Letteratura scientifica selezionata sul tema "QML asymptotic results"

This paper studies a linear regression model, whose errors are functional coefficient autoregressive processes. Firstly, the quasi-maximum likelihood (QML) estimators of some unknown parameters are given. Secondly, under general conditions, the asymptotic properties (existence, consistency, and asymptotic distributions) of the QML estimators are investigated. These results extend those of Maller (2003), White (1959), Brockwell and Davis (1987), and so on. Lastly, the validity and feasibility of the method are illuminated by a simulation example and a real example.

The asymptotic distribution of the Gaussian quasi-maximum likelihood estimator (QMLE) is obtained for a wide class of asymmetric GARCH models with exogenous covariates. The true value of the parameter is not restricted to belong to the interior of the parameter space, which allows us to derive tests for the significance of the parameters. In particular, the relevance of the exogenous variables can be assessed. The results are obtained without assuming that the innovations are independent, which allows conditioning on different information sets. Monte Carlo experiments and applications to financial series illustrate the asymptotic results. In particular, an empirical study demonstrates that the realized volatility can be a helpful covariate for predicting squared returns.

This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a general nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first-order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. We do not require the rescaled errors to be independent, but instead only to form a stationary and ergodic martingale difference sequence. Strong consistency and asymptotic normality of the global Gaussian quasi-maximum likelihood (QML) estimator are established under conditions comparable to those recently used in the corresponding linear case. To the best of our knowledge, this paper provides the first results on consistency and asymptotic normality of the QML estimator in nonlinear autoregressive models with GARCH errors.

We establish the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) of the parameters of a class of multivariate asymmetric generalized autoregressive conditionally heteroskedastic processes, allowing for cross leverage effects. The conditions required to establish the asymptotic properties of the QMLE are mild and coincide with the minimal ones in the univariate case. In particular, no moment assumption is made on the observed process. Instead, we require strict stationarity, for which a necessary and sufficient condition is established. The asymptotic results are illustrated by Monte Carlo experiments, and an application to a bivariate exchange rates series is proposed.

In this paper, the spatial dynamic panel data (SDPD) model is extended to the single-index spatial dynamic panel data (Si-SDPD) model by introducing a nonlinear connection function to reflect the interaction between explanatory variables. The Si-SDPD model not only retains the advantages of the parametric SDPD model in dealing with spatial and temporal interaction effects and spatio-temporal dependencies, but also solves the limitations of the parametric SDPD model that may lead to missed bias. It reduces the data dimension of non-parametric models and enhances the practicability and explanatory power of parametric models. Since the parts of the model to be estimated contain unknown functions, we propose a new estimation method, a profile maximum likelihood (PML) method, to solve the problem of incidental parameters in the estimation. Under the assumption that the spatial coefficients are known, we preliminarily estimate the unknown function by carrying out local polynomial estimation, so as to transform the model into the parametric form for solving purposes. We then solve the dynamic panel parametric model via quasi-maximum likelihood (QML) estimation. We derive the asymptotic properties of profile maximum likelihood estimators (PMLEs) and find that, under certain regularity conditions, both parametric and non-parametric estimators are consistent. Monte Carlo results show that PMLEs have good finite sample performance.

Fifty patients with chronic renal insufficiency underwent clinical evaluation & studies of thyroid function the results were compared with age & sex-matched controls. (20%) of patients had biochemical hypothyroidism with low serum T3, T4, & high serum TSH. All the members of the control group were biochemically euthyroid. The mean values of serum T3, T4 were significantly lower & mean serum TSH was significantly higher as compared to controls. There was no correlation of thyroid functions with decrease in renal function. To conclude thyroid dysfunction occurs both clinically & biochemically in patients with chronic renal insufficiency.

The present study was carried out from Sept. 2010 to Jul. 2011 to detect the viral load and genotypes of HCV infections among asymptomatic peoples and patients referred to the central blood bank, center of thalassemia /AL-Haboby Hospital, renal dialysis unit/Al- Hussein Teaching Hospital and public health laboratory at Thi-Qar province. Real-Time Polymerase Chain Reaction Technique (RT-qPCR) was implemented on 90 individuals of anti-HCV seropositive by ELISA III assay. The results revealed that 51(56.66%) were gave positive results for HCV. The RT-qPCR analyses of the positive samples were showed that the viral loads were ranged from 1.19 × 103 to 4.3 × 106 IU/ml of blood .The mean of viral load was 5.9 × 105 IU/ml of blood, whilst, the median was 2.6 × 105 IU/ml. Three genotypes of HCV were detected in patients serum by RT-PCR technique. Genotype 1a (33.33%), genotype 1b (37.25%) and genotype 4 (86.27%) with significant differences (p>0.05). Genotype 4 was the predominant and found in 44 of 51 cases, of those 21(41.18%) as single infections. Mixed infections with genotype 4 and each of 1a and 1b was found in 21.57% and 11.76% respectively. Mixed infections with genotype 4 and both 1a and 1b was found in 11.76%. Single infections with genotype 1b only was found in 13.73%, while genotype 1a was detected only in mixed infections. This study was the first at Thi-Qar province which involved the searching for HCV viral load and genotypes by using of Real-Time and RT-PCR technique.

