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 estratégia dirigida a modelos e baseada em linguagem de descrição arquitetural para linhas de produtos de software

Model-oriented strategies have been used to facilitate products customization in the software products lines (SPL) context and to generate the source code of these derived products through variability management. Most of these strategies use an UML (Unified Modeling Language)-based model specification. Despite its wide application, the UML-based model specification has some limitations such as the fact that it is essentially graphic, presents deficiencies regarding the precise description of the system architecture semantic representation, and generates a large model, thus hampering the visualization and comprehension of the system elements. In contrast, architecture description languages (ADLs) provide graphic and textual support for the structural representation of architectural elements, their constraints and interactions. This thesis introduces ArchSPL-MDD, a model-driven strategy in which models are specified and configured by using the LightPL-ACME ADL. Such strategy is associated to a generic process with systematic activities that enable to automatically generate customized source code from the product model. ArchSPLMDD strategy integrates aspect-oriented software development (AOSD), modeldriven development (MDD) and SPL, thus enabling the explicit modeling as well as the modularization of variabilities and crosscutting concerns. The process is instantiated by the ArchSPL-MDD tool, which supports the specification of domain models (the focus of the development) in LightPL-ACME. The ArchSPL-MDD uses the Ginga Digital TV middleware as case study. In order to evaluate the efficiency, applicability, expressiveness, and complexity of the ArchSPL-MDD strategy, a controlled experiment was carried out in order to evaluate and compare the ArchSPL-MDD tool with the GingaForAll tool, which instantiates the process that is part of the GingaForAll UML-based strategy. Both tools were used for configuring the products of Ginga SPL and generating the product source code

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

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)

Jogo da Minoria: um modelo baseado em agentes aplicado ao mercado financeiro

Nos últimos anos houve uma contribuição significativa dos físicos para a construção de um tipo de modelo baseado em agentes que busca reproduzir, em simulação computacional, o comportamento do mercado financeiro. Esse modelo, chamado Jogo da Minoria consiste de um grupo de agentes que vão ao mercado comprar ou vender ativos. Eles tomam decisões com base em estratégias e, por meio delas, os agentes estabelecem um intrincado jogo de competição e coordenação pela distribuição da riqueza. O modelo tem demonstrado resultados bastante ricos e surpreendentes, tanto na dinâmica do sistema como na capacidade de reproduzir características estatísticas e comportamentais do mercado financeiro. Neste artigo, são apresentadas a estrutura e a dinâmica do Jogo da Minoria, bem como as contribuições recentes relacionadas ao Jogo da Minoria denominado de Grande Canônico, que é um modelo mais bem ajustado às características do mercado financeiro e reproduz as regularidades estatísticas do preço dos ativos chamadas fatos estilizados.

Increased corticosterone levels in mice subjected to the rat exposure test

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

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

Analyzing the effect of homogeneous frustration in protein folding

The energy landscape theory has been an invaluable theoretical framework in the understanding of biological processes such as protein folding, oligomerization, and functional transitions. According to the theory, the energy landscape of protein folding is funneled toward the native state, a conformational state that is consistent with the principle of minimal frustration. It has been accepted that real proteins are selected through natural evolution, satisfying the minimum frustration criterion. However, there is evidence that a low degree of frustration accelerates folding. We examined the interplay between topological and energetic protein frustration. We employed a Cα structure-based model for simulations with a controlled nonspecific energetic frustration added to the potential energy function. Thermodynamics and kinetics of a group of 19 proteins are completely characterized as a function of increasing level of energetic frustration. We observed two well-separated groups of proteins: one group where a little frustration enhances folding rates to an optimal value and another where any energetic frustration slows down folding. Protein energetic frustration regimes and their mechanisms are explained by the role of non-native contact interactions in different folding scenarios. These findings strongly correlate with the protein free-energy folding barrier and the absolute contact order parameters. These computational results are corroborated by principal component analysis and partial least square techniques. One simple theoretical model is proposed as a useful tool for experimentalists to predict the limits of improvements in real proteins. © 2013 Wiley Periodicals, Inc.