Ebook: Introduction to Modern Time Series Analysis
- Tags: Econometrics, Statistics for Business/Economics/Mathematical Finance/Insurance
- Year: 2007
- Publisher: Springer Berlin Heidelberg
- Language: English
- pdf
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It bridges the gap between methods and realistic applications. This book contains the most important approaches to analyze time series which may be stationary or nonstationary. It starts with modeling and forecasting univariate time series and then presents Granger causality tests and vector autoregressive models for multiple stationary time series.
For real applied work the modeling of nonstationary uni- or multivariate time series is most important. Therefore, unit root and cointegration analysis as well as vector error correction models play a central part. Modelling volatilities of financial time series with autoregressive conditional heteroskedastic models is also treated.
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It bridges the gap between methods and realistic applications. This book contains the most important approaches to analyze time series which may be stationary or nonstationary. It starts with modeling and forecasting univariate time series and then presents Granger causality tests and vector autoregressive models for multiple stationary time series.
For real applied work the modeling of nonstationary uni- or multivariate time series is most important. Therefore, unit root and cointegration analysis as well as vector error correction models play a central part. Modelling volatilities of financial time series with autoregressive conditional heteroskedastic models is also treated.
Content:
Front Matter....Pages I-IX
Introduction and Basics....Pages 1-25
Univariate Stationary Processes....Pages 27-91
Granger Causality....Pages 93-123
Vector Autoregressive Processes....Pages 125-151
Nonstationary Processes....Pages 153-198
Cointegration....Pages 199-239
Autoregressive Conditional Heteroskedasticity....Pages 241-265
Back Matter....Pages 267-274
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It bridges the gap between methods and realistic applications. This book contains the most important approaches to analyze time series which may be stationary or nonstationary. It starts with modeling and forecasting univariate time series and then presents Granger causality tests and vector autoregressive models for multiple stationary time series.
For real applied work the modeling of nonstationary uni- or multivariate time series is most important. Therefore, unit root and cointegration analysis as well as vector error correction models play a central part. Modelling volatilities of financial time series with autoregressive conditional heteroskedastic models is also treated.
Content:
Front Matter....Pages I-IX
Introduction and Basics....Pages 1-25
Univariate Stationary Processes....Pages 27-91
Granger Causality....Pages 93-123
Vector Autoregressive Processes....Pages 125-151
Nonstationary Processes....Pages 153-198
Cointegration....Pages 199-239
Autoregressive Conditional Heteroskedasticity....Pages 241-265
Back Matter....Pages 267-274
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