972 resultados para structure model detection
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A Work Project, presented as part of the requirements for the Award of a Master’s Double Degree in Finance from Maastricht University and NOVA – School of Business and Economics
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.
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Neurospora VS RNA performs an RNA-mediated self-cleavage reaction whose products contain 2',3'-cyclic phosphate and 5'-hydroxyl termini. This reaction is similar to those of hammerhead, hairpin, and hepatitis delta virus ribozymes; however, VS RNA is not similar in sequence to these other self-cleaving motifs. Here we propose a model for the secondary structure of the self-cleaving region of VS RNA, supported by site-directed mutagenesis and chemical modification structure probing data. The secondary structure of VS RNA is distinct from those of the other naturally occurring RNA self-cleaving domains. In addition to a unique secondary structure, several Mg-dependent interactions occur during the folding of VS RNA into its active tertiary conformation.
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Cover title.
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The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances
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BACKGROUND: APOBEC3G (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like 3G) has antiretroviral activity associated with the hypermutation of viral DNA through cytosine deamination. APOBEC3G has two cytosine deaminase (CDA) domains; the catalytically inactive amino-terminal domain of APOBEC3G (N-CDA) carries the Vif interaction domain. There is no 3-D structure of APOBEC3G solved by X-ray or nuclear magnetic resonance. METHODOLOGY/PRINCIPAL FINDINGS: We predicted the structure of human APOBEC3G based on the crystal structure of APOBEC2. To assess the model structure, we evaluated 48 mutants of APOBEC3G N-CDA that identify novel variants altering DeltaVif HIV-1 infectivity and packaging of APOBEC3G. Results indicated that the key residue D128 is exposed at the surface of the model, with a negative local electrostatic potential. Mutation D128K changes the sign of that local potential. In addition, two novel functionally relevant residues that result in defective APOBEC3G encapsidation, R122 and W127, cluster at the surface. CONCLUSIONS/SIGNIFICANCE: The structure model identifies a cluster of residues important for packaging of APOBEC3G into virions, and may serve to guide functional analysis of APOBEC3G.
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The ovariectomized (OVX) rat, a preclinical model for studying postmenopausal bone loss, may also be used to study differences in alveolar bone (AB). The objectives of this study were to quantify the differences in AB following estrogen replacement therapy (ERT), and to investigate the relationship between AB structure and density, and trabecular bone at the femoral neck (FN) and third lumbar vertebral body (LB3). Estrogen treated rats had a higher bone volume fraction (BV/TV) at the AB region (9.8% P < 0.0001), FN (12% P < 0.0001), and LB3 (11.5% P < 0.0001) compared to the OVX group. BV/TV of the AB was positively correlated with the BV/TV at the FN (r = 0.69 P < 0.0001) and the LB3 (r = 0.75 P < 0.0001). The trabecular number (Tb.N), trabecular separation (Tb.Sp), and structure model index (SMI) were also positively correlated (P < 0.05) between the AB and FN (r = 0.42, 0.49, and 0.73, respectfully) and between the AB and LB3 (r = 0.44, 0.63, and 0.69, respectfully). Given the capacity of AB to respond to ERT, future preclinical drug/nutritional intervention studies aimed at improving skeletal health should include the AB as a region of interest (ROI).
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We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.
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A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.
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When long maturity bonds are traded frequently and traders have non-nestedinformation sets, speculative behavior in the sense of Harrison and Kreps (1978) arises.Using a term structure model displaying such speculative behavior, this paper proposesa conceptually and observationally distinct new mechanism generating time varying predictableexcess returns. It is demonstrated that (i) dispersion of expectations about futureshort rates is sufficient for individual traders to systematically predict excess returns and(ii) the new term structure dynamics driven by speculative trade is orthogonal to publicinformation in real time, but (iii) can nevertheless be quantified using only publicly availableyield data. The model is estimated using monthly data on US short to medium termTreasuries from 1964 to 2007 and it provides a good fit of the data. Speculative dynamicsare found to be quantitatively important, potentially accounting for a substantial fractionof the variation of bond yields and appears to be more important at long maturities.
