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Nonlinear Econometric Modeling In Time Series


Nonlinear Econometric Modeling In Time Series
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Nonlinear Time Series Analysis Of Economic And Financial Data


Nonlinear Time Series Analysis Of Economic And Financial Data
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Author : Philip Rothman
language : en
Publisher: Springer Science & Business Media
Release Date : 1999-01-31

Nonlinear Time Series Analysis Of Economic And Financial Data written by Philip Rothman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-01-31 with Business & Economics categories.


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 Econometric Modeling In Time Series


Nonlinear Econometric Modeling In Time Series
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Author : William A. Barnett
language : en
Publisher: Cambridge University Press
Release Date : 2000-05-22

Nonlinear Econometric Modeling In Time Series written by William A. Barnett 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 2000-05-22 with Business & Economics categories.


Nonlinear Econometric Modeling in Time Series presents the more recent literature on nonlinear time series. Specific topics covered with respect to nonlinearity include cointegration tests, risk-related asymmetries, structural breaks and outliers, Bayesian analysis with a threshold, consistency and asymptotic normality, asymptotic inference and error-correction models. With a world-class panel of contributors, this volume addresses topics with major applications for fields such as foreign-exchange markets and interest rate analysis. Eleventh in this series of international symposia, this volume is also part of the European Conference Series in Quantitative Economics and Econometrics (EC)2.



Modelling Nonlinear Economic Time Series


Modelling Nonlinear Economic Time Series
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Author : Timo Teräsvirta
language : en
Publisher:
Release Date : 2010

Modelling Nonlinear Economic Time Series written by Timo Teräsvirta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Econometric models categories.


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


Non Linear Time Series Models In Empirical Finance
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Author : Philip Hans Franses
language : en
Publisher: Cambridge University Press
Release Date : 2000-07-27

Non Linear Time Series Models In Empirical Finance written by Philip Hans Franses 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 2000-07-27 with Business & Economics categories.


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



Nonlinear Time Series


Nonlinear Time Series
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Author : Jianqing Fan
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-11

Nonlinear Time Series written by Jianqing Fan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-11 with Mathematics categories.


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.



Threshold Models In Non Linear Time Series Analysis


Threshold Models In Non Linear Time Series Analysis
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Author : H. Tong
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Threshold Models In Non Linear Time Series Analysis written by H. Tong and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


In the last two years or so, I was most fortunate in being given opportunities of lecturing on a new methodology to a variety of audiences in Britain, China, Finland, France and Spain. Despite my almost Confucian attitude of preferring talking (i.e. a transient record) to writing (i.e. a permanent record), the warm encouragement of friends has led to the ensuing notes. I am also only too conscious of the infancy of the methodology introduced in these notes. However, it is my sincere hope that exposure to a wider audience will accelerate its maturity. Readers are assumed to be familiar with the basic theory of time series analysis. The book by Professor M.B. Priestley (1981) may be used as a general reference. Chapter One is addressed to the general question: "why do we need non-linear time series models?" After describing some significant advantages of linear models, it singles out several major limitations of linearity. Of course, the selection reflects my personal view on the subject, which is only at its very beginning, although there does seem to be a general agreement in the literature that time irr'eversibility and limit cycles are among the most obvious.



Elements Of Nonlinear Time Series Analysis And Forecasting


Elements Of Nonlinear Time Series Analysis And Forecasting
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Author : Jan G. De Gooijer
language : en
Publisher: Springer
Release Date : 2017-04-07

Elements Of Nonlinear Time Series Analysis And Forecasting written by Jan G. De Gooijer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-07 with Mathematics categories.


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.



Nonlinear Time Series Analysis


Nonlinear Time Series Analysis
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Author : Holger Kantz
language : en
Publisher: Cambridge University Press
Release Date : 2004

Nonlinear Time Series Analysis written by Holger Kantz 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 with Mathematics categories.


The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.



Nonlinear Time Series


Nonlinear Time Series
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Author : Randal Douc
language : en
Publisher: CRC Press
Release Date : 2014-01-06

Nonlinear Time Series written by Randal Douc and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-06 with Mathematics categories.


This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.



The Econometric Analysis Of Seasonal Time Series


The Econometric Analysis Of Seasonal Time Series
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Author : Eric Ghysels
language : en
Publisher: Cambridge University Press
Release Date : 2001-06-18

The Econometric Analysis Of Seasonal Time Series written by Eric Ghysels 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 2001-06-18 with Business & Economics categories.


Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.