Recent Advances in Estimating Nonlinear Models: With Applications in Economics and Finance - Softcover

Softcover

ISBN 10: 1493952595 ISBN 13: 9781493952595

Verlag: Springer, 2017

Inhaltsangabe

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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Über die Autorin bzw. den Autor

Jun Ma

Professor Ma’s primary research interests are Macroeconomics, International Finance, Asset Pricing, and Time Series Econometrics. He has published in journals such as Journal of International Economics, Journal of Money, Credit, and Banking, Journal of Economic Dynamics and Control, Studies in Nonlinear Dynamics and Econometrics, Journal of Banking and Finance, and European Journal of Finance. He was a visiting scholar at Norges Bank (the central bank of Norway) and has been invited to present his research work at central banks and universities, including Norges Bank, Federal Reserve Bank of St. Louis, University of Washington, Virginia Tech, University of Houston, University of Kansas, and University of Nebraska at Omaha.

Department of Economic, Finance, and Legal Studies University of Alabama Tuscaloosa, AL 35487 USA jma@cba.ua.edu Mark E. Wohar Department of Economics University of Nebraska-Omaha RH 512K Omaha, NE 68182 mwohar@mail.unomaha.edu

Mark E. Wohar

Professor Wohar's areas of research include, Domestic and International Macroeconomics, International Finance, Monetary Theory and Financial Economics, Financial Institutions, and Applied Time Series Econometrics. He has published over 120 refereed journal articles. Some of his more noteworthy publications have appeared in journals such as the American Economic Review, Economic Journal, Journal of Finance, Journal of International Economics, Economic Inquiry, Journal of Applied Econometrics, Journal of Forecasting, International Journal of Forecasting, Review of Economics and Statistics, and Journal of Money, Credit and Banking. His research has been cited by more than 950 papers of other authors. He has received many awards for research excellence. Wohar has presented his research at a number of Universities (both in the US and abroad), including Kansas State University, Michigan State University, University ofNew Orleans, University of Notre Dame, Ohio State University, University of Washington, University of California-San Diego, Southern Methodist University, University of Wisconsin-Madison, University of Syracuse, University of Illinois, University of Essex, Cambridge University, University of Warwick, University of Nottingham, University of Durham, Cass Business School-London, University of Kansas, University of California at Davis, among others.

Von der hinteren Coverseite

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2017
• ISBN 10: 1493952595
• ISBN 13: 9781493952595
• Einband: Tapa blanda
• Sprache: Englisch
• Anzahl der Seiten: 316
• Herausgeber: Ma Jun, Wohar Mark
• Kontakt zum Hersteller: Nicht verfügbar