573 resultados para predictability


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This paper investigates the predictions of an inflationary phase starting from a homogeneous and anisotropic universe of the Bianchi I type. After discussing the evolution of the background spacetime, focusing on the number of e-folds and the isotropization, we solve the perturbation equations and predict the power spectra of the curvature perturbations and gravity waves at the end of inflation. The main features of the early anisotropic phase is (1) a dependence of the spectra on the direction of the modes, (2) a coupling between curvature perturbations and gravity waves and (3) the fact that the two gravity wave polarizations do not share the same spectrum on large scales. All these effects are significant only on large scales and die out on small scales where isotropy is recovered. They depend on a characteristic scale that can, but a priori must not, be tuned to some observable scale. To fix the initial conditions, we propose a procedure that generalizes the one standardly used in inflation but that takes into account the fact that the WKB regime is violated at early times when the shear dominates. We stress that there exist modes that do not satisfy the WKB condition during the shear-dominated regime and for which the amplitude at the end of inflation depends on unknown initial conditions. On such scales, inflation loses its predictability. This study paves the way for the determination of the cosmological signature of a primordial shear, whatever the Bianchi I spacetime. It thus stresses the importance of the WKB regime to draw inflationary predictions and demonstrates that, when the number of e-folds is large enough, the predictions converge toward those of inflation in a Friedmann-Lemaitre spacetime but that they are less robust in the case of an inflationary era with a small number of e-folds.

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Nowadays, noninvasive methods of diagnosis have increased due to demands of the population that requires fast, simple and painless exams. These methods have become possible because of the growth of technology that provides the necessary means of collecting and processing signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this paper is to characterize healthy and pathological voice signals with the aid of relative entropy measures. Phase space reconstruction technique is also used as a way to select interesting regions of the signals. Three groups of samples were used, one from healthy individuals and the other two from people with nodule in the vocal fold and Reinke`s edema. All of them are recordings of sustained vowel /a/ from Brazilian Portuguese. The paper shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Relative entropy is well suited due to its sensibility to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. The results showed that the pathological groups had higher entropy values in accordance with other vocal acoustic parameters presented. This suggests that these techniques may improve and complement the recent voice analysis methods available for clinicians. (C) 2008 Elsevier Inc. All rights reserved.

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This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

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Distributed systems comprised of autonomous self-interested entities require some sort of control mechanism to ensure the predictability of the interactions that drive them. This is certainly true in the aerospace domain, where manufacturers, suppliers and operators must coordinate their activities to maximise safety and profit, for example. To address this need, the notion of norms has been proposed which, when incorporated into formal electronic documents, allow for the specification and deployment of contract-driven systems. In this context, we describe the CONTRACT framework and architecture for exactly this purpose, and describe a concrete instantiation of this architecture as a prototype system applied to an aerospace aftercare scenario.

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O objetivo deste artigo é examinar como as decisões de taxa de juros básica no Brasil (um forte mecanismo de sinalização em política monetária) afetam a estrutura a termo da curva de juros. Diferentemente de outros trabalhos sobre o caso brasileiro, este avalia a evolução da previsibilidade das decisões de política monetária após a introdução do regime de metas de inflação e, também, compara esta evolução com outros países. A metodologia utilizada é um estudo de eventos em 2 períodos distintos: entre jan/2000 e ago/2003, após a introdução do regime de metas de inflação, e entre set/2003 e jul/2008, quando o regime de metas atinge certa maturidade. Os resultados indicam que: 1) os efeitos surpresa na curva de juros estão menores; 2) o poder explicativo das ações de política monetária aumentou; 3) o mercado tem efetuado o ajuste das expectativas de decisão sobre a taxa de juros com antecedência de 3 dias; 4) a previsibilidade e transparência das decisões de política monetária no Brasil aumentaram e estão próximas daquelas observadas nos EUA e Alemanha e superiores ao caso italiano e britânico.

