Modelling Nonlinear Economic Time Series

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Modelling Nonlinear Economic Time Series

Author : Timo Teräsvirta,Dag Tjøstheim,Clive W. J. Granger
Publisher : OUP Oxford
Page : 592 pages
File Size : 55,5 Mb
Release : 2010-12-16
Category : Business & Economics
ISBN : 0199587140

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Modelling Nonlinear Economic Time Series by Timo Teräsvirta,Dag Tjøstheim,Clive W. J. Granger Pdf

This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For thispurpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried outusing numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter isdevoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.

Modelling Nonlinear Economic Time Series

Author : Timo Teräsvirta,Clive William John Granger,Dag Tjøstheim
Publisher : Unknown
Page : 557 pages
File Size : 47,9 Mb
Release : 2010
Category : Econometric models
ISBN : 0191595381

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Modelling Nonlinear Economic Time Series by Timo Teräsvirta,Clive William John Granger,Dag Tjøstheim Pdf

A comprehensive assessment of many recent developments in the modelling of time series, this text introduces various nonlinear models and discusses their practical use, encouraging the reader to apply nonlinear models to their practical modelling problems.

Non-Linear Time Series Models in Empirical Finance

Author : Philip Hans Franses,Dick van Dijk
Publisher : Cambridge University Press
Page : 299 pages
File Size : 52,9 Mb
Release : 2000-07-27
Category : Business & Economics
ISBN : 9780521770415

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Non-Linear Time Series Models in Empirical Finance by Philip Hans Franses,Dick van Dijk Pdf

This 2000 volume reviews non-linear time series models, and their applications to financial markets.

Nonlinear Econometric Modeling in Time Series

Author : William A. Barnett
Publisher : Cambridge University Press
Page : 248 pages
File Size : 51,6 Mb
Release : 2000-05-22
Category : Business & Economics
ISBN : 0521594243

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Nonlinear Econometric Modeling in Time Series by William A. Barnett Pdf

This book presents some of the more recent developments in nonlinear time series, including Bayesian analysis and cointegration tests.

Nonlinear Time Series Analysis of Economic and Financial Data

Author : Philip Rothman
Publisher : Springer Science & Business Media
Page : 379 pages
File Size : 46,7 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461551294

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Nonlinear Time Series Analysis of Economic and Financial Data by Philip Rothman Pdf

Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.

Time Series Techniques for Economists

Author : Terence C. Mills
Publisher : Cambridge University Press
Page : 392 pages
File Size : 44,6 Mb
Release : 1990
Category : Business & Economics
ISBN : 0521405742

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Time Series Techniques for Economists by Terence C. Mills Pdf

The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.

Modelling Trends and Cycles in Economic Time Series

Author : Terence C. Mills
Publisher : Springer Nature
Page : 219 pages
File Size : 44,5 Mb
Release : 2021-07-29
Category : Business & Economics
ISBN : 9783030763596

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Modelling Trends and Cycles in Economic Time Series by Terence C. Mills Pdf

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

Essays in Nonlinear Time Series Econometrics

Author : Niels Haldrup,Mika Meitz,Pentti Saikkonen
Publisher : Oxford University Press
Page : 393 pages
File Size : 55,9 Mb
Release : 2014-05
Category : Business & Economics
ISBN : 9780199679959

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Essays in Nonlinear Time Series Econometrics by Niels Haldrup,Mika Meitz,Pentti Saikkonen Pdf

A book on nonlinear economic relations that involve time. It covers specification testing of linear versus non-linear models, model specification testing, estimation of smooth transition models, volatility modelling using non-linear model specification, analysis of high dimensional data set, and forecasting.

