Preliminary knowledge

Basics in R or python, basics in data science or statistics.

Abstract

In the first third of the Module the students study the competition design, the forecast evaluation methods, benchmark methods and forecasting principles in general in a lecture. The competition task and the corresponding data sets will be released immediately. In the second part the student construct their own forecasting model for the competition and submit their forecasts. Shortly afterwards the results will be released. In the third part of the students write a report on the prediction methods and present their finding.

Contents

1. Introduction on forecasting competitions
2. Competition design and reporting of forecasts
3. Evaluation metrics
4. Benchmark methods
5. Options for improving forecasts

Literature

• Hong, T., Pinson, P., Fan, S., Zareipour, H., Troccoli, A., & Hyndman, R. J. (2016). Probabilistic energy forecasting: Global energy forecasting competition 2014 and beyond.  International Journal of Forecasting, 32(3), 896-913.
• Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2020). The M4 Competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting, 36(1), 54-74.
• Further Literature will be mentioned during the lecture.

Teaching concept

Classic lectures + Learning by doing

Die Veranstaltung entspricht einem Vorlesungsanteil von 2 SWS und einem Seminaranteil von 2 SWS.

Participants

• BWL-EaF-Ma-2015 > Wahlpflichtbereich > (1st-3rd Semester, Elective) Modul "Energy Forecasting Competition"
• ECMX-Ma-2019 > Wahlpflichtbereich > ME5 Economics > (1st-3rd Semester, Elective) Modul "Energy Forecasting Competition"
• GOEMIK-Ma-2016 > Wahlpflichtbereich > Bereich Betriebswirtschaftslehre > (1st-3rd Semester, Elective) Modul "Energy Forecasting Competition"
• MuU-Ma-2013 > Wahlpflichtbereich II > Wahlpflichtbereich II B.: Märkte und Unternehmen aus Marktperspektive > (1st-3rd Semester, Elective) Modul "Energy Forecasting Competition"
• VWL-Ma-2009-V2013 > Wahlpflichtbereich II > (1st-3rd Semester, Elective) Modul "Energy Forecasting Competition"