Prediction of Extreme Price Occurrences in the German Day-Ahead Electricity Market

28 Pages Posted: 21 Dec 2016

See all articles by Lars Hagfors

Lars Hagfors

Norwegian University of Science and Technology (NTNU)

Hilde Kamperud

Norwegian University of Science and Technology (NTNU)

Florentina Paraschiv

Norwegian University of Science and Technology, Faculty of Economics and Management, NTNU Business School; University of St. Gallen, Institute for Operations Research and Computational Finance

Marcel Prokopczuk

Leibniz Universität Hannover - Faculty of Economics and Management; University of Reading - ICMA Centre

Alma Sator

Norwegian University of Science and Technology (NTNU)

Sjur Westgaard

Norwegian University of Science and Technology (NTNU) - Department of Industrial Economics and Technology

Date Written: July 20, 2016

Abstract

Understanding the mechanisms that drive extreme negative and positive prices in day-ahead electricity prices is crucial for managing risk and market design. In this paper, we consider the problem of understanding how fundamental drivers impact the probability of extreme price occurrences in the German day-ahead electricity market. We develop models using fundamental variables to predict the probability of extreme prices. The dynamics of negative prices and positive price spikes differ greatly. Positive spikes are related to high demand, low supply, and high prices the previous days, and mainly occur during the morning and afternoon peak hours. Negative prices occur mainly during the night, and are closely related to low demand combined with high wind production levels. Furthermore, we do a closer analysis of how renewable energy sources, hereby photovoltaic and wind power, impact the probability of negative prices and positive spikes. The models confirm that extremely high and negative prices have different drivers, and that wind power is particularly important in relation to negative price occurrences. The models capture the main drivers of both positive and negative extreme price occurrences, and perform well with respect to accurately forecasting the probability with high levels of confidence. Our results suggests that probability models are well suited to aid in risk management for market participants in day-ahead electricity markets.

Keywords: EnergyMarkets, Fundamental Analysis, Spikes, EPEX

Suggested Citation

Hagfors, Lars and Kamperud, Hilde and Paraschiv, Florentina and Prokopczuk, Marcel and Sator, Alma and Westgaard, Sjur, Prediction of Extreme Price Occurrences in the German Day-Ahead Electricity Market (July 20, 2016). Quantitative Finance, Vol. 16(12), 2016, University of St.Gallen, School of Finance Research Paper No. 2017/2, Available at SSRN: https://ssrn.com/abstract=2887989

Lars Hagfors

Norwegian University of Science and Technology (NTNU) ( email )

Høgskoleringen
Trondheim NO-7491, 7491
Norway

Hilde Kamperud

Norwegian University of Science and Technology (NTNU) ( email )

Høgskoleringen
Trondheim NO-7491, 7491
Norway

Florentina Paraschiv

Norwegian University of Science and Technology, Faculty of Economics and Management, NTNU Business School ( email )

Klæbuveien 72
Trondheim, NO-7030
Norway

University of St. Gallen, Institute for Operations Research and Computational Finance ( email )

Bodanstrasse 6
St. Gallen, 9000
Switzerland

Marcel Prokopczuk (Contact Author)

Leibniz Universität Hannover - Faculty of Economics and Management ( email )

Koenigsworther Platz 1
Hannover, 30167
Germany

University of Reading - ICMA Centre ( email )

Whiteknights Park
P.O. Box 242
Reading RG6 6BA
United Kingdom

Alma Sator

Norwegian University of Science and Technology (NTNU) ( email )

Høgskoleringen
Trondheim NO-7491, 7491
Norway

Sjur Westgaard

Norwegian University of Science and Technology (NTNU) - Department of Industrial Economics and Technology ( email )

NO-7491 Trondheim
Norway

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