Página 1 dos resultados de 285 itens digitais encontrados em 0.025 segundos

## Modelo de razão de hedge ótima e percepção subjetiva de risco nos mercados futuros; Optimal hedge ratio model and subjective risk perception in the futures markets

Cruz Júnior, José César
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Relevância na Pesquisa
55.99%

## Comparação de rols classificatórios de tratamentos e de estimativas de componentes de variância em grupos de experimentos; Comparison of treatments classicatory rankings and of variance components estimates in experimental groups

Dessotti, Cássio
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Relevância na Pesquisa
35.84%

## Methods to verify parameter equality in nonlinear regression models

Carvalho, Lídia Raquel de; Pinho, Sheila Zambello de; Mischan, Martha Maria
Fonte: Universidade de São Paulo (USP), Escola Superior de Agricultura Luiz de Queiroz (ESALQ) Publicador: Universidade de São Paulo (USP), Escola Superior de Agricultura Luiz de Queiroz (ESALQ)
Tipo: Artigo de Revista Científica Formato: 218-222
ENG
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## The valuation of turbo warrants under the CEV model

Domingues, Ana Margarida David
Relevância na Pesquisa
45.78%
Tese de mestrado em Matemática Financeira, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2012; This thesis uses the Laplace transform of the probability distributions of the minimum and maximum asset prices and of the expected value of the terminal payoff of a down-and-out option to derive closed-form solutions for the prices of lookback options and turbo call warrants, under the Constant Elasticity of Variance (CEV) and geometric Brownian motion (GBM) models. These solutions require numerical computations to invert the Laplace transforms. The analytical solutions proposed are implemented in Matlab and Mathematica. We show that the prices of these contracts are sensitive to variations of the elasticity parameter β in the CEV model.

## Methods to verify parameter equality in nonlinear regression models

Carvalho,Lídia Raquel de; Pinho,Sheila Zambello de; Mischan,Martha Maria
Fonte: São Paulo - Escola Superior de Agricultura "Luiz de Queiroz" Publicador: São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"
Tipo: Artigo de Revista Científica Formato: text/html
Relevância na Pesquisa
35.76%
In biologic experiments, in which growth curves are adjusted to sample data, treatments applied to the experimental material can affect the parameter estimates. In these cases the interest is to compare the growth functions, in order to distinguish treatments. Three methods that verify the equality of parameters in nonlinear regression models were compared: (i) developed by Carvalho in 1996, performing ANOVA on estimates of parameters of individual fits; (ii) suggested by Regazzi in 2003, using the likelihood ratio method; and (iii) constructing a pooled variance from individual variances. The parametric tests, F and Tukey, were employed when the parameter estimators were near to present the properties of linear model estimators, that is, unbiasedness, normal distribution and minimum variance. The first and second methods presented similar results, but the third method is simpler in calculations and uses all information contained in the original data.

## Unbiased Invariant Least Squares Estimation in A Generalized Growth Curve Model

Wu, Xiaoyong; Liang, Hua; Zou, Guohua
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
35.76%
This paper is concerned with a generalized growth curve model. We derive the unbiased invariant least squares estimators of the linear functions of variance-covariance matrix of disturbances. Under the minimum variance criterion, we obtain the necessary and sufficient conditions of the proposed estimators to be optimal. Simulation studies show that the proposed estimators perform well.

## Linear constraint minimum variance beamformer functional magnetic resonance inverse imaging

Lin, Fa-Hsuan; Witzel, Thomas; Zeffiro, Thomas A.; Belliveau, John W.
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
35.81%
Accurate estimation of the timing of neural activity is required to fully model the information flow among functionally specialized regions whose joint activity underlies perception, cognition and action. Attempts to detect the fine temporal structure of task-related activity would benefit from functional imaging methods allowing higher sampling rates. Spatial filtering techniques have been used in magnetoencephalography source imaging applications. In this work, we use the linear constraint minimal variance (LCMV) beamformer localization method to reconstruct single-shot volumetric functional magnetic resonance imaging (fMRI) data using signals acquired simultaneously from all channels of a high density radio-frequency (RF) coil array. The LCMV beamformer method generalizes the existing volumetric magnetic resonance inverse imaging (InI) technique, achieving higher detection sensitivity while maintaining whole-brain spatial coverage and 100 ms temporal resolution. In this paper, we begin by introducing the LCMV reconstruction formulation and then quantitatively assess its performance using both simulated and empirical data. To demonstrate the sensitivity and inter-subject reliability of volumetric LCMV InI, we employ an event-related design to probe the spatial and temporal properties of task-related hemodynamic signal modulations in primary visual cortex. Compared to minimum-norm estimate (MNE) reconstructions...