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Este trabalho tem como objetivo descrever como os fatores racionais, organizacionais e políticos influenciam o processo decisório no Exército Brasileiro para a obtenção de Materiais de Emprego Militar (MEM). Utilizou-se a abordagem proposta no trabalho de Allison para análise das decisões durante a crise dos mísseis de Cuba em 1962. Os fatores racionais utilizados foram: cálculo, maximização de valor, impessoalidade, escolha racional e racionalidade limitada. Os fatores organizacionais foram: padrões e processos organizacionais, segmentação do problema, coordenação e controle centralizados, flexibilidade limitada, previsibilidade e cultura organizacional. Os fatores políticos utilizados foram: conflito, poder, negociação, contingências, cooptação, interesses e influência externa. Os resultados permitiram constatar que o processo decisório, mesmo ocorrendo em uma organização baseada em pressupostos racionais, sofre influência de fatores organizacionais e políticos.

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The evolution of integrated circuits technologies demands the development of new CAD tools. The traditional development of digital circuits at physical level is based in library of cells. These libraries of cells offer certain predictability of the electrical behavior of the design due to the previous characterization of the cells. Besides, different versions of each cell are required in such a way that delay and power consumption characteristics are taken into account, increasing the number of cells in a library. The automatic full custom layout generation is an alternative each time more important to cell based generation approaches. This strategy implements transistors and connections according patterns defined by algorithms. So, it is possible to implement any logic function avoiding the limitations of the library of cells. Tools of analysis and estimate must offer the predictability in automatic full custom layouts. These tools must be able to work with layout estimates and to generate information related to delay, power consumption and area occupation. This work includes the research of new methods of physical synthesis and the implementation of an automatic layout generation in which the cells are generated at the moment of the layout synthesis. The research investigates different strategies of elements disposition (transistors, contacts and connections) in a layout and their effects in the area occupation and circuit delay. The presented layout strategy applies delay optimization by the integration with a gate sizing technique. This is performed in such a way the folding method allows individual discrete sizing to transistors. The main characteristics of the proposed strategy are: power supply lines between rows, over the layout routing (channel routing is not used), circuit routing performed before layout generation and layout generation targeting delay reduction by the application of the sizing technique. The possibility to implement any logic function, without restrictions imposed by a library of cells, allows the circuit synthesis with optimization in the number of the transistors. This reduction in the number of transistors decreases the delay and power consumption, mainly the static power consumption in submicrometer circuits. Comparisons between the proposed strategy and other well-known methods are presented in such a way the proposed method is validated.

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This paper builds a simple, empirically-verifiable rational expectations model for term structure of nominal interest rates analysis. It solves an stochastic growth model with investment costs and sticky inflation, susceptible to the intervention of the monetary authority following a policy rule. The model predicts several patterns of the term structure which are in accordance to observed empirical facts: (i) pro-cyclical pattern of the level of nominal interest rates; (ii) countercyclical pattern of the term spread; (iii) pro-cyclical pattern of the curvature of the yield curve; (iv) lower predictability of the slope of the middle of the term structure; and (v) negative correlation of changes in real rates and expected inflation at short horizons.

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We build a pricing kernel using only US domestic assets data and check whether it accounts for foreign markets stylized facts that escape consumption based models. By interpreting our stochastic discount factor as the projection of a pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets. We address predictability issues associated with the forward premium puzzle by: i) using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations, and; ii) by pricing Lustig and Verdelhan (2007)'s foreign currency portfolios. Our results indicate that the relevant state variables that explain foreign-currency market asset prices are also the driving forces behind U.S. domestic assets behavior.

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Using information on US domestic financial data only, we build a stochastic discount factor—SDF— and check whether it accounts for foreign markets stylized facts that escape consumption based models. By interpreting our SDF as the projection of a pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. We address predictability issues associated with the forward premium puzzle by: i) using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations, and; ii) by pricing Lustig and Verdelhan (2007)’s foreign currency portfolios. Our results indicate that the relevant state variables that explain foreign-currency market asset prices are also the driving forces behind U.S. domestic assets behavior.

