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Humboldt-Universität zu Berlin -

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:

  1. Descriptive Methods
    • Sample Moments
    • Classical Components Models 
    • Trend Determination
    • Seasonal Adjustment
  2. Models of Time Series
    • Stochastic Processes and Stationarity
    • AR, MA and ARMA Processes
    • The Partial Autocorrelation Function
  3. Estimation, Specification, Validation and Forecasting of ARMA Models
  4. Models for Nonstationary Time Series and Unit Root Tests
    • Trend Stationarity vs. Unit Root
    • ARIMA and Seasonal ARIMA Models
    • Unit Root Tests
  5. GARCH Models for Clustered Volatility
  6. 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)