Time Series Analysis - Summer Term 2016
Further Course Information and Material will ONLY be available on Moodle.
The Course-Key for Subscription will be published in the first lecture.
Lecturer: Prof. Dr. Bernd Droge
Lecture/exercise:
Monday, 14-16, SPA1, 22 (some exercises will take place in the PC-lab SPA1, 025)
Tuesday, 10-12, SPA1, 22
Contents:
-
Descriptive Methods
- Sample Moments
- Classical Components Models
- Trend Determination
- Seasonal Adjustment
-
Models of Time Series
- Stochastic Processes and Stationarity
- AR, MA and ARMA Processes
- The Partial Autocorrelation Function
- Estimation, Specification, Validation and Forecasting of ARMA Models
-
Models for Nonstationary Time Series and Unit Root Tests
- Trend Stationarity vs. Unit Root
- ARIMA and Seasonal ARIMA Models
- Unit Root Tests
- GARCH Models for Clustered Volatility
-
Multivariate Extensions
- VAR Processes
- Causality and Impulse Response Analysis
- Cointegrated Processes
References:
Hamilton, D.J. (1994). Time Series Analysis, Princeton University Press.
Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis, Springer Verlag, Heidelberg
Exam: written exam (90 min)