Nonlinear Time Series

Author : Jianqing Fan,Qiwei Yao
Publisher : Springer Science & Business Media
Page : 565 pages
File Size : 53,7 Mb
Release : 2008-09-11
Category : Mathematics
ISBN : 9780387693958

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Nonlinear Time Series by Jianqing Fan,Qiwei Yao Pdf

This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

Modelling Nonlinear Economic Relationships

Author : Clive William John Granger,Timo Teräsvirta
Publisher : Oxford University Press, USA
Page : 187 pages
File Size : 52,9 Mb
Release : 1993
Category : Social Science
ISBN : 0198773196

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Modelling Nonlinear Economic Relationships by Clive William John Granger,Timo Teräsvirta Pdf

Economic Time Series

Author : William R. Bell,Scott H. Holan,Tucker S. McElroy
Publisher : CRC Press
Page : 554 pages
File Size : 44,7 Mb
Release : 2012-03-19
Category : Mathematics
ISBN : 9781439846582

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Economic Time Series by William R. Bell,Scott H. Holan,Tucker S. McElroy Pdf

Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies. For easier perusal and absorption, the contents have been grouped into seven topical sections: Section I deals with periodic modeling of time series, introducing, applying, and comparing various seasonally periodic models Section II examines the estimation of time series components when models for series are misspecified in some sense, and the broader implications this has for seasonal adjustment and business cycle estimation Section III examines the quantification of error in X-11 seasonal adjustments, with comparisons to error in model-based seasonal adjustments Section IV discusses some practical problems that arise in seasonal adjustment: developing asymmetric trend-cycle filters, dealing with both temporal and contemporaneous benchmark constraints, detecting trading-day effects in monthly and quarterly time series, and using diagnostics in conjunction with model-based seasonal adjustment Section V explores outlier detection and the modeling of time series containing extreme values, developing new procedures and extending previous work Section VI examines some alternative models and inference procedures for analysis of seasonal economic time series Section VII deals with aspects of modeling, estimation, and forecasting for nonseasonal economic time series By presenting new methodological developments as well as pertinent empirical analyses and reviews of established methods, the book provides much that is stimulating and practically useful for the serious researcher and analyst of economic time series.

Modeling Financial Time Series with S-PLUS

Author : Eric Zivot,Jiahui Wang
Publisher : Springer Science & Business Media
Page : 632 pages
File Size : 55,7 Mb
Release : 2013-11-11
Category : Business & Economics
ISBN : 9780387217635

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Modeling Financial Time Series with S-PLUS by Eric Zivot,Jiahui Wang Pdf

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.

Time Series Models for Business and Economic Forecasting

Author : Philip Hans Franses
Publisher : Cambridge University Press
Page : 300 pages
File Size : 53,6 Mb
Release : 1998-10-15
Category : Business & Economics
ISBN : 0521586410

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Time Series Models for Business and Economic Forecasting by Philip Hans Franses Pdf

An introduction to time series models for business and economic forecasting.

Nonlinear Economic Models

Author : John Creedy,Vance Martin
Publisher : Edward Elgar Publishing
Page : 312 pages
File Size : 50,5 Mb
Release : 1997
Category : Business & Economics
ISBN : STANFORD:36105022825264

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Nonlinear Economic Models by John Creedy,Vance Martin Pdf

A sequel to Creedy and Martin's (eds.) Chaos and Nonlinear Models (1994). Compiles recent developments in such techniques as cross- sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural networks and genetic algorithms of financial markets. Also considers the development of theoretical models and estimating and testing methods, with a wide range of applications in microeconomics, macroeconomics, labor, and finance. Annotation copyrighted by Book News, Inc., Portland, OR

Periodic Time Series Models

Author : Philip Hans Franses,Richard Paap
Publisher : OUP Oxford
Page : 166 pages
File Size : 44,6 Mb
Release : 2004-03-25
Category : Business & Economics
ISBN : 9780191529269

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Periodic Time Series Models by Philip Hans Franses,Richard Paap Pdf

This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking and forecasting of univariate periodic autoregressive models. Tests for periodic integration, are discussed, and an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting is provided. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, as these are the most relevant. This overview contains single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be of interest to advanced graduate students and researchers in econometrics, as well as practitioners looking for an understanding of how to approach seasonal data.