Download or read book Asymptotic Theory for GARCH in mean Models written by Weiwei Liu and published by . This book was released on 2013 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The GARCH-in-mean process is an important extension of the standard GARCH (generalized autoregressive conditional heteroscedastic) process and it has wide applications in economics and finance. The parameter estimation of GARCH type models usually involves the quasi-maximum likelihood (QML) technique as it produces consistent and asymptotically Gaussian distributed estimators under certain regularity conditions. For a pure GARCH model, such conditions were already found with asymptotic properties of its QML estimator well understood. However, when it comes to GARCH-in-mean models those properties are still largely unknown. The focus of this work is to establish a set of conditions under which the QML estimator of GARCH-in-mean models will have the desired asymptotic properties. Some general Markov model tools are applied to derive the result.
Download or read book Asymptotics for Parametric GARCH in Mean Models written by Christian Conrad and published by . This book was released on 2017 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we develop an asymptotic theory for the Quasi-Maximum Likelihood Estimator (QMLE) of the parametric GARCH-in-Mean model. The asymptotics is based on a study of the volatility as a process of the model parameters. The proof makes use of stochastic recurrence equations for this random function and uses exponential inequalities to localize the problem. Our results show why the asymptotics for this specification is quite complex although it is a rather standard parametric model. Nevertheless, our theory does not yet treat all standard specifications of the mean function.
Download or read book Topics in Asymptotic Theory for Garch type Models written by Kazuhiko Shinki and published by . This book was released on 2010 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Theory for a Factor GARCH Model written by Christian M. Hafner and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Theory of General Multivariate GARCH Models written by Weibin Jiang and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financial markets. Parameters of GARCH models are usually estimated by the quasi-maximum likelihood estimator (QMLE). In recent years, economic theory often implies equilibrium between the levels of time series, which makes the application of multivariate models a necessity. Unfortunately the asymptotic theory of the multivariate GARCH models is far from coherent since many algorithms on the univariate case do not extend to multivariate models naturally. This thesis studies the asymptotic theory of the QMLE under mild conditions. We give some counterexamples for the parameter identifiability result in Jeantheau [1998] and provide a better necessary and sufficient condition. We prove the ergodicity of the conditional variance process on an application of theorems by Meyn and Tweedie [2009]. Under those conditions, the consistency and asymptotic normality of the QMLE can be proved by the standard compactness argument and Taylor expansion of the score function. We also give numeric example on verifying the assumptions and the scaling issue when estimating GARCH parameters in S+ FinMetrics.
Download or read book Asymptotic Theory for QMLE for Real Time GARCH 1 1 Model written by Ekaterina Smetanina and published by . This book was released on 2019 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate the asymptotic properties of the Gaussian Quasi-Maximum-Likelihood estimator (QMLE) for the Real-time GARCH(1,1) model of Smetanina (2017). The developed theory relies on the new dependence measure developed in Wu (2005) and is substantially different to the standard asymptotic theory for GARCH models. We prove consistency and asymptotic normality for the parameter vector at the usual √T rate. Finally, as part of the developed theory we also demonstrate how convergence rates of uniform laws of large numbers can be established via the powerful maximal inequalities for high-dimensional heavy-tailed time series using uniform functional dependence measure.
Download or read book Structure and Asymptotic Theory for Nonlinear Models with GARCH Errors written by Felix Chan and published by . This book was released on 2010 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Theory for the QMLE in GARCH X Models with Stationary and Non stationary Covariates written by Heejoon Han and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book GARCH Models written by Christian Francq and published by John Wiley & Sons. This book was released on 2011-06-24 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation and tests. The book also provides coverage of several extensions such as asymmetric and multivariate models and looks at financial applications. Key features: Provides up-to-date coverage of the current research in the probability, statistics and econometric theory of GARCH models. Numerous illustrations and applications to real financial series are provided. Supporting website featuring R codes, Fortran programs and data sets. Presents a large collection of problems and exercises. This authoritative, state-of-the-art reference is ideal for graduate students, researchers and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.
Download or read book GARCH Models written by Christian Francq and published by John Wiley & Sons. This book was released on 2019-06-10 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation, and tests. The book also provides new coverage of several extensions such as multivariate models, looks at financial applications, and explores the very validation of the models used. GARCH Models: Structure, Statistical Inference and Financial Applications, 2nd Edition features a new chapter on Parameter-Driven Volatility Models, which covers Stochastic Volatility Models and Markov Switching Volatility Models. A second new chapter titled Alternative Models for the Conditional Variance contains a section on Stochastic Recurrence Equations and additional material on EGARCH, Log-GARCH, GAS, MIDAS, and intraday volatility models, among others. The book is also updated with a more complete discussion of multivariate GARCH; a new section on Cholesky GARCH; a larger emphasis on the inference of multivariate GARCH models; a new set of corrected problems available online; and an up-to-date list of references. Features up-to-date coverage of the current research in the probability, statistics, and econometric theory of GARCH models Covers significant developments in the field, especially in multivariate models Contains completely renewed chapters with new topics and results Handles both theoretical and applied aspects Applies to researchers in different fields (time series, econometrics, finance) Includes numerous illustrations and applications to real financial series Presents a large collection of exercises with corrections Supplemented by a supporting website featuring R codes, Fortran programs, data sets and Problems with corrections GARCH Models, 2nd Edition is an authoritative, state-of-the-art reference that is ideal for graduate students, researchers, and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.
Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
Download or read book A Tour in the Asymptotic Theory of GARCH Estimation written by Christian Francq and published by . This book was released on 2008 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Theory for Multivariate GARCH Processes written by F. Comte and published by . This book was released on 2001 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Theory in Probability and Statistics with Applications written by T. L. Lai and published by . This book was released on 2008 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a collection of 18 papers, many of which are surveys, on asymptotic theory in probability and statistics, with applications to a variety of problems. This volume comprises three parts: limit theorems, statistics and applications, and mathematical finance and insurance. It is suitable for graduate students in probability and statistics.
Download or read book Asymptotic Theory for ARCH Models written by Andrew A. Weiss and published by . This book was released on 1982 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic Models for Volatility and Heavy Tails written by Andrew C. Harvey and published by Cambridge University Press. This book was released on 2013-04-22 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.
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.
