Christopher Kath, Florian Ziel
arXiv 21 Nov 2018 · Finance — Statistical Finance · publishedEnergy Economics (2018) · 76 citations (OpenAlex)
arXiv:1811.08604 · PDF · DOI · OpenAlex · Extracted main text
We propose a multivariate elastic net regression forecast model for German quarter-hourly electricity spot markets. While the literature is diverse on day-ahead prediction approaches, both the intraday continuous and intraday call-auction prices have not been studied intensively with a clear focus on predictive power. Besides electricity price forecasting, we check for the impact of early day-ahead (DA) EXAA prices on intraday forecasts. Another novelty of this paper is the complementary discussion of economic benefits. A precise estimation is worthless if it cannot be utilized. We elaborate possible trading decisions based upon our forecasting scheme and analyze their monetary effects. We find that even simple electricity trading strategies can lead to substantial economic impact if combined with a decent forecasting technique.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Uniejewski, B., Weron, R., & Ziel, F (2018) Variance stabilizing transformations for electricity spot price forecasting self | 0.644 | 4 | 1 | 100% |
| 2 | Kiesel, R., & Paraschiv, F (2017) Econometric analysis of 15-minute intraday electricity prices | 0.644 | 2 | 2 | 100% |
| 3 | Märkle-Hu, J., Feuerriegel, S., & Neumann, D (2018) Contract durations in the electricity market: Causal impact of 15min trading on the epex spot market | 0.644 | 2 | 2 | 100% |
| 4 | Ziel, F., Steinert, R., & Husmann, S (2015) Forecasting day ahead electricity spot prices: The impact of the exaa to other european electricity markets self | 0.644 | 2 | 2 | 100% |
| 5 | Calvo-Silvosa, A., Antelo, S. I., Soares, I. et al (2017) Energy planning and modern portfolio theory: A review | 0.585 | 3 | 1 | 100% |
| 6 | Ziel, F (2017) Modeling the impact of wind and solar power forecasting errors on intraday electricity prices self | 0.511 | 2 | 1 | 100% |
| 7 | Ad, R., Gruet, P., & Pham, H (2016) An optimal trading problem in intraday electricity markets | 0.405 | 1 | 1 | 100% |
| 8 | Bordignon, S., Bunn, D. W., Lisi, F., & Nan, F (2013) Combining day-ahead forecasts for british electricity prices | 0.405 | 1 | 1 | 100% |
| 9 | Buuren, S., & Groothuis-Oudshoorn, K (2011) mice: Multivariate imputation by chained equations in R | 0.405 | 1 | 1 | 100% |
| 10 | Diebold, F. X., & Mariano, R. S (1995) Comparing predictive accuracy | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 39 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market | 0.644 | 2 | 2 |
| 2 | Ranking probabilistic forecasting models with different loss functions | 0.405 | 1 | 1 |