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En 1981, le gouvernement de l'Alberta a amélioré la surveillance de la pointe sud « South Peak » de la montagne Turtle, sur la frontière sud du glissement Frank de 1903. Le programme de surveillance vise à comprendre les taux de déformation des fissures larges et profondes sur « South Peak », et à prédire une seconde avalanche rocheuse sur la montagne. Le programme de surveillance consiste à installer un complément de points statiques et de stations suivies à distance, qui sont mesurés périodiquement. Des données climatiques, microsismiques et de déformation sont recueillies automatiquement à intervalles journaliers, et sont archivées. À la fin des années 1980, le financement pour le développement du programme de surveillance a cessé et quelques installations se sont détériorées. Entre mai 2004 et septembre 2006, des lectures sur les points de surveillance encore fonctionnels ont été compilées et interprétées. De plus, les lectures prélevées auparavant ont été réinterprétées à partir des connaissances récentes sur les modèles de mouvement à court terme et les influences climatiques. Ces observations ont été comparées à des récentes observations aériennes d'un modèle digital d'élévation, provenant de « light detection and ranging (LiDAR) », et des photos de terrain, afin d'estimer plus précisément les taux, l'étendue et la distribution des mouvements pour les derniers 25 ans.
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Using a variation of the Nelson-Siegel term structure model we examine the sensitivity of real estate securities in six key global markets to unexpected changes in the level, slop and curvature of the yield curve. Our results confirm the time-sensitive nature of the exposure and sensitivity to interest rates and highlight the importance of considering the entire term structure of interest rates. One issue that is of particular of interest is that despite the 2007-9 financial crisis the importance of unanticipated interest rate risk weakens post 2003. Although the analysis does examine a range of markets the empirical analysis is unable to provide definitive evidence as to whether REIT and property-company markets display heightened or reduced exposure.
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This thesis is composed of three articles with the subjects of macroeconomics and - nance. Each article corresponds to a chapter and is done in paper format. In the rst article, which was done with Axel Simonsen, we model and estimate a small open economy for the Canadian economy in a two country General Equilibrium (DSGE) framework. We show that it is important to account for the correlation between Domestic and Foreign shocks and for the Incomplete Pass-Through. In the second chapter-paper, which was done with Hedibert Freitas Lopes, we estimate a Regime-switching Macro-Finance model for the term-structure of interest rates to study the US post-World War II (WWII) joint behavior of macro-variables and the yield-curve. We show that our model tracks well the US NBER cycles, the addition of changes of regime are important to explain the Expectation Theory of the term structure, and macro-variables have increasing importance in recessions to explain the variability of the yield curve. We also present a novel sequential Monte-Carlo algorithm to learn about the parameters and the latent states of the Economy. In the third chapter, I present a Gaussian A ne Term Structure Model (ATSM) with latent jumps in order to address two questions: (1) what are the implications of incorporating jumps in an ATSM for Asian option pricing, in the particular case of the Brazilian DI Index (IDI) option, and (2) how jumps and options a ect the bond risk-premia dynamics. I show that jump risk-premia is negative in a scenario of decreasing interest rates (my sample period) and is important to explain the level of yields, and that gaussian models without jumps and with constant intensity jumps are good to price Asian options.
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A structure modeling of two families of sol-gel derived Eu3+-doped organic/inorganic hybrids based on the results of small-angle X-ray scattering experiments is reported. The materials are composed of poly(oxyethylene) chains grafted at one or both ends to siloxane groups and are called mono- and di-urethanesils, respectively. A theoretical function corresponding to a two-level hierarchical structure model fits well the experimental Scattering curves. The first level corresponds to small siloxane clusters embedded in a polymeric matrix. The secondary level is associated to the existence of siloxane cluster rich domains surrounded by a cluster-depleted polymeric matrix. Results show that increasing europium doping favors the growth of the secondary domains. (C) 2002 Elsevier B.V. B.V. All rights reserved.