Download or read book Nonlinear Economic Time Series as a Testbed for Dynamic Macro Models Including Finance written by Michael Wood and published by . This book was released on 2019 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is consequent upon an earlier paper of mine (Non linear economic time series as a test bed for dynamic macro models) which was an exercise in using nonlinear time series analysis (NLTS) to assess the fit of a dynamic nonlinear macro economic process, the Goodwin model, against “realworld” nonlinear time series.This paper extends that approach to address models which include Finance and Debt as variables. Notably the work of Professor S Keen, This, Finance and Debt, is something notably missing from Goodwin's models.

Download or read book Non Linear Economic Time Series as a Testbed for Dynamic Macro Models written by Michael Wood and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a short exercise in using nonlinear time series analysis (NLTS) to assess the fit of a dynamic nonlinear macro economic process, the Goodwin model, against “realworld” nonlinear time series.The methodology follows the approach developed by Huffaker (2015 and variously) 1 After simulating the Goodwin model and generating plausible time series and an attractor a topologically equivalent attractor is extracted from a single dimension (unemployment) from the Goodwin model.Real US unemployment data is then subjected to SSA analysis to extract a signal from any background “noise” and this signal is then subject to time delay embedding. The attractor resulting from the SSA/Takens process to US unemployment data is topologically equivalent to the attractor from the Goodwin / Predator Prey phase portrait. This primae facie, suggests that the (assumed “black box”) nonlinear economic process which generated these statistics could well have had Goodwin characteristics. The solution is both a limit cycle but also the amplitude (ratio of profitability and unemployment) suddenly increases. This probably reflects that the time series covers the “great moderation” and the subsequent 07/08 crash. This is also a characteristic of more complex nonlinear models like Keen (1997) and suggests that a similar exercise with Keens model and private debt statistics would be interesting.

Download or read book Nonlinear Time Series Analysis of Economic and Financial Data written by Philip Rothman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonlinear Modeling of Economic and Financial Time Series written by Fredj Jawadi and published by Emerald Group Publishing. This book was released on 2010-12-17 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents researches in linear and nonlinear modelling of economic and financial time-series. This book provides a comprehensive understanding of financial and economic dynamics in various aspects using modern financial econometric methods. It also presents and discusses research findings and their implications.

Download or read book Modelling Nonlinear Economic Time Series written by Timo Teräsvirta and published by OUP Oxford. This book was released on 2010-12-16 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Essays in Nonlinear Time Series Econometrics written by Niels Haldrup and published by OUP Oxford. This book was released on 2014-06-26 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonlinear Econometric Modeling in Time Series written by William A. Barnett and published by Cambridge University Press. This book was released on 2000-05-22 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents some of the more recent developments in nonlinear time series, including Bayesian analysis and cointegration tests.

Download or read book Recent Advances in Estimating Nonlinear Models written by Jun Ma and published by Springer. This book was released on 2017-04-30 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonlinear Economic Models written by John Creedy and published by Edward Elgar Publishing. This book was released on 1997 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book A Nonlinear Time Series Workshop written by Douglas M. Patterson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complex dynamic behavior exhibited by many nonlinear systems - chaos, episodic volatility bursts, stochastic regimes switching - has attracted a good deal of attention in recent years. A Nonlinear Time Series Workshop provides the reader with both the statistical background and the software tools necessary for detecting nonlinear behavior in time series data. The most useful existing detection techniques are described, including Engle's LaGrange Multiplier test for conditional hetero-skedasticity and tests based on the correlation dimension and on the estimated bispectrum. These techniques are illustrated using actual data from fields such as economics, finance, engineering, and geophysics.

Download or read book Analysis of Economic Time Series written by Marc Nerlove and published by Academic Press. This book was released on 2014-05-10 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of Economic Time Series: A Synthesis integrates several topics in economic time-series analysis, including the formulation and estimation of distributed-lag models of dynamic economic behavior; the application of spectral analysis in the study of the behavior of economic time series; and unobserved-components models for economic time series and the closely related problem of seasonal adjustment. Comprised of 14 chapters, this volume begins with a historical background on the use of unobserved components in the analysis of economic time series, followed by an Introduction to the theory of stationary time series. Subsequent chapters focus on the spectral representation and its estimation; formulation of distributed-lag models; elements of the theory of prediction and extraction; and formulation of unobserved-components models and canonical forms. Seasonal adjustment techniques and multivariate mixed moving-average autoregressive time-series models are also considered. Finally, a time-series model of the U.S. cattle industry is presented. This monograph will be of value to mathematicians, economists, and those interested in economic theory, econometrics, and mathematical economics.

