994 resultados para non-Gaussian cage
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We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009
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Neste trabalho é dado ênfase à inclusão das incertezas na avaliação do comportamento estrutural, objetivando uma melhor representação das características do sistema e uma quantificação do significado destas incertezas no projeto. São feitas comparações entre as técnicas clássicas existentes de análise de confiabilidade, tais como FORM, Simulação Direta Monte Carlo (MC) e Simulação Monte Carlo com Amostragem por Importância Adaptativa (MCIS), e os métodos aproximados da Superfície de Resposta( RS) e de Redes Neurais Artificiais(ANN). Quando possível, as comparações são feitas salientando- se as vantagens e inconvenientes do uso de uma ou de outra técnica em problemas com complexidades crescentes. São analisadas desde formulações com funções de estado limite explícitas até formulações implícitas com variabilidade espacial de carregamento e propriedades dos materiais, incluindo campos estocásticos. É tratado, em especial, o problema da análise da confiabilidade de estruturas de concreto armado incluindo o efeito da variabilidade espacial de suas propriedades. Para tanto é proposto um modelo de elementos finitos para a representação do concreto armado que incorpora as principais características observadas neste material. Também foi desenvolvido um modelo para a geração de campos estocásticos multidimensionais não Gaussianos para as propriedades do material e que é independente da malha de elementos finitos, assim como implementadas técnicas para aceleração das avaliações estruturais presentes em qualquer das técnicas empregadas. Para o tratamento da confiabilidade através da técnica da Superfície de Resposta, o algoritmo desenvolvido por Rajashekhar et al(1993) foi implementado. Já para o tratamento através de Redes Neurais Artificias, foram desenvolvidos alguns códigos para a simulação de redes percéptron multicamada e redes com função de base radial e então implementados no algoritmo de avaliação de confiabilidade desenvolvido por Shao et al(1997). Em geral, observou-se que as técnicas de simulação tem desempenho bastante baixo em problemas mais complexos, sobressaindo-se a técnica de primeira ordem FORM e as técnicas aproximadas da Superfície de Resposta e de Redes Neurais Artificiais, embora com precisão prejudicada devido às aproximações presentes.
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Empirical evidence suggests that real exchange rate is characterized by the presence of near-unity and additive outliers. Recent studeis have found evidence on favor PPP reversion by using the quasi-differencing (Elliott et al., 1996) unit root tests (ERS), which is more efficient against local alternatives but is still based on least squares estimation. Unit root tests basead on least saquares method usually tend to bias inference towards stationarity when additive out liers are present. In this paper, we incorporate quasi-differencing into M-estimation to construct a unit root test that is robust not only against near-unity root but also against nonGaussian behavior provoked by assitive outliers. We re-visit the PPP hypothesis and found less evidemce in favor PPP reversion when non-Gaussian behavior in real exchange rates is taken into account.
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In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.
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The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.
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This paper constructs a unit root test baseei on partially adaptive estimation, which is shown to be robust against non-Gaussian innovations. We show that the limiting distribution of the t-statistic is a convex combination of standard normal and DF distribution. Convergence to the DF distribution is obtaineel when the innovations are Gaussian, implying that the traditional ADF test is a special case of the proposed testo Monte Carlo Experiments indicate that, if innovation has heavy tail distribution or are contaminated by outliers, then the proposed test is more powerful than the traditional ADF testo Nominal interest rates (different maturities) are shown to be stationary according to the robust test but not stationary according to the nonrobust ADF testo This result seems to suggest that the failure of rejecting the null of unit root in nominal interest rate may be due to the use of estimation and hypothesis testing procedures that do not consider the absence of Gaussianity in the data.Our results validate practical restrictions on the behavior of the nominal interest rate imposed by CCAPM, optimal monetary policy and option pricing models.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this work we study a connection between a non-Gaussian statistics, the Kaniadakis
statistics, and Complex Networks. We show that the degree distribution P(k)of
a scale free-network, can be calculated using a maximization of information entropy in
the context of non-gaussian statistics. As an example, a numerical analysis based on the
preferential attachment growth model is discussed, as well as a numerical behavior of
the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive
epidemic process (DEP) on a regular lattice one-dimensional. The model is composed
of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion
rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This
model belongs to the category of non-equilibrium systems with an absorbing state and a
phase transition between active an inactive states. We investigate the critical behavior of
the DEP using an auto-adaptive algorithm to find critical points: the method of automatic
searching for critical points (MASCP). We compare our results with the literature and we
find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases
DA =DB, DA
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The recent astronomical observations indicate that the universe has null spatial curvature, is accelerating and its matter-energy content is composed by circa 30% of matter (baryons + dark matter) and 70% of dark energy, a relativistic component with negative pressure. However, in order to built more realistic models it is necessary to consider the evolution of small density perturbations for explaining the richness of observed structures in the scale of galaxies and clusters of galaxies. The structure formation process was pioneering described by Press and Schechter (PS) in 1974, by means of the galaxy cluster mass function. The PS formalism establishes a Gaussian distribution for the primordial density perturbation field. Besides a serious normalization problem, such an approach does not explain the recent cluster X-ray data, and it is also in disagreement with the most up-to-date computational simulations. In this thesis, we discuss several applications of the nonextensive q-statistics (non-Gaussian), proposed in 1988 by C. Tsallis, with special emphasis in the cosmological process of the large structure formation. Initially, we investigate