Introduction: Interleukin-6 (IL-6) is a pro-inflammatory cytokine and an anti-inflammatory myokine. Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in adults. The exact role of IL-6 in CLL is still contraversial and needs alot of research. Aim of the study: To measure serum level of interleukin-6 among Iraqi patients from Babil province with a newly diagnosed untreated chronic lymphocytic leukemia and to assess it's association with the stage of the disease and peripheral blood indices. Materials and methods: This is a case-control study included 106 Iraqi patients with a newly diagnosed untreated chronic lymphocytic leukemia (CLL). They were from Babil province and attended the hospital during the period from 1st of November 2012 to 30th of October 2015, while the control group included 106 age and sex matched healthy individuals. CBC, blood film and serum IL-6 (Human IL-6 ELISA kit ) were done for both groups, and bone marrow exam was performed for the patients only. Results: The age of the patients ranged from 44 to 82 years with mean age of 61.8 ±6.14 years. Male:Female ratio was 1.8:1 and 57.5% of them were asymptomatic. Serum IL-6 was undetected in 39.6% (42/106) of the control cases and in 13.2% (14/106) of the patients; all of them were in CLL stages 0 and 1. Mean serum IL-6 in the patient group was 12.6 ±5.1 pg/ml, while it was 6.2 ±2.3 pg/ml in the control group (P-value was 0.001). Higher levels were documented in stages 3 and 4 (P-value 0.0001). Conclusion and recommendations: Elevated serum IL-6 was found among Iraqi patients with newly diagnosed untreated CLL, and higher levels were documented in advanced stage disease. Further studies are needed to assess exact role of IL-6 in CLL as it may have prognostic and/or therapeutic implications.

Abstract For large multivariate models of generalized autoregressive conditional heteroskedasticity (GARCH), it is important to reduce the number of parameters to cope with the ‘curse of dimensionality’. Recently, Laurent, Rombouts and Violante (2014 “Multivariate Rotated ARCH Models” Journal of Econometrics 179: 16–30) developed the rotated multivariate GARCH model, which focuses on the parameters for standardized variables. This paper extends the rotated multivariate GARCH model by considering a hyper-rotation, which uses a more flexible structure for the rotation matrix. The paper shows an alternative representation based on a random coefficient vector autoregressive and moving-average (VARMA) process, and provides the regularity conditions for the consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator for VARMA with hyper-rotated multivariate GARCH. The paper investigates the finite sample properties of the QML estimator for the new model. Empirical results for four exchange rate returns show the new specifications works satisfactory for reducing the number of parameters.

Abstract We develop a heterogeneous spatial arbit and regression coefficients, and heteroscedastic variances, and further establish identification of parameters and asymptotic normality of the conditional QML estimators under some mild conditions. We apply the proposed model to study a real data set of 11 eurozone stock index returns and extend the Fama–French five-factor model to regional stock indices, in which heterogeneous spatial effects and heteroscedastic disturbances are highly significant and they both play very important roles in explaining distinct endogenous effects and distinct risks of the 11 eurozone stock markets. Our empirical results reveal unique characteristics of each of 11 eurozone stock markets and their inner connections.

