Syllabus:
- Overview
- Fundamentals and Properties of Stochastic Processes
- Univariate ARIMA-Processes
- Estimation and Forecasting of ARIMA-Models
- Univariate GARCH-Models + Extensions
- Selected aspects: Long Memory und Fractional Differencing, Threshold-Models
Intended audience: Advanced bachelor and master students of statistics, mathematics, computer science (Informatik), economics and business administration.
Prerequisites: Solid mathematical foundations (analysis and linear algebra), basic knowledge in econometrics (econometrics 1) or statistics (linear models).
Record of Achievement:
This course grants 6 ECTS and can be credited for Zeitreihen (WP7, BA Statistik, PO 2010), Time Series (WP 18, MA Statistics and Data Science, PO 2021), Zeitreihen (P 6.0.27, MA Statistik, PO 2010), Zeitreihen (P 8.0.32, MA Biostatistik, PO 2010) and Zeitreihen (P 7.0.5, MA WiSo Statistik, PO 2010)
Students of other courses of study (mathematics, computer science, etc.) or
external students (e.g. TUM) may take part in the final exam and
receive a grade as well. However, you have to clarify the crediting
modalities on
your own with your Prüfungsamt beforehand.
Key: utsa24
- Trainer/in: Dennis Mao