the statistics of the primordial fluctuation field of the density contrast, since the most recent data from the Wilkinson Microwave Anisotropy Probe (WMAP) indicates a deviation from gaussianity. We assume that such deviations may be described by the nonextensive statistics, because it reduces to the Gaussian distribution in the limit of the free parameter q = 1, thereby allowing a direct comparison with the standard theory. We study its application for a galaxy cluster catalog based on the ROSAT All-Sky Survey (hereafter HIFLUGCS). We conclude that the standard Gaussian model applied to HIFLUGCS does not agree with the most recent data independently obtained by WMAP. Using the nonextensive statistics, we obtain values much more aligned with WMAP results. We also demonstrate that the Burr distribution corrects the normalization problem. The cluster mass function formalism was also investigated in the presence of the dark energy. In this case, constraints over several cosmic parameters was also obtained. The nonextensive statistics was implemented yet in 2 distinct problems: (i) the plasma probe and (ii) in the Bremsstrahlung radiation description (the primary radiation from X-ray clusters); a problem of considerable interest in astrophysics. In another line of development, by using supernova data and the gas mass fraction from galaxy clusters, we discuss a redshift variation of the equation of state parameter, by considering two distinct expansions. An interesting aspect of this work is that the results do not need a prior in the mass parameter, as usually occurs in analyzes involving only supernovae data.Finally, we obtain a new estimate of the Hubble parameter, through a joint analysis involving the Sunyaev-Zeldovich effect (SZE), the X-ray data from galaxy clusters and the baryon acoustic oscillations. We show that the degeneracy of the observational data with respect to the mass parameter is broken when the signature of the baryon acoustic oscillations as given by the Sloan Digital Sky Survey (SDSS) catalog is considered. Our analysis, based on the SZE/X-ray data for a sample of 25 galaxy clusters with triaxial morphology, yields a Hubble parameter in good agreement with the independent studies, provided by the Hubble Space Telescope project and the recent estimates of the WMAP
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Considering a non-relativistic ideal gas, the standard foundations of kinetic theory are investigated in the context of non-gaussian statistical mechanics introduced by Kaniadakis. The new formalism is based on the generalization of the Boltzmann H-theorem and the deduction of Maxwells statistical distribution. The calculated power law distribution is parameterized through a parameter measuring the degree of non-gaussianity. In the limit = 0, the theory of gaussian Maxwell-Boltzmann distribution is recovered. Two physical applications of the non-gaussian effects have been considered. The first one, the -Doppler broadening of spectral lines from an excited gas is obtained from analytical expressions. The second one, a mathematical relationship between the entropic index and the stellar polytropic index is shown by using the thermodynamic formulation for self-gravitational systems
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Considering a quantum gas, the foundations of standard thermostatistics are investigated in the context of non-Gaussian statistical mechanics introduced by Tsallis and Kaniadakis. The new formalism is based on the following generalizations: i) Maxwell- Boltzmann-Gibbs entropy and ii) deduction of H-theorem. Based on this investigation, we calculate a new entropy using a generalization of combinatorial analysis based on two different methods of counting. The basic ingredients used in the H-theorem were: a generalized quantum entropy and a generalization of collisional term of Boltzmann equation. The power law distributions are parameterized by parameters q;, measuring the degree of non-Gaussianity of quantum gas. In the limit q
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There is a well-developed framework, the Black-Scholes theory, for the pricing of contracts based on the future prices of certain assets, called options. This theory assumes that the probability distribution of the returns of the underlying asset is a Gaussian distribution. However, it is observed in the market that this hypothesis is flawed, leading to the introduction of a fudge factor, the so-called volatility smile. Therefore, it would be interesting to explore extensions of the Black-Scholes theory to non-Gaussian distributions. In this paper, we provide an explicit formula for the price of an option when the distributions of the returns of the underlying asset is parametrized by an Edgeworth expansion, which allows for the introduction of higher independent moments of the probability distribution, namely skewness and kurtosis. We test our formula with options in the Brazilian and American markets, showing that the volatility smile can be reduced. We also check whether our approach leads to more efficient hedging strategies of these instruments. (C) 2004 Elsevier B.V. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Tradicionalmente, o método dos mínimos quadrados tem sido empregado na inversão não linear de dados de campo potencial. No caso em que as observações dos campos gravimétrico ou magnético contém apenas ruído Gaussiano. O método dos mínimos quadrados não apresenta problemas. Entretanto, quando as observações são perturbadas por ruído não Gaussiano, ou mesmo por ruído não aleatório, como é o caso de muitos ruídos geológicos, o método dos mínimos quadrados torna-se bastante ineficiente, e métodos alternativos devem ser empregados a fim de produzir interpretações realísticas. Neste trabalho, uma comparação é feita entre os métodos dos mínimos quadrados, dos mínimos absolutos e do ajuste-M, aplicados à inversão não linear de dados de campo potencial. A comparação é efetuada usando-se dados teóricos, onde diversas situações geológicas são simuladas. Os resultados mostram que na presença de ruído geológico, caracterizado por pequeno corpo raso acima do corpo principal, ou por corpo grande, adjacente ao corpo principal, o ajuste-M apresenta desempenho muito superior ao dos mínimos quadrados e dos mínimos absolutos. Na presença de ruído Gaussiano, entretanto, o ajuste-M tem um desempenho inferior aos outros dois métodos. Como o ruído Gaussiano é um ruído branco, parte dele pode ser removido por um filtro passa baixa adequado, sem muita perda do sinal, o que não ocorre com o ruído geológico que contém componentes importantes de baixo número de onda. Desse modo o ajuste-M se torna uma ferramenta importante na interpretação de áreas geologicamente complexas, onde é comum a contaminação das anomalias por ruído geológico. Os três métodos em estudo são aplicados a uma anomalia magnética real causada por uma intrusão de diabásio em forma de dique, em sedimentos arenosos da formação Piauí na Bacia do Parnaíba. Os três métodos apresentaram resultados semelhantes indicando que tanto o nível de ruído Gaussiano como geológico são baixos nesta anomalia.