## A Generalized ideal observer model for decoding sensory neural responses

Purushothaman, Gopathy; Casagrande, Vivien A.
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
35.8%
We show that many ideal observer models used to decode neural activity can be generalized to a conceptually and analytically simple form. This enables us to study the statistical properties of this class of ideal observer models in a unified manner. We consider in detail the problem of estimating the performance of this class of models. We formulate the problem de novo by deriving two equivalent expressions for the performance and introducing the corresponding estimators. We obtain a lower bound on the number of observations (N) required for the estimate of the model performance to lie within a specified confidence interval at a specified confidence level. We show that these estimators are unbiased and consistent, with variance approaching zero at the rate of 1/N. We find that the maximum likelihood estimator for the model performance is not guaranteed to be the minimum variance estimator even for some simple parametric forms (e.g., exponential) of the underlying probability distributions. We discuss the application of these results for designing and interpreting neurophysiological experiments that employ specific instances of this ideal observer model.

## A Switching Black-Scholes Model and Option Pricing

Webb, Melanie Ann
Tipo: Tese de Doutorado Formato: 439092 bytes; 1105970 bytes; 145201 bytes; application/pdf; application/pdf; application/pdf
Relevância na Pesquisa
35.83%
Derivative pricing, and in particular the pricing of options, is an important area of current research in financial mathematics. Experts debate on the best method of pricing and the most appropriate model of a price process to use. In this thesis, a Switching Black-Scholes' model of a price process is proposed. This model is based on the standard geometric Brownian motion (or Black-Scholes) model of a price process. However, the drift and volatility parameters are permitted to vary between a finite number of possible values at known times, according to the state of a hidden Markov chain. This type of model has been found to replicate the Black-Scholes implied volatility smiles observed in the market, and produce option prices which are closer to market values than those obtained from the traditional Black-Scholes formula. As the Markov chain incorporates a second source of uncertainty into the Black-Scholes model, the Switching Black-Scholes market is incomplete, and no unique option pricing methodology exists. In this thesis, we apply the methods of mean-variance hedging, Esscher transforms and minimum entropy in order to price options on assets which evolve according to the Switching Black-Scholes model. C programs to compute these prices are given...

## A eficiência nas Carteiras de Markowitz, Variância Mínima e Naïve aplicada ao índice italiano

Martins, Luís Pedro Rosa
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Relevância na Pesquisa
65.99%

## The efficiency in Markowitz, minimum-variance and naïve portfolios applied to smi

Fernandes, Cristiano Mateus Cunha
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Relevância na Pesquisa
76%

Félix, João Pedro Santos Silva
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Relevância na Pesquisa
45.97%

Monteiro, Pedro Matoso Coimbra Sacramento
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Relevância na Pesquisa
65.89%
Mestrado em Finanças; A presente dissertação teve como objetivo principal analisar e comparar a gestão ativa e passiva de um determinado portfolio constituído por ações do Índice Bolsista Espanhol (IBEX 35). Na gestão ativa utilizaram-se dois modelos: uma carteira de ações determinada através do modelo de otimização de Markowitz, e uma carteira de ações resultante do modelo de variância mínima. Na gestão passiva recorreu-se a uma carteira de ações com pesos iguais. O período de tempo considerado para o efeito foi de 10 anos, de 1997 a 2006. A gestão ativa do portfolio, com base nos dois modelos considerados, consistiu na revisão mensal das proporções investidas em cada uma das ações que compuseram a carteira tendo em conta a evolução do mercado. A gestão passiva implicou um investimento de proporções iguais nos ativos constituintes da carteira, proporções essas que se mantiveram inalteradas durante o período em análise e que, portanto, não tiveram em conta a evolução do mercado. Para a determinação das ponderações das carteiras dos três modelos, utilizou-se um ?sistema de janela? de 1 e 2 anos. Um segundo objetivo deste trabalho foi perceber o impacto dos custos de intermediação financeira no desempenho dos portfolios de ações. Com este estudo...

## Minimum Variance Estimation of a Sparse Vector within the Linear Gaussian Model: An RKHS Approach

Jung, Alexander; Schmutzhard, Sebastian; Hlawatsch, Franz; Ben-Haim, Zvika; Eldar, Yonina C.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.12%
We consider minimum variance estimation within the sparse linear Gaussian model (SLGM). A sparse vector is to be estimated from a linearly transformed version embedded in Gaussian noise. Our analysis is based on the theory of reproducing kernel Hilbert spaces (RKHS). After a characterization of the RKHS associated with the SLGM, we derive novel lower bounds on the minimum variance achievable by estimators with a prescribed bias function. This includes the important case of unbiased estimation. The variance bounds are obtained via an orthogonal projection of the prescribed mean function onto a subspace of the RKHS associated with the SLGM. Furthermore, we specialize our bounds to compressed sensing measurement matrices and express them in terms of the restricted isometry and coherence parameters. For the special case of the SLGM given by the sparse signal in noise model (SSNM), we derive closed-form expressions of the minimum achievable variance (Barankin bound) and the corresponding locally minimum variance estimator. We also analyze the effects of exact and approximate sparsity information and show that the minimum achievable variance for exact sparsity is not a limiting case of that for approximate sparsity. Finally, we compare our bounds with the variance of three well-known estimators...

