Recent Advances in Estimating Nonlinear Models
With Applications in Economics and Finance
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Beschreibung
This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. The focus is on such topics as state-space model and the identification issue, use of Markov Switching Models and Smooth Transition Models to analyze economic series, and how best to distinguish between competing nonlinear models. Most economic theory suggests that the economic relationships among economic variables in the real world are fairly complex and nonlinear. Nonlinear models are necessary to capture these important channels through which economic variables can influence each other and various policies can affect economic activities. This volume features cutting-edge research from leading academics in economics, finance, and business management. The principles and techniques used here 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.
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.
First comprehensive text to feature the most advanced methodologies and nonlinear modeling techniques for economics and finance Ideal supplement for graduate students and researchers working with time series analysis Includes contributions from well-known academics and nonlinear modeling experts
Autor*in
Jun Ma
Themen in »Recent Advances in Estimating Nonlinear Models«
Markov-switching models Nonlinear models Smooth transition Threshold models Time series analysis