Nonlinear Time Series Analysis of Economic and Financial Data


Book Description

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.




Smooth Transition Autoregressive Model. A study of production index of production sector in Germany


Book Description

Academic Paper from the year 2017 in the subject Business economics - Miscellaneous, grade: 1.3, University of Wuppertal, language: English, abstract: The main aim of this seminar is to define, examine and present Smooth Transition Autoregressive Model (STAR) which is a model used to analyze nonlinear time-series economic data with regime-switching. In going forward, the overall structure of the seminar is designed to study the nonlinear features of production sector production index of Germany using data from January 1991 to April 2017. The author did first a Chow Test to evidence the existence of a data structural breakpoint. Then a model specification procedure given by Teräsvirta (1994) was followed. The author used, accordingly, three steps to specify the model. First, a linear AR model was developed using the data. Secondly, a linearity test against the STAR model was carried out. Once a test of the null hypothesis of linearity against non-linearity is rejected by the carried out Lagrange Multiplier (LM) test, the delay parameter d was determined. Afterwards, a choice between the LSTAR and the ESTAR model was made using a sequence of tests. Finally, the estimation of the model is done. As the results from the set of tests indicate, the STAR model is found to be appropriate for modeling and analyzing the data.




Recent Advances in Estimating Nonlinear Models


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.







A Companion to Economic Forecasting


Book Description

A Companion to Economic Forecasting provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.




Analysis of Financial Time Series


Book Description

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.




Nonlinear Econometric Modeling in Time Series


Book Description

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




Non-Linear Time Series Models in Empirical Finance


Book Description

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




The Fiscal State-Dependent Effects of Capital Income Tax Cuts


Book Description

Using the post-WWII data of U.S. federal corporate income tax changes, within a Smooth Transition VAR, this paper finds that the output effect of capital income tax cuts is government debt-dependent: it is less expansionary when debt is high than when it is low. To explore the mechanisms that can drive this fiscal state-dependent tax effect, the paper uses a DSGE model with regime-switching fiscal policy and finds that a capital income tax cut is stimulative to the extent that it is unlikely to result in a future fiscal adjustment. As government debt increases to a sufficiently high level, the probability of future fiscal adjustments starts rising, and the expansionary effects of a capital income tax cut can diminish substantially, whether the expected adjustments are through a policy reversal or a consumption tax increase. Also, a capital income tax cut need not always have large revenue feedback effects as suggested in the literature.




Nonlinear Time Series Analysis of Economic and Financial Data


Book Description

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.