Introduction to Modern Time Series Analysis
Authors: Kirchgässner, Gebhard, Wolters, Jürgen, Hassler, Uwe
Free Preview- Presents modern methods of time series econometrics and their applications to macroeconomics and finance
- With numerous examples and analyses based on real economic data
- Helps to acquire a rigorous understanding of the methods and to develop empirical skills
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- About this Textbook
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This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.
- Table of contents (8 chapters)
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Introduction and Basics
Pages 1-25
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Univariate Stationary Processes
Pages 27-93
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Granger Causality
Pages 95-125
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Vector Autoregressive Processes
Pages 127-154
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Nonstationary Processes
Pages 155-203
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Table of contents (8 chapters)
- Download Preface 1 PDF (146 KB)
- Download Sample pages 1 PDF (775.9 KB)
- Download Table of contents PDF (407.5 KB)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Introduction to Modern Time Series Analysis
- Authors
-
- Gebhard Kirchgässner
- Jürgen Wolters
- Uwe Hassler
- Series Title
- Springer Texts in Business and Economics
- Copyright
- 2013
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag GmbH Germany, part of Springer Nature
- eBook ISBN
- 978-3-642-33436-8
- DOI
- 10.1007/978-3-642-33436-8
- Hardcover ISBN
- 978-3-642-33435-1
- Softcover ISBN
- 978-3-642-44029-8
- Series ISSN
- 2192-4333
- Edition Number
- 2
- Number of Pages
- XII, 320
- Topics
