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Introduction to Modern Time Series Analysis (Springer Texts in Business and Economics) - Tapa blanda

Libro 12 de 190: Springer Texts in Business and Economics

Kirchgässner, Gebhard; Wolters, Jürgen; Hassler, Uwe

 
9783642440298: Introduction to Modern Time Series Analysis (Springer Texts in Business and Economics)
Tapa blanda
ISBN 10: 3642440290 ISBN 13: 9783642440298
Editorial: Springer, 2014

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2014
Idioma
Inglés
ISBN 10 
3642440290
ISBN 13 
9783642440298
Encuadernación
Tapa blanda
Número de edición
2
Número de páginas
332
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