La modélisation des séries temporelles financières est rendue difficile par la présence de faits stylisés. Ces propriétés statistiques empiriques rendent nécessaires l'utilisation de modèles non-linéaires hétéroscédastiques. Les modèles ARCH d'ordre infini ont été introduits afin de permettre une modélisation plus fine de ces faits stylisés, et en particulier le phénomène de forte persistance des chocs de volatilités. Nous présentons de nouvelles extensions à ces modèles flexibles et étudions leur inférence. En premier lieu, nous considérons un modèle ARCH d'ordre infini asymétrique. Nous démontrons l'existence d'une solution stationnaire et nous établissons les propriétés asymptotiques de l'estimateur de quasi-maximum de vraisemblance dans le cadre de ce modèle. En particulier, nous permettons au paramètre d'être sur le bord de l'espace des paramètres, empêchant la normalité asymptotique. De plus, nous introduisons un test portmanteau vérifiant l'adéquation du modèle aux données ainsi qu'un test statistique pour la présence de mémoire et d'asymétrie. Dans un second temps, nous nous intéressons à la modélisation des coefficients d'une régression linéaire conditionnelle. Les modèles à facteurs linéaires sont au cœur de nombreux modèles financiers et souvent, les coefficients de régressions sont supposés constants. Nous proposons un modèle permettant la mesure de la dynamique de ces coefficients Bêtas dans le cadre des modèles ARCH d'ordre infini multivariés. En particulier, nous permettons l'ajout de variables exogènes dans la dynamique des Bêtas conditionnels et discutons de potentiels candidats. Nous établissons les conditions d'existence d'une solution stationnaire et discutons l'existence de moments de cette dernière. Enfin, nous considérons un exercice de valorisation d'actifs basé sur des Bêtas dynamiques. A cet effet, nous étendons les résultats de tests statistiques dans le cas de Bêtas dérivés d'un modèle GAS et proposons une procédure de rééchantillonnage. Nous introduisons une méthode d'estimation en deux étapes pour mesurer les primes de risque dynamiques sous-jacentes au modèle d'évaluation
The modeling of financial time series is made difficult by the presence of stylized facts. These empirical statistical properties led to the development of heteroskedastic nonlinear models. Infinite ARCH specifications have been introduced to allow finer modeling of these stylized facts, and in particular the phenomenon of strong persistence of volatility shocks. We present new extensions to these flexible models and study their inference. First, we consider an asymmetric infinite ARCH model. We prove the existence of a stationary solution and establish the asymptotic properties of the quasi-maximum likelihood estimator in this framework. In particular, we allow the parameter to lie on the boundary of the parameter space, precluding asymptotic normality. Moreover, we introduce a portmanteau test assessing the goodness-of-fit of the model on data. We also propose a test for the presence of memory and asymmetry. In a second time, we consider the modeling of the coefficients of a conditional linear regression. Linear factor models are key to many financial models and regression coefficients are often wrongfully assumed constant. We propose a model allowing for dynamic beta coefficients within the framework of multivariate infinite ARCH models. In particular, we allow the addition of exogenous variables in the dynamics of conditional betas and discuss potential candidates. We establish the conditions of existence of a stationary solution and discuss the existence of its moments. Finally, we consider an asset pricing exercise based on dynamic betas. To this end, we extend the results of statistical tests in the case of score-driven betas and propose a bootstrap procedure. Additionally, we introduce a two-step estimation method to measure the dynamic risk premia underlying the asset pricing model

Latent tuberculosis infection is an asymptomatic condition in which patients carry the bacteria, but do not show any sign of illness, however they are at risk of disease activation at any time in the future. Understanding of influence of latent tuberculosis infection on the physical and mental well-being of these patients is important as successful strategies to reduce the tuberculosis burden globally. Our purpose is to explore patients during diagnosis and treatment of latent tuberculosis infection, measure their quality of life. Materials and methods: during 2017–2019 was examined 100 children 4–7 years age. Children were divided in 3 groups. First group (n = 40) - a children with LTI. Group of the comparison (n = 40) has comprised preschool age children with tuberculosis. Group of the checking (n = 20) have constituted the preschool age healthy children. Estimation of children health was conducted by analysis health factors: social, genetic, biological. In addition were studied criteria of health. It was used study anamnestic data, questioning, estimation quality of life, anthropometry, data of objective examination, laboratory data and parameters of functioning, electrocardiography, vegetative nervous system spectrography (VNS-spectrography), manual ergometry. Physical development valued with the help of specialized tables. Leukocyte intoxication index is calculated on formula Shemitova V.F. Variety heart rhythm (VHR) was studied by method VNS-spectrography on vegetotester “VNS-Micro” with computer program “Polispectr” of company “Neyrosoft”. Interpretation source vegetative tone and vegetative reactivity was realized according to recommendation N.A. Belokon. Vegetative provision of activity was valued on tolerance to steady-state load by method manual ergometry (MEM) in help of manual dynamometer. Quality of life was defined with the help of questionnaire PedsQL version 4.0 (the Russian version). Results and their discussion: in children with active tuberculosis, specific process has a most negative influence upon quality of life, comparatively temporary negative influence has LTI. Revealed changes in general have brought to reduction of QL indicators both in first and second group. With provision of latency currents of infecting with mycobacteria of tuberculosis, indicators of quality of life should be considered as one of defining, reflecting psychological component adaptation of child, and can be recommended to enter in program of examination and dispensary observation of children with LTI. Conclusions: our study has shown that preschool age children with LTI have rather significant deflections of health condition, revealing by symptoms of intoxication, expressed breaches adaptation and regulation mechanisms. Results of study have logistical confirmed need of improvement of the preventive maintenance and dispensary observation at children with LTI and active participation in its base of the interdepartmental approach. All of this allows newly taking a look at problem of the latent tuberculous infection at preschool age children and role general practitioner in preventive maintenance of the development such dangerous diseases as tuberculosis.