Modelo interno de risco de crédito de Basiléia II: possíveis impactos no capital mínimo exigido dos bancos

Com a implementação do Acordo de Basiléia II no Brasil, os grandes conglomerados bancários poderão utilizar o chamado modelo IRB (Internal Ratings Based) para cômputo da parcela de risco de crédito da exigência de capital. O objetivo desta dissertação é mensurar a diferença entre o capital mínimo exigido (e, conseqüentemente, do Índice de Basiléia) calculado pela abordagem IRB em relação à regulamentação atual. Para isso, foram estimadas probabilidades de inadimplência (PD) utilizando matrizes de transição construídas a partir dos dados da Central de Risco de Crédito (SCR) do Banco Central do Brasil. Os resultados indicam aumento da exigência de capital, ao contrário do ocorrido nos países do G-10.

Pricing and hedging of oil futures : a unifying approach

We develop and empirically test a continuous time equilibrium model for the pricing of oil futures. The model provides a link between no-arbitrage models and expectation oriented models. It highlights the role of inventories for the identification of different pricing regimes. In an empirical study the hedging performance of our model is compared with five other one- and two-factor pricing models. The hedging problem considered is related to Metallgesellschaft´s strategy to hedge long-term forward commitments with short-term futures. The results show that the downside risk distribution of our inventory based model stochastically dominates those of the other models.

Crowdfunding no Brasil: uma análise sobre as motivações de quem participa

Este trabalho procurou investigar as motivações para a participação de apoiadores no modelo de recompensa de crowdfunding no Brasil, sob a luz dos aspectos encontrados na pesquisa americana de Gerber e Hui (2014). Como a participação nesse modelo é voluntária, entendeu- se ser importante compreender os motivos que levam pessoas a apoiarem projetos. Acredita- se que este trabalho tenha atingido o que foi por ele proposto, deixando contribuições em diversos sentidos. A fim de aprofundar o entendimento desse novo fenômeno social, apresentou-se uma pesquisa qualitativa fundamentada em um estudo de caso múltiplo, em que os apoiadores eram a unidade de análise, nas três maiores plataformas de crowdfunding do Brasil: Queremos, Catarse e Benfeitoria. E, como fonte de informações para esta metodologia, optou-se pelo método qualitativo de entrevistas em profundidade com os elementos da unidade de análise. Foram realizadas 11 entrevistas com apoiadores, sendo 06 homens e 05 mulheres. O trabalho também teve o objetivo de conhecer melhor o cenário nacional desse mercado, a partir de entrevistas em profundidade com os fundadores das plataformas e um heavy user (mais de 140 projetos apoiados) do modelo. Após a consolidação e análise dos dados obtidos, verificou-se a presença das motivações encontradas nos estudos de Gerber (GERBER e HUI, 2014), porém com algumas ressalvas quanto a motivação “Fazer parte de uma comunidade”, explicitada a seguir. A pesquisa qualitativa refinou substancialmente a compreensão do que motiva apoiadores a participar de crowdfunding, incluindo aspectos importantes que devem ser levados em consideração quanto a práticas do mercado. Ao final, as conclusões e implicações deste estudo foram detalhadamente apresentadas.

Redes sociais e a lógica do desvio comportamental em relação às normas de trabalho

This paper aim to check a hypothesis that assumes several behaviors related to social work norm´s obeying as a phenomenon that can be explained by actor´s social network structure and the rational choice processes related to the social norm inside that network, principally the payoff´s analysis received by the closest actors, or neighbors, at a social situation. Taking the sociological paradigm of rational action theory as a basis, the focus is on a debate about the logic of social norms, from Émile Durkheim´s method to Jon Elster´s theory, but also including social network analysis´s variables according to Robert Hanneman; and also Vilfredo Pareto´s constants related to human sociability, at the aim to detect elements that can help the scholars to develop an agent based model which could explain the sociological problem of deviance by a better way than the common sense´s view about morality and ethics at a social work environment

Problematizando a Reforma Psiquiátrica na atualidade: a saúde mental como campo da práxis

Mental Health, in the form of the Psychiatric Reform, and the Anti-Asylum Movement do not ignore the production of knowledge about that field, mainly due to the consolidation of Public Health as a field of knowledge. The article explores some authors who consider Mental Health as a new field of knowledge, introducing a new paradigm in the perception of health - Disease and Care -; however, the goal is to introduce Psychosocial Care as a means to enforce the transdisciplinary and multiprofessional practices. The possibility is that mental health produces developments in Health, consolidating the public policies. In practice, the hospital-centered and drug-based model still predominates, and there are setbacks to be overcome by taking advantage of loopholes capable of breaking with what is instituted.