## Variance Competitiveness for Monotone Estimation: Tightening the Bounds

Cohen, Edith
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
35.86%
Random samples are extensively used to summarize massive data sets and facilitate scalable analytics. Coordinated sampling, where samples of different data sets "share" the randomization, is a powerful method which facilitates more accurate estimation of many aggregates and similarity measures. We recently formulated a model of {\it Monotone Estimation Problems} (MEP), which can be applied to coordinated sampling, projected on a single item. MEP estimators can then be used to estimate sum aggregates, such as distances, over coordinated samples. For MEP, we are interested in estimators that are unbiased and nonnegative. We proposed {\it variance competitiveness} as a quality measure of estimators: For each data vector, we consider the minimum variance attainable on it by an unbiased and nonnegative estimator. We then define the competitiveness of an estimator as the maximum ratio, over data, of the expectation of the square to the minimum possible. We also presented a general construction of the L$^*$ estimator, which is defined for any MEP for which a nonnegative unbiased estimator exists, and is at most 4-competitive. Our aim here is to obtain tighter bounds on the {\em universal ratio}, which we define to be the smallest competitive ratio that can be obtained for any MEP. We obtain an upper bound of 3.375...

## Variance Reduction in SGD by Distributed Importance Sampling

Alain, Guillaume; Lamb, Alex; Sankar, Chinnadhurai; Courville, Aaron; Bengio, Yoshua
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
35.81%
Humans are able to accelerate their learning by selecting training materials that are the most informative and at the appropriate level of difficulty. We propose a framework for distributing deep learning in which one set of workers search for the most informative examples in parallel while a single worker updates the model on examples selected by importance sampling. This leads the model to update using an unbiased estimate of the gradient which also has minimum variance when the sampling proposal is proportional to the L2-norm of the gradient. We show experimentally that this method reduces gradient variance even in a context where the cost of synchronization across machines cannot be ignored, and where the factors for importance sampling are not updated instantly across the training set.

## Estimation of the Global Minimum Variance Portfolio in High Dimensions

Bodnar, Taras; Parolya, Nestor; Schmid, Wolfgang
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.86%
We estimate the global minimum variance (GMV) portfolio in the high-dimensional case using results from random matrix theory. This approach leads to a shrinkage-type estimator which is distribution-free and it is optimal in the sense of minimizing the out-of-sample variance. Its asymptotic properties are investigated assuming that the number of assets $p$ depends on the sample size $n$ such that $\frac{p}{n}\rightarrow c\in (0,+\infty)$ as $n$ tends to infinity. The results are obtained under weak assumptions imposed on the distribution of the asset returns, namely it is only required the fourth moments existence. Furthermore, we make no assumption on the upper bound of the spectrum of the covariance matrix. As a result, the theoretical findings are also valid if the dependencies between the asset returns are described by a factor model which appears to be very popular in financial literature nowadays. This is also well-documented in a numerical study where the small- and large-sample behavior of the derived estimator are compared with existing estimators of the GMV portfolio. The resulting estimator shows significant improvements and it turns out to be robust to the deviations from normality.; Comment: 38 pages inc. 16 figures. Revised and corrected version

## Analysis of the improvement in sky coverage for multiconjugate adaptive optics systems obtained using minimum variance split tomography

Wang, Lianqi; Gilles, Luc; Ellerbroek, Brent
Fonte: Optical Society of America Publicador: Optical Society of America
Tipo: Article; PeerReviewed Formato: application/pdf
Relevância na Pesquisa
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The scientific utility of laser-guide-star-based multiconjugate adaptive optics systems depends upon high sky coverage. Previously we reported a high-fidelity sky coverage analysis of an ad hoc split tomography control algorithm and a postprocessing simulation technique. In this paper, we present the performance of a newer minimum variance split tomography algorithm, and we show that it brings a median improvement at zenith of 21 nm rms optical path difference error over the ad hoc split tomography control algorithm for our system, the Narrow Field Infrared Adaptive Optics System for the Thirty Meter Telescope. In order to make the comparison, we also validated our previously developed sky coverage postprocessing software using an integrated simulation of both high- (laser guide star) and low-order (natural guide star) loops. A new term in the noise model is also identified that improves the performance of both algorithms by more properly regularizing the reconstructor.

## Métodos de verificação de igualdade de parâmetros em modelos de regressão não-linear; Methods to verify parameter equality in nonlinear regression models

Carvalho, Lídia Raquel de; Pinho, Sheila Zambello de; Mischan, Martha Maria
Fonte: Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz Publicador: Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; ; ; ; Formato: application/pdf