书目名称 | Introduction to Modern Time Series Analysis |
编辑 | Gebhard Kirchgässner,Jürgen Wolters,Uwe Hassler |
视频video | |
概述 | 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 und |
丛书名称 | Springer Texts in Business and Economics |
图书封面 |  |
描述 | .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.. . |
出版日期 | Textbook 2013Latest edition |
关键词 | Cointegration; Granger Causality; Time Series Analysis; Unit Roots; Vector Autogressive Models; Volatilit |
版次 | 2 |
doi | https://doi.org/10.1007/978-3-642-33436-8 |
isbn_softcover | 978-3-642-44029-8 |
isbn_ebook | 978-3-642-33436-8Series ISSN 2192-4333 Series E-ISSN 2192-4341 |
issn_series | 2192-4333 |
copyright | Springer-Verlag GmbH Germany, part of Springer Nature 2013 |