946 resultados para High-frequency induction


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Ex vivo T cell depletion of allogeneic grafts is associated with a high (up to 80%) rate of mixed chimerism (MC) posttransplantation. The number of transplanted progenitor cells is an important factor in achieving complete donor chimerism in the T cell depletion setting. Use of granulocyte colony-stimulating factor (G-CSF) peripheral blood allografts allows the administration of large numbers of CD34+ cells. We studied the chimeric status of 13 patients who received allogeneic CD34+-selected peripheral blood progenitor cell transplants (allo-PBPCTs/CD34+) from HLA-identical sibling donors. Patients were conditioned with cyclophosphamide (120 mg/kg) and total-body irradiation (13 Gy in four fractions). Apheresis products were T cell-depleted by the immunoadsorption avidin-biotin method. The median number of CD34+ and CD3+ cells infused was 2.8x10(6)/kg (range 1.9-8.6x10(6)/kg) and 0.4x10(6)/kg (range 0.3-1x10(6)/kg), respectively. Molecular analysis of the engraftment was performed using polymerase chain reaction (PCR) amplification of highly polymorphic short tandem repeat (PCR-STR) sequences in peripheral blood samples. MC was detected in two (15%) of 13 patients. These two patients relapsed at 8 and 10 months after transplant, respectively. The remaining 11 patients showed complete donor chimerism and were in clinical remission after a maximum follow-up period of 24 months (range 6-24 months). These results were compared with those obtained in 10 patients who were treated with T cell-depleted bone marrow transplantation by means of elutriation and who received the same conditioning treatment and similar amounts of CD3+ cells (median 0.45x10(6)/kg; not significant) but a lower number of CD34+ cells (median 0.8x10(6)/kg; p = 0.001). MC was documented in six of 10 patients (60%), which was significantly higher than in the allo-PBPCT/CD34+ group (p = 0.04). We conclude that a high frequency of complete donor chimerism is achieved in patients receiving allo-PBPCT/CD34+ and that this is most likely due to the high number of progenitor cells administered.

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We assess the predictive ability of three VPIN metrics on the basis of two highly volatile market events of China, and examine the association between VPIN and toxic-induced volatility through conditional probability analysis and multiple regression. We examine the dynamic relationship on VPIN and high-frequency liquidity using Vector Auto-Regression models, Granger Causality tests, and impulse response analysis. Our results suggest that Bulk Volume VPIN has the best risk-warning effect among major VPIN metrics. VPIN has a positive association with market volatility induced by toxic information flow. Most importantly, we document a positive feedback effect between VPIN and high-frequency liquidity, where a negative liquidity shock boosts up VPIN, which, in turn, leads to further liquidity drain. Our study provides empirical evidence that reflects an intrinsic game between informed traders and market makers when facing toxic information in the high-frequency trading world.

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This note develops general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit the recent asymptotic distributional results in Barndorff-Nielsen and Shephard (2002a), are both easy to implement and highly accurate in empirically realistic situations. On properly accounting for the measurement errors in the volatility forecast evaluations reported in Andersen, Bollerslev, Diebold and Labys (2003), the adjustments result in markedly higher estimates for the true degree of return-volatility predictability.

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The attached file is created with Scientific Workplace Latex

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Rapport de recherche présenté à la Faculté des arts et des sciences en vue de l'obtention du grade de Maîtrise en sciences économiques.

