Essays in Nonlinear Time Series Econometrics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Essays in Nonlinear Time Series Econometrics PDF full book. Access full book title Essays in Nonlinear Time Series Econometrics by Niels Haldrup. Download full books in PDF and EPUB format.
Author: Niels Haldrup
Publisher: OUP Oxford
ISBN: 0191669547
Category : Business & Economics
Languages : en
Pages : 393
Get Book Here
Book Description
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Author: Niels Haldrup
Publisher: OUP Oxford
ISBN: 0191669547
Category : Business & Economics
Languages : en
Pages : 393
Get Book Here
Book Description
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Author: Jan G. De Gooijer
Publisher: Springer
ISBN: 3319432524
Category : Mathematics
Languages : en
Pages : 626
Get Book Here
Book Description
This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.
Author: Mark Watson
Publisher: Oxford University Press
ISBN: 0199549494
Category : Business & Economics
Languages : en
Pages : 432
Get Book Here
Book Description
A volume that celebrates and develops the work of Nobel Laureate Robert Engle, it includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics
Author: Thomas B. Fomby
Publisher: Emerald Group Publishing
ISBN: 1784411825
Category : Political Science
Languages : en
Pages : 772
Get Book Here
Book Description
This volume honors Professor Peter C.B. Phillips' many contributions to the field of econometrics. The topics include non-stationary time series, panel models, financial econometrics, predictive tests, IV estimation and inference, difference-in-difference regressions, stochastic dominance techniques, and information matrix testing.
Author: Clive W. J. Granger
Publisher: Cambridge University Press
ISBN: 9780521774963
Category : Business & Economics
Languages : en
Pages : 548
Get Book Here
Book Description
These are econometrician Clive W. J. Granger's major essays in spectral analysis, seasonality, nonlinearity, methodology, and forecasting.
Author: Jun Ma
Publisher: Springer Science & Business Media
ISBN: 1461480604
Category : Business & Economics
Languages : en
Pages : 308
Get Book Here
Book Description
Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among several others. This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. It features cutting-edge research from leading academics in economics, finance, and business management, and will focus on such topics as Zero-Information-Limit-Conditions, using Markov Switching Models to analyze economics series, and how best to distinguish between competing nonlinear models. Principles and techniques in this book will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.
Author: Dag Tjøstheim
Publisher: Academic Press
ISBN: 0128154454
Category : Business & Economics
Languages : en
Pages : 460
Get Book Here
Book Description
Statistical Modeling using Local Gaussian Approximation extends powerful characteristics of the Gaussian distribution, perhaps, the most well-known and most used distribution in statistics, to a large class of non-Gaussian and nonlinear situations through local approximation. This extension enables the reader to follow new methods in assessing dependence and conditional dependence, in estimating probability and spectral density functions, and in discrimination. Chapters in this release cover Parametric, nonparametric, locally parametric, Dependence, Local Gaussian correlation and dependence, Local Gaussian correlation and the copula, Applications in finance, and more. Additional chapters explores Measuring dependence and testing for independence, Time series dependence and spectral analysis, Multivariate density estimation, Conditional density estimation, The local Gaussian partial correlation, Regression and conditional regression quantiles, and a A local Gaussian Fisher discriminant. - Reviews local dependence modeling with applications to time series and finance markets - Introduces new techniques for density estimation, conditional density estimation, and tests of conditional independence with applications in economics - Evaluates local spectral analysis, discovering hidden frequencies in extremes and hidden phase differences - Integrates textual content with three useful R packages
Author: Jennifer Castle
Publisher: Yale University Press
ISBN: 0300244665
Category : Business & Economics
Languages : en
Pages : 228
Get Book Here
Book Description
Concise, engaging, and highly intuitive--this accessible guide equips you with an understanding of all the basic principles of forecasting Making accurate predictions about the economy has always been difficult, as F. A. Hayek noted when accepting his Nobel Prize in economics, but today forecasters have to contend with increasing complexity and unpredictable feedback loops. In this accessible and engaging guide, David Hendry, Michael Clements, and Jennifer Castle provide a concise and highly intuitive overview of the process and problems of forecasting. They explain forecasting concepts including how to evaluate forecasts, how to respond to forecast failures, and the challenges of forecasting accurately in a rapidly changing world. Topics covered include: What is a forecast? How are forecasts judged? And how can forecast failure be avoided? Concepts are illustrated using real-world examples including financial crises, the uncertainty of Brexit, and the Federal Reserve's record on forecasting. This is an ideal introduction for university students studying forecasting, practitioners new to the field and for general readers interested in how economists forecast.
Author: Jennifer L. Castle
Publisher: Springer Nature
ISBN: 303021432X
Category : Business & Economics
Languages : en
Pages : 142
Get Book Here
Book Description
This open access book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temperatures, to modelling unemployment rates, wage inflation and population growth. Except where otherwise noted, this book is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0.
Author: Peter Fuleky
Publisher: Springer Nature
ISBN: 3030311503
Category : Business & Economics
Languages : en
Pages : 716
Get Book Here
Book Description
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
