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Module (6 Credits)

Econometrics of Electricity Markets

Name in diploma supplement
Econometrics of Electricity Markets
Responsible
Admission criteria
See exam regulations.
Workload
180 hours of student workload, in detail:
  • Attendance: 60 hours
  • Preparation, follow up: 80 hours
  • Exam preparation: 40 hours
Duration
The module takes 1 semester(s).
Qualification Targets

The students

  • have an advanced understanding of electricity markets
  • understand regression based modeling methods for electricity prices
  • can apply estimation and forecasting algorithms to real data using the statistical Software R
  • able to interpret and to visualize the results
Module Exam

Equally weighted average of a group R-project and a presentation (usually about 20 minutes).

Usage in different degree programs
  • BWL EaFWahlpflichtbereich1st-3rd Sem, Elective
  • ECMXWahlpflichtbereichME6 Applied Econometrics1st-3rd Sem, Elective
  • MuUWahlpflichtbereich IWahlpflichtbereich I A.: Methodologie und allgemeine Theorien zur Untersuchung von Märkten und Unternehmen1st-2nd Sem, Elective
  • VWLWahlpflichtbereich I1st-3rd Sem, Elective
Elements
Name in diploma supplement
Econometrics of Electricity Markets
Organisational Unit
Lecturers
SPW
2
Language
English
Cycle
irregular
Participants at most
24
Preliminary knowledge
  • 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.

Contents
  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
Literature

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.

Teaching concept

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

Participants
Lecture: Econometrics of Electricity Markets (WIWI‑C1073)
Name in diploma supplement
Econometrics of Electricity Markets
Organisational Unit
Lecturers
SPW
2
Language
English
Cycle
irregular
Participants at most
24
Preliminary knowledge

See Lecture

Contents

See Lecture

Literature

See Lecture

Teaching concept

Tutorials. The students apply the learned methods in a own real data project.

Participants
Exercise: Econometrics of Electricity Markets (WIWI‑C1126)
Module: Econometrics of Electricity Markets (WIWI‑M0788)