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Nous développons dans cette thèse, des méthodes de bootstrap pour les données financières de hautes fréquences. Les deux premiers essais focalisent sur les méthodes de bootstrap appliquées à l’approche de "pré-moyennement" et robustes à la présence d’erreurs de microstructure. Le "pré-moyennement" permet de réduire l’influence de l’effet de microstructure avant d’appliquer la volatilité réalisée. En se basant sur cette ap- proche d’estimation de la volatilité intégrée en présence d’erreurs de microstructure, nous développons plusieurs méthodes de bootstrap qui préservent la structure de dépendance et l’hétérogénéité dans la moyenne des données originelles. Le troisième essai développe une méthode de bootstrap sous l’hypothèse de Gaussianité locale des données financières de hautes fréquences. Le premier chapitre est intitulé: "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns". Nous proposons dans ce chapitre, des méthodes de bootstrap robustes à la présence d’erreurs de microstructure. Particulièrement nous nous sommes focalisés sur la volatilité réalisée utilisant des rendements "pré-moyennés" proposés par Podolskij et Vetter (2009), où les rendements "pré-moyennés" sont construits sur des blocs de rendements à hautes fréquences consécutifs qui ne se chevauchent pas. Le "pré-moyennement" permet de réduire l’influence de l’effet de microstructure avant d’appliquer la volatilité réalisée. Le non-chevauchement des blocs fait que les rendements "pré-moyennés" sont asymptotiquement indépendants, mais possiblement hétéroscédastiques. Ce qui motive l’application du wild bootstrap dans ce contexte. Nous montrons la validité théorique du bootstrap pour construire des intervalles de type percentile et percentile-t. Les simulations Monte Carlo montrent que le bootstrap peut améliorer les propriétés en échantillon fini de l’estimateur de la volatilité intégrée par rapport aux résultats asymptotiques, pourvu que le choix de la variable externe soit fait de façon appropriée. Nous illustrons ces méthodes en utilisant des données financières réelles. Le deuxième chapitre est intitulé : "Bootstrapping pre-averaged realized volatility under market microstructure noise". Nous développons dans ce chapitre une méthode de bootstrap par bloc basée sur l’approche "pré-moyennement" de Jacod et al. (2009), où les rendements "pré-moyennés" sont construits sur des blocs de rendements à haute fréquences consécutifs qui se chevauchent. Le chevauchement des blocs induit une forte dépendance dans la structure des rendements "pré-moyennés". En effet les rendements "pré-moyennés" sont m-dépendant avec m qui croît à une vitesse plus faible que la taille d’échantillon n. Ceci motive l’application d’un bootstrap par bloc spécifique. Nous montrons que le bloc bootstrap suggéré par Bühlmann et Künsch (1995) n’est valide que lorsque la volatilité est constante. Ceci est dû à l’hétérogénéité dans la moyenne des rendements "pré-moyennés" au carré lorsque la volatilité est stochastique. Nous proposons donc une nouvelle procédure de bootstrap qui combine le wild bootstrap et le bootstrap par bloc, de telle sorte que la dépendance sérielle des rendements "pré-moyennés" est préservée à l’intérieur des blocs et la condition d’homogénéité nécessaire pour la validité du bootstrap est respectée. Sous des conditions de taille de bloc, nous montrons que cette méthode est convergente. Les simulations Monte Carlo montrent que le bootstrap améliore les propriétés en échantillon fini de l’estimateur de la volatilité intégrée par rapport aux résultats asymptotiques. Nous illustrons cette méthode en utilisant des données financières réelles. Le troisième chapitre est intitulé: "Bootstrapping realized covolatility measures under local Gaussianity assumption". Dans ce chapitre nous montrons, comment et dans quelle mesure on peut approximer les distributions des estimateurs de mesures de co-volatilité sous l’hypothèse de Gaussianité locale des rendements. En particulier nous proposons une nouvelle méthode de bootstrap sous ces hypothèses. Nous nous sommes focalisés sur la volatilité réalisée et sur le beta réalisé. Nous montrons que la nouvelle méthode de bootstrap appliquée au beta réalisé était capable de répliquer les cummulants au deuxième ordre, tandis qu’il procurait une amélioration au troisième degré lorsqu’elle est appliquée à la volatilité réalisée. Ces résultats améliorent donc les résultats existants dans cette littérature, notamment ceux de Gonçalves et Meddahi (2009) et de Dovonon, Gonçalves et Meddahi (2013). Les simulations Monte Carlo montrent que le bootstrap améliore les propriétés en échantillon fini de l’estimateur de la volatilité intégrée par rapport aux résultats asymptotiques et les résultats de bootstrap existants. Nous illustrons cette méthode en utilisant des données financières réelles.

