Syllabus
- Introduction to Stochastic Processes
- Autoregressive Moving Average Processes
- Estimation of Vector ARMA Models
- Prediction
- Testing for Causality
- Innovations Accounting
- Structural VAR
Intended audience: Advanced students and PhD students in econometrics, statistics, VWL, BWL, mathematics or computer science.
Prerequisites: Profound knowledge in matrix-algebra and econometrics (econometrics I) or statistics (linear models). Basic knowledge in univariate time series analysis is not demanded but of advantage.
Teaching Style: Online via Zoom and Moodle
Examination: (written) Exam
Record of Achievement: 3 ECTS + 3 ECTS
Time Schedule
The lectures and tutorials take place between 01.06.2021 (first lecture) and 06.07.2021.
Inscription key: MTSA2021SoSe
- Trainer/in: Robert Czudaj
- Trainer/in: Dennis Mao