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Using information on US domestic financial data only, we build a stochastic discount factor—SDF— and check whether it accounts for foreign markets stylized facts that escape consumption based models. By interpreting our SDF as the projection of a pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. We address predictability issues associated with the forward premium puzzle by: i) using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations, and; ii) by comparing this out-of-sample results with the one obtained performing an in-sample exercise, where the return-based SDF captures sources of risk of a representative set of developed and emerging economies government bonds. Our results indicate that the relevant state variables that explain foreign-currency market asset prices are also the driving forces behind U.S. domestic assets behavior.

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We build a stochastic discount factor—SDF— using information on US domestic financial data only, and provide evidence that it accounts for foreign markets stylized facts that escape SDF’s generated by consumption based models. By interpreting our SDF as the projection of the pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. In our tests, we address predictability, a defining feature of the Forward Premium Puzzle—FPP— by using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations both in the equity and the foreign markets.

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Esta dissertação investigou, no mercado brasileiro, se o atraso no ajuste de preços das ações de baixa liquidez gera previsibilidade do retorno dessas ações quando comparadas às mais líquidas. O interesse estava em confrontar os resultados com os existentes na literatura internacional que apresentavam esse efeito. Para tanto, utilizamos a metodologia proposta no artigo “Trading volume and cross-autocorrelations in stock returns”, de Chordia e Swaminathan (2000), onde foi analisada a Bolsa de Valores de Nova York (NYSE). Verificamos que, na Bolsa de Valores de São Paulo (BOVESPA), uma vez controlados pelo tamanho das empresas, os retornos, sejam diários ou semanais, de portfólios com maior liquidez antecipam os retornos dos portfólios de menor liquidez, mais explicitamente nos quartis com pequenas e médias empresas. Os efeitos de não sincronia nas negociações e as autocorrelações próprias não são suficientes para explicar os padrões de antecipação-defasagem observados nos retornos das ações, já que esses são mais significativamente influenciados pelo volume negociado. As diferenças na velocidade da incorporação de novas informações aos preços ocorrem porque as ações menos líquidas parecem responder mais lentamente a informações de mercado, pelo menos nos portfólios de empresas de menor tamanho. Dessa maneira, podemos afirmar que no Brasil, assim como nos Estados Unidos, a baixa liquidez induz um atraso no ajuste de preços das ações de pequenas e médias empresas capaz de gerar previsibilidade dos retornos dessas ações, sugerindo alguma ineficiência do mercado. Os resultados são interessantes, já que indicam que, tanto no mercado nacional quanto nos de países desenvolvidos, os volumes negociados possuem um papel significativo na velocidade em que os preços se ajustam, jogando uma luz sobre como eles podem se tornar mais eficientes.

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We build a stochastic discount factor—SDF— using information on US domestic financial data only, and provide evidence that it accounts for foreign markets stylized facts that escape SDF’s generated by consumption based models. By interpreting our SDF as the projection of the pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. In our tests, we address predictability, a defining feature of the Forward Premium Puzzle—FPP— by using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations both in the equity and the foreign markets.

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Há um grau de incerteza que é próprio da atividade jurisdicional e não é possível de ser mitigado em razão da própria natureza dos juízos a respeito de normas jurídicas. Decisões judiciais não são e nem podem ser absolutamente previsíveis. Há, contudo, um grau de incerteza que é evitável e o deve ser evitado, por ser prejudicial à saúde de um sistema jurídico. Outros pesquisadores no Brasil trabalharam com esta noção, e foi muito bem sucedida a formulação dos conceitos de incerteza estrutural e incerteza patológica de Joaquim Falcão, Luís Fernando Schuartz e Diego Arguelhes. Contudo, acreditamos que a concepção de incerteza patológica apresentada dos autores precisa de reformulação, especialmente para que pudesse ser verificada a partir de elementos da decisão judicial e não apenas de elementos sociológicos e psicológicos. Propomos uma concepção de incerteza patológica calcada na qualidade da fundamentação das decisões judiciais e concluímos que o cultivo de uma cultura de precedentes é necessária no Brasil para mitigar os efeitos nocivos da incerteza patológica.