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We consider the problem of conducting inference on nonparametric high-frequency estimators without knowing their asymptotic variances. We prove that a multivariate subsampling method achieves this goal under general conditions that were not previously available in the literature. We suggest a procedure for a data-driven choice of the bandwidth parameters. Our simulation study indicates that the subsampling method is much more robust than the plug-in method based on the asymptotic expression for the variance. Importantly, the subsampling method reliably estimates the variability of the Two Scale estimator even when its parameters are chosen to minimize the finite sample Mean Squared Error; in contrast, the plugin estimator substantially underestimates the sampling uncertainty. By construction, the subsampling method delivers estimates of the variance-covariance matrices that are always positive semi-definite. We use the subsampling method to study the dynamics of financial betas of six stocks on the NYSE. We document significant variation in betas within year 2006, and find that tick data captures more variation in betas than the data sampled at moderate frequencies such as every five or twenty minutes. To capture this variation we estimate a simple dynamic model for betas. The variance estimation is also important for the correction of the errors-in-variables bias in such models. We find that the bias corrections are substantial, and that betas are more persistent than the naive estimators would lead one to believe.

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The thesis deals with the preparation and dielectric characterization of Poly aniline and its analogues in ISM band frequency of 2-4 GHz that includes part of the microwave region (300 MHz to 300 GHz) of the electromagnetic spectrum and an initial dielectric study in the high frequency [O.05MHz-13 MHz]. PolyaniIine has been synthesized by an in situ doping reaction under different temperature and in the presence of inorganic dopants such as HCl H2S04, HN03, HCl04 and organic dopants such as camphorsulphonic acid [CSA], toluenesulphonic acid {TSA) and naphthalenesulphonic acid [NSA]. The variation in dielectric properties with change in reaction temperature, dopants and frequency has been studied. The effect of codopants and microemulsions on the dielectric properties has also been studied in the ISM band. The ISM band of frequencies (2-4 GHz) is of great utility in Industrial, Scientific and Medical (ISM) applications. Microwave heating is a very efficient method of heating dielectric materials and is extensively used in industrial as well as household heating applications.

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The main challenges in the deposition of cathode materials in thin film form are the reproduction of stoichiometry close to the bulk material and attaining higher rates of deposition and excellent crystallinity at comparatively lower annealing temperatures. There are several methods available to develop stoichiometric thin film cathode materials including pulsed laser deposition; plasma enhanced chemical vapor deposition, electron beam evaporation, electrostatic spray deposition and RF magnetron sputtering. Among them the most versatile method is the sputtering technique, owing to its suitability for micro-fabricating the thin film batteries directly on chips in any shape or size, and on flexible substrates, with good capacity and cycle life. The main drawback of the conventional sputtering technique using RF frequency of 13.56MHz is its lower rate of deposition, compared to other deposition techniques A typical cathode layer for a thin film battery requires a thickness around one micron. To deposit such thick layers using convention RF sputtering, longer time of deposition is required, since the deposition rate is very low, which is typically 10-20 Å/min. This makes the conventional RF sputtering technique a less viable option for mass production in an economical way. There exists a host of theoretical and experimental evidences and results that higher excitation frequency can be efficiently used to deposit good quality films at higher deposition rates with glow discharge plasma. The effect of frequencies higher than the conventional one (13.56MHz) on the RF magnetron sputtering process has not been subjected to detailed investigations. Attempts have been made in the present work, to sputter deposit spinel oxide cathode films, using high frequency RF excitation source. Most importantly, the major challenge faced by the thin film battery based on the LiMn2O4 cathode material is the poor capacity retention during charge discharge cycling. The major causes for the capacity fading reported in LiMn2O4cathode materials are due to, Jahn-Teller distortion, Mn2+ dissolution into the electrolyte and oxygen loss in cathode material during cycling. The work discussed in this thesis is an attempt on overcoming the above said challenges and developing a high capacity thin film cathode material.

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This dissertation examines the frequency response that results in the maximum level of speech intelligibility for persons with noise-induced hearing loss.