Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Consistency Of Quasi Maximum Likelihood Estimators For Models With Conditional Heteroskedasticity
Download Consistency Of Quasi Maximum Likelihood Estimators For Models With Conditional Heteroskedasticity full books in PDF, epub, and Kindle. Read online Consistency Of Quasi Maximum Likelihood Estimators For Models With Conditional Heteroskedasticity ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Consistency of Quasi-Maximum Likelihood Estimators for Models with Conditional Heteroskedasticity by : Whitney K. Newey
Download or read book Consistency of Quasi-Maximum Likelihood Estimators for Models with Conditional Heteroskedasticity written by Whitney K. Newey and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Virtually all empirical studies that assume a time-varying conditional variance use a quasi-maximum likelihood estimator (QMLE). If the density from which the likelihood is constructed is assumed to be Gaussian, the QMLE is known to be consistent under correct specification of both the conditional mean and conditional variance. We show that if both the assumed density and the true density are symmetric a QMLE remains consistent. If, however, either the assumed density or the true density is asymmetric, a QMLE is generally not consistent. To ensure that a QMLE is consistent under asymmetric densities, we include the conditional standard deviation as a regressor. We calculate the efficiency loss associated with the added regressor if the densities are symmetric and show that for a QMLE of the conditional variance parameters of a GARCH process there is no efficiency loss. Finally, we develop a test of consistency of a QMLE from the significance of the additional regressor.
Book Synopsis Consistency of Quasi Maximum Likelihood Estimators for Models with Conditional Heteroscedasticity by : Whitney K. Newey
Download or read book Consistency of Quasi Maximum Likelihood Estimators for Models with Conditional Heteroscedasticity written by Whitney K. Newey and published by . This book was released on 1994 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Maximum Likelihood Estimation of Misspecified Models by : T. Fomby
Download or read book Maximum Likelihood Estimation of Misspecified Models written by T. Fomby and published by Elsevier. This book was released on 2003-12-12 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.
Book Synopsis Quasi-maximum Likelihood Estimation of Heteroskedastic Fractional Time Series Models by : Giuseppe Cavaliere
Download or read book Quasi-maximum Likelihood Estimation of Heteroskedastic Fractional Time Series Models written by Giuseppe Cavaliere and published by . This book was released on 2014 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Consistency of Quasi-maximum Likelihood Estimators for the Reduced Regime-switching GARCH Models by : Yingfu Xie
Download or read book Consistency of Quasi-maximum Likelihood Estimators for the Reduced Regime-switching GARCH Models written by Yingfu Xie and published by . This book was released on 2005 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Consistency of Quasi-maximum Likelihood Estimators for the Regime-switching GARCH Models by : Yingfu Xie
Download or read book Consistency of Quasi-maximum Likelihood Estimators for the Regime-switching GARCH Models written by Yingfu Xie and published by . This book was released on 2005 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis On the Weak Consistency of the Quasi-maximum Likelihood Estimator in Var Models with Bekkk-Garch (1,q) Errors by : L. Bauwens
Download or read book On the Weak Consistency of the Quasi-maximum Likelihood Estimator in Var Models with Bekkk-Garch (1,q) Errors written by L. Bauwens and published by . This book was released on 1995 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Quasi-Maximum Likelihood Estimation for Conditional Expectiles by : Collin Philipps
Download or read book Quasi-Maximum Likelihood Estimation for Conditional Expectiles written by Collin Philipps and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We characterize the quasi-likelihood functions that may elicit expectiles and find that the family has a unique representation under standard conditions for linear regression. The only distribution that elicits expectiles as its quasi-maximum likelihood estimator under general conditions is an asymmetric normal distribution. Next, we analyze the quasi maximum likelihood estimator and give conditions for consistency, asymptotic normality, and efficiency. The estimator is unique up to the choice of weights on individual observations and nests the usual GLS estimator. We give the asymptotic MVUE and a uniform Cramer-Rao theorem for expectile regression.
Book Synopsis On the Weak Consistency of the Quasi-maximum Likelihood Estimator in VAR Models with BEKK-GARCH(1,q) Errors by : Luc Bauwens
Download or read book On the Weak Consistency of the Quasi-maximum Likelihood Estimator in VAR Models with BEKK-GARCH(1,q) Errors written by Luc Bauwens and published by . This book was released on 1995 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Macroeconometrics by : Kevin D. Hoover
Download or read book Macroeconometrics written by Kevin D. Hoover and published by Springer Science & Business Media. This book was released on 1995-12-31 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each chapter of Macroeconometrics is written by respected econometricians in order to provide useful information and perspectives for those who wish to apply econometrics in macroeconomics. The chapters are all written with clear methodological perspectives, making the virtues and limitations of particular econometric approaches accessible to a general readership familiar with applied macroeconomics. The real tensions in macroeconometrics are revealed by the critical comments from different econometricians, having an alternative perspective, which follow each chapter.
Book Synopsis Estimation in Conditionally Heteroscedastic Time Series Models by : Daniel Straumann
Download or read book Estimation in Conditionally Heteroscedastic Time Series Models written by Daniel Straumann and published by Springer Science & Business Media. This book was released on 2006-01-27 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies.
