Details
| Original language | English |
|---|---|
| Pages (from-to) | 1929-1948 |
| Number of pages | 20 |
| Journal | Quantitative Finance |
| Volume | 16 |
| Issue number | 12 |
| Publication status | Published - 1 Dec 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 suggest that probability models are well suited to aid in risk management for market participants in day-ahead electricity markets.
Keywords
- Energy markets, EPEX, Fundamental analysis, Spikes
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Finance
- Economics, Econometrics and Finance(all)
Sustainable Development Goals
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Quantitative Finance, Vol. 16, No. 12, 01.12.2016, p. 1929-1948.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Prediction of extreme price occurrences in the German day-ahead electricity market
AU - Hagfors, Lars Ivar
AU - Kamperud, Hilde Hørthe
AU - Paraschiv, Florentina
AU - Prokopczuk, Marcel
AU - Sator, Alma
AU - Westgaard, Sjur
PY - 2016/12/1
Y1 - 2016/12/1
N2 - 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 suggest that probability models are well suited to aid in risk management for market participants in day-ahead electricity markets.
AB - 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 suggest that probability models are well suited to aid in risk management for market participants in day-ahead electricity markets.
KW - Energy markets
KW - EPEX
KW - Fundamental analysis
KW - Spikes
UR - http://www.scopus.com/inward/record.url?scp=84987617437&partnerID=8YFLogxK
U2 - 10.1080/14697688.2016.1211794
DO - 10.1080/14697688.2016.1211794
M3 - Article
AN - SCOPUS:84987617437
VL - 16
SP - 1929
EP - 1948
JO - Quantitative Finance
JF - Quantitative Finance
SN - 1469-7688
IS - 12
ER -