empfohlenes Vorwissen

• Good knowledge of linear models.
• R knowledge (esp. functions like lm)
• Understanding of AR(p) processes is very helpful

Abstract

The objective of the lecture is to provide a basic understanding of electricity markets and regression based modeling methods for electricity prices. The aim of this course is to apply estimation and forecasting algorithms to real data using the statistical Software R, to interpret and to visualize the results.

Lehrinhalte

1. Introduction to electricity markets
2. Overview of different model approaches
3. Regression based modeling methods for electricity prices
4. Forcasting and evaluation techniques
5. Advanced estimation and modeling approaches

Literaturangaben

The relevant material will be given during the course.

Suggested reading:

Weron, Rafał. "Electricity price forecasting: A review of the state-of-the-art with a look into the future." International Journal of Forecasting 30.4 (2014): 1030-1081.

didaktisches Konzept

Lecture. The studied modeling an forecasting methods are applied on real data using the statistical sofware R.

Hörerschaft

• BWL-EaF-Ma-2015 > Wahlpflichtbereich > (1.-3. Fachsemester, Wahlpflicht) Modul "Econometrics of Electricity Markets"
• ECMX-Ma-2019 > Wahlpflichtbereich > ME6 Applied Econometrics > (1.-3. Fachsemester, Wahlpflicht) Modul "Econometrics of Electricity Markets"
• MuU-Ma-2013 > Wahlpflichtbereich I > Wahlpflichtbereich I A.: Methodologie und allgemeine Theorien zur Untersuchung von Märkten und Unternehmen > (1.-2. Fachsemester, Wahlpflicht) Modul "Econometrics of Electricity Markets"
• VWL-Ma-2009-V2013 > Wahlpflichtbereich I > (1.-3. Fachsemester, Wahlpflicht) Modul "Econometrics of Electricity Markets"