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Modelling Nonlinear Economic Time Series

Author : Timo Teräsvirta
Publisher : OUP Oxford
Page : 592 pages
File Size : 14,44 MB
Release : 2010-12-16
Category : Business & Economics
ISBN : 9780199587148

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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
Publisher :
Page : 557 pages
File Size : 28,47 MB
Release : 2010
Category : Econometric models
ISBN : 9780191595387

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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
Publisher : Cambridge University Press
Page : 299 pages
File Size : 15,97 MB
Release : 2000-07-27
Category : Business & Economics
ISBN : 0521770416

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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 : 10,56 MB
Release : 2000-05-22
Category : Business & Economics
ISBN : 9780521594240

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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 : 20,12 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 1461551293

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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.

Nonlinear Time Series

Author : Jianqing Fan
Publisher : Springer Science & Business Media
Page : 565 pages
File Size : 37,79 MB
Release : 2008-09-11
Category : Mathematics
ISBN : 0387693955

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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.

Non-Linear Time Series

Author : Kamil Feridun Turkman
Publisher : Springer
Page : 255 pages
File Size : 22,3 MB
Release : 2014-09-29
Category : Mathematics
ISBN : 3319070282

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This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.

Modeling Financial Time Series with S-PLUS

Author : Eric Zivot
Publisher : Springer Science & Business Media
Page : 632 pages
File Size : 35,52 MB
Release : 2013-11-11
Category : Business & Economics
ISBN : 0387217630

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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.

Essays in Nonlinear Time Series Econometrics

Author : Niels Haldrup
Publisher : OUP Oxford
Page : 393 pages
File Size : 31,20 MB
Release : 2014-06-26
Category : Business & Economics
ISBN : 0191669547

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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.

Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models

Author : G. Gregoriou
Publisher : Springer
Page : 216 pages
File Size : 23,50 MB
Release : 2010-12-21
Category : Business & Economics
ISBN : 0230295223

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This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.