Processos cognitivos que operam na configuração de narrativas: uma pesquisa exploratória dos fenômenos que subjazem à compreensão de textos

This paper investigates the cognitive processes that operate in understanding narratives in this case, the novel Macunaíma, by Mário de Andrade. Our work belongs to the field of Embodied-based Cognitive Linguistics and, due to its interdisciplinary nature, it dialogues with theoretical and methodological frameworks of Psycholinguistics, Cognitive Psychology and Neurosciences. Therefore, we adopt an exploratory research design, recall and cloze tests, adapted, with postgraduation students, all native speakers of Brazilian Portuguese. The choice of Macunaíma as the novel and initial motivation for this proposal is due to the fact it is a fantastic narrative, which consists of events, circumstances and characters that are clearly distant types from what is experienced in everyday life. Thus, the novel provides adequate data to investigate the configuration of meaning, within an understanding-based model. We, therefore, seek, to answer questions that are still, generally, scarcely explored in the field of Cognitive Linguistics, such as to what extent is the activation of mental models (schemas and frames) related to the process of understanding narratives? How are we able to build sense even when words or phrases are not part of our linguistic repertoire? Why do we get emotionally involved when reading a text, even though it is fiction? To answer them, we assume the theoretical stance that meaning is not in the text, it is constructed through language, conceived as a result of the integration between the biological (which results in creating abstract imagery schemes) and the sociocultural (resulting in creating frames) apparatus. In this sense, perception, cognitive processing, reception and transmission of the information described are directly related to how language comprehension occurs. We believe that the results found in our study may contribute to the cognitive studies of language and to the development of language learning and teaching methodologies

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Uma análise da aplicação do modelo de Rede Neural RePART em Comitês de classificadores

RePART (Reward/Punishment ART) is a neural model that constitutes a variation of the Fuzzy Artmap model. This network was proposed in order to minimize the inherent problems in the Artmap-based model, such as the proliferation of categories and misclassification. RePART makes use of additional mechanisms, such as an instance counting parameter, a reward/punishment process and a variable vigilance parameter. The instance counting parameter, for instance, aims to minimize the misclassification problem, which is a consequence of the sensitivity to the noises, frequently presents in Artmap-based models. On the other hand, the use of the variable vigilance parameter tries to smoouth out the category proliferation problem, which is inherent of Artmap-based models, decreasing the complexity of the net. RePART was originally proposed in order to minimize the aforementioned problems and it was shown to have better performance (higer accuracy and lower complexity) than Artmap-based models. This work proposes an investigation of the performance of the RePART model in classifier ensembles. Different sizes, learning strategies and structures will be used in this investigation. As a result of this investigation, it is aimed to define the main advantages and drawbacks of this model, when used as a component in classifier ensembles. This can provide a broader foundation for the use of RePART in other pattern recognition applications

X-ARM: um modelo de representação de artefatos de software

A great challenge of the Component Based Development is the creation of mechanisms to facilitate the finding of reusable assets that fulfill the requirements of a particular system under development. In this sense, some component repositories have been proposed in order to answer such a need. However, repositories need to represent the asset characteristics that can be taken into account by the consumers when choosing the more adequate assets for their needs. In such a context, the literature presents some models proposed to describe the asset characteristics, such as identification, classification, non-functional requirements, usage and deployment information and component interfaces. Nevertheless, the set of characteristics represented by those models is insufficient to describe information used before, during and after the asset acquisition. This information refers to negotiation, certification, change history, adopted development process, events, exceptions and so on. In order to overcome this gap, this work proposes an XML-based model to represent several characteristics, of different asset types, that may be employed in the component-based development. Besides representing metadata used by consumers, useful for asset discovering, acquisition and usage, this model, called X-ARM, also focus on helping asset developers activities. Since the proposed model represents an expressive amount of information, this work also presents a tool called X-Packager, developed with the goal of helping asset description with X-ARM

Antimicrobial use and incidence of multidrug-resistant Pseudomonas aeruginosa in a teaching hospital: an ecological approach

