankings, or summaries of top cities and lowest ranking cities. This papers goal is to study the most livable cities using living cost data. To accomplish this objective, a cluster analysis has been conducted using 2015 prices data and three clusters were obtained in result: high, medium and low cost. In addition, a multinomial logistic regression using 2014 prices data was adjusted to predict the cluster each city would fall into. This model could help companies or even people to decide which city to move to in order to decrease living costs. It can be important to avoid a wrong decision in case of an upcoming cluster change for a determined city.

A Meta-algorithm for Planning Optimization in a software Production Line

Nowadays there are various forms for performing software design, planning, and manufacturing. To each of these it is required a proper process definition to achieve metrological forecasting goal. In this investigation, the research area is Artificial Intelligence algorithms applied to projects for Production Lines design, characterized as Manufacturing Cells. In this type of approach the design project is aimed at improving the understanding and assertiveness in the planning of the operation, through an Intelligent Agent use. The Intelligent Agent was proposed as a model-driven and was aimed at identifying the code capacity installed in a specific programming language.

Stability of stock prices in the Brazilian capital market: a study applying neural networks and the Lyapunov exponent

En este trabajo se estudia la estabilidad de los precios de mercado de acciones para dos categorias de empresas: industrial y otros sectores, en el periodo comprendido entre el 2 de enero de 1995 y el 2 de enero de 2008. Es decir, se analiza la estabilidad de los precios de mercado para el periodo anterior a la crisis de 2008, que comenzo con los titulos subprime de Estados Unidos. Se analizan las implicaciones de la estabilidad del proceso de generacion de retorno por paradigmas de racionalidad. La verificacion de la estabilidad se realizo por medio de la aplicacion de exponentes de Lyapunov. Se presentan los resultados sobre la estabilidad de los precios para las dos categorias de empresas: las industrias, formadas por Acesita, Ambev, Aracruz, Braskem, Duratex, Fosfertil, Gerdau, Klabin, Randon, Sadia, Sid Nacional, Souza Cruz, Unipar, Usiminas, y VCP; y las empresas de la categoria otros sectores, formadas por Ampla Energia, Bradesco, Brasil Telecom, Cemig, Eletrobras, Itaubanco, Itausa, JB Duarte, Pronor, Besc, Alfa Financeira e Inepar. Un diagrama de dispersion del logaritmo de los precios de registro sin tendencia frente a los retornos de las dos categorias (o carteras) mostro un patron caotico en los precios de las acciones, lo que indica la presencia de no linealidad. Sin embargo, en el calculo de los exponentes de Lyapunov, se obtuvieron valores negativos. Esto indica que las fluctuaciones de las treinta empresas analizadas resultan de procesos de difusion en lugar de dinamicas no lineales. Se estudia la racionalidad del comportamiento de los precios por medio de la verificacion de los residuos generados a partir de las estimaciones de los modelos ARMA, NAIVE y de redes neuronales feedforward.