Book Synopsis Quasi-Likelihood And Its Application by : Christopher C. Heyde
Download or read book Quasi-Likelihood And Its Application written by Christopher C. Heyde and published by Springer Science & Business Media. This book was released on 2008-01-08 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first account in book form of all the essential features of the quasi-likelihood methodology, stressing its value as a general purpose inferential tool. The treatment is rather informal, emphasizing essential principles rather than detailed proofs, and readers are assumed to have a firm grounding in probability and statistics at the graduate level. Many examples of the use of the methods in both classical statistical and stochastic process contexts are provided.
Book Synopsis Parameter Estimation in Nonlinear AR-GARCH Models by : Mika Meitz
Download or read book Parameter Estimation in Nonlinear AR-GARCH Models written by Mika Meitz and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a functional coefficient 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. 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.
Book Synopsis QMLE for Quadratic Arch Model with Long Memory by : Ieva Grublytė
Download or read book QMLE for Quadratic Arch Model with Long Memory written by Ieva Grublytė and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We discuss parametric quasi-maximum likelihood estimation for quadratic autoregressive conditional heteroskedasticity (ARCH) process with long memory introduced in Doukhan emphet al. (2016) and Grublytė and Škarnulis (2016) with conditional variance involving the square of inhomogeneous linear combination of observable sequence with square summable weights. The aforementioned model extends the quadratic ARCH model of Sentana ([Sentana E, 1995]) and the linear ARCH model of Robinson ([Robinson PM, 1991]) to the case of strictly positive conditional variance. We prove consistency and asymptotic normality of the corresponding quasi-maximum likelihood estimates, including the estimate of long memory parameter 0
Book Synopsis On Asymptotic Theory for Arch (∞) Models by : Christian Hafner
Download or read book On Asymptotic Theory for Arch (∞) Models written by Christian Hafner and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autoregressive conditional heteroskedasticity (ARCH)() models nest a wide range of ARCH and generalized ARCH models including models with long memory in volatility. Existing work assumes the existence of second moments. However, the fractionally integrated generalized ARCH model, one version of a long memory in volatility model, does not have finite second moments and rarely satisfies the moment conditions of the existing literature. This article weakens the moment assumptions of a general ARCH() class of models and develops the theory for consistency and asymptotic normality of the quasi-maximum likelihood estimator.
Book Synopsis On the Three-Step Non-Gaussian Quasi-Maximum Likelihood Estimation of Heavy-Tailed Double Autoregressive Models by : Dong Li
Download or read book On the Three-Step Non-Gaussian Quasi-Maximum Likelihood Estimation of Heavy-Tailed Double Autoregressive Models written by Dong Li and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This note considers a three-step non-Gaussian quasi-maximum likelihood estimation (TS-NGQMLE) of the double autoregressive model with its asymptotics, which improves efficiency of the GQMLE and circumvents inconsistency of the NGQMLE when the innovation is heavy-tailed. Under mild conditions, the estimator not only can achieve consistency and asymptotic normality regardless of density misspecification of the innovation, but also outperforms the existing estimators, such as the GQMLE and the (weighted) least absolute deviation estimator, when the innovation is indeed heavy-tailed.
Book Synopsis Statistics And Finance: An Interface - Proceedings Of The Hong Kong International Workshop On Statistics In Finance by : Wai-sum Chan
Download or read book Statistics And Finance: An Interface - Proceedings Of The Hong Kong International Workshop On Statistics In Finance written by Wai-sum Chan and published by World Scientific. This book was released on 2000-04-28 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Heavy-Tailed and Nonlinear Continuous-Time ARMA Models for Financial Time Series (P J Brockwell)Nonlinear State Space Model Approach to Financial Time Series with Time-Varying Variance (G Kitagawa & S Sato)Nonparametric Estimation and Bootstrap for Financial Time Series (J-P Kreiβ)A Note on Kernel Estimation in Integrated Time Series (Y-C Xia et al.)Stylized Facts on the Temporal and Distributional Properties of Absolute Returns: An Update (C W J Granger et al.)Volatility Computed by Time Series Operators at High Frequency (U A Müller)Missing Values in ARFIMA Models (W Palma)Second Order Tail Effects (C G de Vries)Bayesian Estimation of Stochastic Volatility Model via Scale Mixtures Distributions (S T B Choy & C M Chan)On a Smooth Transition Double Threshold Model (Y N Lee & W K Li)Interval Prediction of Financial Time Series (B Cheng & H Tong)A Decision Theoretic Approach to Forecast Evaluation (C W J Granger & M H Pesaran)Portfolio Management and Market Risk Quantification Using Neural Networks (J Franke)Detecting Structural Changes Using Genetic Programming with an Application to the Greater-China Stock Markets (X B Zhang et al.)and other papers Readership: Researchers in finance, time series analysis, economics and actuarial science, as well as investment bankers, stock market analysts and risk managers. Keywords:Proceedings;Workshop;Statistics;Finance;Hongkong (China)
