Introduction to Modern Time Series Analysis (PDF)
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...
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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. It also covers modeling volatilities of financial time series with autoregressive conditional heteroskedastic models.
- Autoren: Gebhard Kirchgässner , Jürgen Wolters
- 2007, 2007, 274 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3540732918
- ISBN-13: 9783540732914
- Erscheinungsdatum: 17.08.2007
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 2.22 MB
- Ohne Kopierschutz
- Vorlesefunktion
From the reviews:
"This excellent textbook presents an introduction to the time series analysis. It provides a good source of information for graduate and master students in economics and statistics. It is a well-written and easy to read book, illustrated by 56 good examples. Also, many important references are listed at the end of each chapter." (Miroslav M. Ristic, Zentralblatt MATH, Vol. 1148, 2008)
"This book presents to beginners a readable and easily accessible introduction to modern developments in time series econometrics and financial time series with an emphasis on basic concepts and practical applications. The book is a textbook consisting of seven chapters … . the greatest merit of this textbook is that it enables readers to grasp the basic framework of time-series econometrics without relying on extensive reading." (Yuzo Hosoya, Mathematical Reviews, Issue 2009 k)
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