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Unobserved Components In Arch Models

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Unobserved Components In Arch Models

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Author : Gabriele Fiorentini
language : en
Publisher:
Release Date : 1994

Unobserved Components In Arch Models written by Gabriele Fiorentini and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Autoregression (Statistics) categories.

Unobserved Components In Arch Models

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Author : Gabriele Fiorentini
language : en
Publisher:
Release Date : 1993

Unobserved Components In Arch Models

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Author : Gabriele Fiorentini
language : de
Publisher:
Release Date : 1993

Unobserved Components And Time Series Econometrics

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Author : Siem Jan Koopman
language : en
Publisher: Oxford University Press
Release Date : 2015

Unobserved Components And Time Series Econometrics written by Siem Jan Koopman and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Business & Economics categories.

Presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and methodological perspectives.

Readings In Unobserved Components Models

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Author : Andrew Harvey
language : en
Publisher: OUP Oxford
Release Date : 2005-04-07

Readings In Unobserved Components Models written by Andrew Harvey and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-07 with Business & Economics categories.

This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature. - ;This book presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. It contains four parts, three of which concern recent theoretical developments in classical and Bayesian estimation of linear, nonlinear, and non Gaussian UC models, signal extraction and testing, and one is devoted to selected econometric applications. The first part focuses on the linear state space model; the readings provide insight on prediction theory, signal extraction, and likelihood inference for non stationary and non invertible processes, diagnostic checking, and the use of state space methods for spline smoothing. Part II deals with applications of linear UC models to various estimation problems concerning economic time series, such as trend-cycle decompositions, seasonal adjustment, and the modelling of the serial correlation induced by survey sample design. The issues involved in testing in linear UC models are the theme of part III, which considers tests concerned with whether or not certain variance parameters are zero, with special reference to stationarity tests. Finally, part IV is devoted to the advances concerning classical and Bayesian inference for non linear and non Gaussian state space models, an area that has been evolving very rapidly during the last decade, paralleling the advances in computational inference using stochastic simulation techniques. The book is intended to give a relatively self-contained presentation of the methods and applicative issues. For this purpose, each part comes with an introductory chapter by the editors that provides a unified view of the literature and the many important developments that have occurred in the last years. -

State Space And Unobserved Component Models

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Author : James Durbin
language : en
Publisher: Cambridge University Press
Release Date : 2004-06-10

State Space And Unobserved Component Models written by James Durbin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-10 with Business & Economics categories.

A comprehensive overview of developments in the theory and application of state space modeling, first published in 2004.

Arch Models For Financial Applications

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Author : Evdokia Xekalaki
language : en
Publisher: John Wiley & Sons
Release Date : 2010-03-18

Arch Models For Financial Applications written by Evdokia Xekalaki and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-18 with Mathematics categories.

Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to model asset price volatility over time. This book introduces both the theory and applications of ARCH models and provides the basic theoretical and empirical background, before proceeding to more advanced issues and applications. The Authors provide coverage of the recent developments in ARCH modelling which can be implemented using econometric software, model construction, fitting and forecasting and model evaluation and selection. Key Features: Presents a comprehensive overview of both the theory and the practical applications of ARCH, an increasingly popular financial modelling technique. Assumes no prior knowledge of ARCH models; the basics such as model construction are introduced, before proceeding to more complex applications such as value-at-risk, option pricing and model evaluation. Uses empirical examples to demonstrate how the recent developments in ARCH can be implemented. Provides step-by-step instructive examples, using econometric software, such as Econometric Views and the G@RCH module for the Ox software package, used in Estimating and Forecasting ARCH Models. Accompanied by a CD-ROM containing links to the software as well as the datasets used in the examples. Aimed at readers wishing to gain an aptitude in the applications of financial econometric modelling with a focus on practical implementation, via applications to real data and via examples worked with econometrics packages.

Forecasting Economic Time Series

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Author : C. W. J. Granger
language : en
Publisher: Academic Press
Release Date : 2014-05-10

Forecasting Economic Time Series written by C. W. J. Granger and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Business & Economics categories.

Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.

Gauss Programs For The Estimation Of State Space Models With Arch Errors

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Author : Maral Kichian
language : en
Publisher:
Release Date : 2000

Gauss Programs For The Estimation Of State Space Models With Arch Errors written by Maral Kichian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Banks and banking categories.

The purpose of this paper is to explain the use of the GAUSS programs developed to estimate a state-space model with autoregressive conditional heteroskedastic (ARCH) errors. The programs are based on the Harvey, Ruiz & Sentana (1992) paper, are flexible, and allow the user to estimate a wide variety of economic models with or without ARCH errors. The impetus for writing these programs came from the need to estimate an unobserved components model with ARCH expectations for the explicit purposes of estimating Canadian potential output and forecasting inflation. Section 2 of the paper presents the model and explains notations. Section 3 explains the GAUSS code, indicating which parts to modify in order to set up a particular model. Section 4 contains two examples that demonstrate the flexibility and limitations of the code.

Garch Models

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Author : Christian Francq
language : en
Publisher: John Wiley & Sons
Release Date : 2019-06-10

Garch Models written by Christian Francq and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Mathematics categories.

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.

Unobserved Components In Arch Models

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