Introduction: Multidrug-resistant Pseudomonas aeruginosa is a major threat in healthcare settings. The use of antimicrobials can influence the incidence of resistant strains by direct and indirect mechanisms. The latter can be addressed by ecological studies. Methods: Our group attempted to analyze the relation between the use of antipseudomonal drugs and the incidence of MDR-PA among 18 units from a 400-bed teaching hospital. The study had a retrospective, ecological design, comprising data from 2004 and 2005. Data on the use of four antimicrobials (amikacin, ciprofloxacin, ceftazidime and imipenem) were tested for correlation with the incidence of MDR-PA (defined as isolates resistant to the four antimicrobials of interest) in clinical cultures. Univariate and multivariate linear regression analyses were performed. Results: Significant correlations were determined between use and resistance for all antimicrobials in the univariate analysis: amikacin (standardized correlation coefficient = 0.73, p = 0.001); ciprofloxacin (0.71, p = 0.001); ceftazidime (0.61, p = 0.007) and imipenem (0.87, p < 0.001). In multivariate analysis, only imipenem (0.67, p = 0.01) was independently related to the incidence of multidrug-resistant strains. Conclusions: These findings share similarities with those reported in individual-based observational studies, with possible implications for infection control.

Sete motivações teóricas para o uso da modelagem baseada no indivíduo em ecologia

A modelagem baseada no indivíduo tem sido crescentemente empregada para analisar processos ecológicos, desenvolver e avaliar teorias, bem como para fins de manejo da vida silvestre e conservação. Os modelos baseados no indivíduo (MBI) são bastante flexíveis, permitem o uso detalhado de parâmetros com maior significado biológico, sendo portanto mais realistas do que modelos populacionais clássicos, mais presos dentro de um rígido formalismo matemático. O presente artigo apresenta e discute sete razões para a adoção dos MBI em estudos de simulação na Ecologia: (1) a inerente complexidade de sistemas ecológicos, impassíveis de uma análise matemática formal; (2) processos populacionais são fenômenos emergentes, resultando das interações entre seus elementos constituintes (indivíduos) e destes com o meio; (3) poder de predição; (4) a adoção definitiva, por parte da Ecologia, de uma visão evolutiva; (5) indivíduos são entidades discretas; (6) interações são localizadas no espaço e (7) indivíduos diferem entre si.

Impacts of Climate Change and the End of Deforestation on Land Use in the Brazilian Legal Amazon

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Efeitos do estado e especificidade do treinamento aeróbio na relação %VO2max versus %FCmax durante o ciclismo

OBJETIVO: Determinar os efeitos do estado e especificidade de treinamento aeróbio na relação entre o percentual do consumo máximo de oxigênio (%VO2max) e o percentual da frequência cardíaca máxima (%FCmax) durante o exercício incremental realizado no cicloergômetro. MÉTODOS: Sete corredores, 9 ciclistas, 11 triatletas e 12 sedentários, todos do sexo masculino e aparentemente saudáveis, foram submetidos a um teste incremental até a exaustão no cicloergômetro. Regressões lineares entre %VO2max e %FCmax foram determinadas para cada indivíduo. Com base nessas regressões, foram calculados %FCmax correspondentes a determinados %VO2max (50, 60, 70, 80 e 90%) de cada participante. RESULTADOS: Não foram encontradas diferenças significantes entre todos os grupos nos %FCmax para cada um dos %VO2max avaliados. Analisando-se os voluntários como um único grupo, as médias dos %FCmax correspondentes a 50, 60, 70, 80 e 90% %VO2max foram 67, 73, 80, 87, e 93%, respectivamente. CONCLUSÃO: Nos grupos analisados, a relação entre o %VO2max e %FCmax durante o exercício incremental no ciclismo não é dependente do estado e especificidade do treinamento aeróbio.

Edge detection and noise removal by use of a partial differential equation with automatic selection of parameters

This work deals with noise removal by the use of an edge preserving method whose parameters are automatically estimated, for any application, by simply providing information about the standard deviation noise level we wish to eliminate. The desired noiseless image u(x), in a Partial Differential Equation based model, can be viewed as the solution of an evolutionary differential equation u t(x) = F(u xx, u x, u, x, t) which means that the true solution will be reached when t ® ¥. In practical applications we should stop the time ''t'' at some moment during this evolutionary process. This work presents a sufficient condition, related to time t and to the standard deviation s of the noise we desire to remove, which gives a constant T such that u(x, T) is a good approximation of u(x). The approach here focused on edge preservation during the noise elimination process as its main characteristic. The balance between edge points and interior points is carried out by a function g which depends on the initial noisy image u(x, t0), the standard deviation of the noise we want to eliminate and a constant k. The k parameter estimation is also presented in this work therefore making, the proposed model automatic. The model's feasibility and the choice of the optimal time scale is evident through out the various experimental results.

The Origin of Nonmonotonic Complex Behavior and the Effects of Nonnative Interactions on the Diffusive Properties of Protein Folding

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)