Download or read book Time Series Models written by D.R. Cox and published by CRC Press. This book was released on 2020-11-26 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds. The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book. The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader.

Download or read book Time Series Analysis and Macroeconometric Modelling written by Kenneth Frank Wallis and published by Edward Elgar Publishing. This book was released on 1995 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of 28 essays by Wallis (econometrics, U. of Warwick, UK), published from 1966 to 1991, on the statistical analysis of economic time series, large-scale macroeconometric modeling, and the interface between them. The articles are organized in four parts: time-series econometrics; modeling seasonality; forecasting in theory and practice; and macroeconometric modeling. The introduction by Wallis provides the background to the papers and comments on subsequent developments. Indexed by name only. Distributed by Ashgate. Annotation copyright by Book News, Inc., Portland, OR

Download or read book Modelling Nonlinear Economic Time Series written by Timo Teräsvirta and published by . This book was released on 2010 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multivariate Modelling of Non Stationary Economic Time Series written by John Hunter and published by Springer. This book was released on 2017-05-08 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.

Download or read book Applications of Non linear Time Series Models on Finance and Macroeconomics written by Jinki Kim and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonlinear Time Series Models with Applications in Macroeconomics and Finance written by Songlin Zeng and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The following three chapters investigate: 1) whether Southeast Asian real exchange rates are nonlinear mean reverting, 2) bayesian inference on nonlinear time series model with applications in real exchange rate, and 3)cyclicality and bounce-back effect in stock market. Since the late nineties, both theoretical and empirical analyses devoted to the real exchange rate suggest that their dynamics might be well approximated by nonlinear models. This paper examines this possibility for post-1970 monthly ASEAN-5 data, extending the existing research in two directions. First, we use recently developed unit root tests which allow for more flexible nonlinear stationary models under the alternative than the commonly used Self-Exciting Threshold or Exponential Smooth Transition AutoRegressions. Second, while different nonlinear models survive the mis-specification tests, a Monte Carlo experiment from generalized impulse response functions is used to compare their relative relevance. Our results support the nonlinear mean-reverting hypothesis, and hence the Purchasing Power Parity, in half the cases and point to the Multiple Regime-Logistic Smooth Transition and the Self-Exciting Threshold AutoRegressive models as the most likely data generating processes of these real exchange rates.Various nonlinear threshold models are employed to mimic the real exchange rate dynamics. A natural question arises: Which model does the best job of modeling the real exchange rate process? It is difficult and not straightforward to formally compare the nonlinear models within classic approach. In the second chapter, we propose to use Bayesian approach to address this issue. The second part of my dissertation actually uses a Bayesian method to estimate some nonlinear time series models, the ACR model, SETAR model, and MAR model. We propose a full Bayesian inference approach and particular attention is paid to the parameters of the threshold variables. We discuss the choice of the prior distributions and propose a Markov-chain Monte Carlo algorithm for estimating both the parameters and the latent variables. A simulation study and the application to real exchange rate data illustrate the analysis. Our empirical results of the second chapter show that i) Bayesian estimations closely match those of the Maximum likelihood for French real exchange rate vis-a-vis Deutsche Mark; ii)the speed of real exchange rate's adjustment to equilibrium level is overestimated if heterogeneous variances in two regimes is not taken into account; iii) ACR model is preferred to other nonlinear threshold models, SETAR and MAR; iv) within ACR class models, the suitable transition function form is selected based on Bayes factor.This paper proposes an empirical study of the shape of recoveries in financial markets from a bounce-back augmented Markov Switching model. It relies on models first applied by Kim, Morley et Piger [2005] to the business cycle analysis. These models are estimated for monthly stock market returns data of five developed countries for the post-1970 period. Focusing on a potential bounce-back effect in financial markets, its presence and shape are formally tested. Our results show that i) the bounce-back effect is statistically significant and large in all countries, but Germany where evidence is less clear-cut and ii) the negative permanent impact of bear markets on the stock price index is notably reduced when the rebound is explicitly taken into account.