Econometrics, Statistics and Empirical Economics

S411 Advanced Time Series Analysis

Lecturer PD Dr. Thomas Dimpfl
Dr. Jantje Sönksen
Profiles First year Master
Prerequisites Bachelor level exposure to Econometrics/Time Series Analysis
Language English
Time and Place Monday 08:10-09:50, HS23 (Kupferbau)
Tuesday 10:10-11:50, HS24 (Kupferbau)
Practical class

Group 1: Monday 10-12, PC-lab

Group 2: Monday 12-14, PC-lab

Exam written exam and assignments
Credit Points 9 ECTS
Start of the lecture 14-10-2019


Hamilton J.: Time Series Analysis, Princeton University Press, 1994


Rigorous treatment of state-of-the art univariate and multivariate time series methods used in economics and finance. Thorough treatment of autoregressive moving average (ARMA) models. Forecasting. Regression analysis with stationary time series. Non-stationary processes. Structural Vector-Autoregressive Models and Cointegration. Equilibrium Correction models. Johansen methodology. Applications of time series methods in macroeconomics and finance. Modeling conditional heteroskedasticity in financial time series. Newer developments. Applications use Matlab in practical class in PC lab.

Practical class

Detailed information on the practical class will be give in the first lecture. There will be no practical class in the first week of the winter term.