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Recent Advances in Estimating Nonlinear Models - With Applications in Economics and Finance (Hardcover, 2014 ed.)
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Recent Advances in Estimating Nonlinear Models - With Applications in Economics and Finance (Hardcover, 2014 ed.)
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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.
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