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Prediction of extreme price occurrences in the German day-ahead electricity market

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  1. Saji Thazhungal Govindan Nair, 2021. "On extreme value theory in the presence of technical trend: pre and post Covid-19 analysis of cryptocurrency markets," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 14(4), pages 533-561, December.
  2. Guo, Bowei & Newbery, David, 2021. "The cost of uncoupling GB interconnectors," Energy Policy, Elsevier, vol. 158(C).
  3. Hinderks, W.J. & Wagner, A., 2019. "Pricing German Energiewende products: Intraday cap/floor futures," Energy Economics, Elsevier, vol. 81(C), pages 287-296.
  4. Maciejowska, Katarzyna, 2020. "Assessing the impact of renewable energy sources on the electricity price level and variability – A quantile regression approach," Energy Economics, Elsevier, vol. 85(C).
  5. Nikkinen, Jussi & Rothovius, Timo, 2019. "Market specific seasonal trading behavior in NASDAQ OMX electricity options," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 16-29.
  6. Loizidis, Stylianos & Kyprianou, Andreas & Georghiou, George E., 2024. "Electricity market price forecasting using ELM and Bootstrap analysis: A case study of the German and Finnish Day-Ahead markets," Applied Energy, Elsevier, vol. 363(C).
  7. Tselika, Kyriaki, 2022. "The impact of variable renewables on the distribution of hourly electricity prices and their variability: A panel approach," Energy Economics, Elsevier, vol. 113(C).
  8. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
  9. Mayer, Klaus & Trück, Stefan, 2018. "Electricity markets around the world," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 77-100.
  10. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
  11. Bartosz Uniejewski & Rafał Weron, 2018. "Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models," Energies, MDPI, vol. 11(8), pages 1-26, August.
  12. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits," Energies, MDPI, vol. 12(4), pages 1-15, February.
  13. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
  14. Li, Wei & Paraschiv, Florentina, 2022. "Modelling the evolution of wind and solar power infeed forecasts," Journal of Commodity Markets, Elsevier, vol. 25(C).
  15. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
  16. Ritmeester, Tim & Meyer-Ortmanns, Hildegard, 2021. "Minority games played by arbitrageurs on the energy market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
  17. Liu, Luyao & Bai, Feifei & Su, Chenyu & Ma, Cuiping & Yan, Ruifeng & Li, Hailong & Sun, Qie & Wennersten, Ronald, 2022. "Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model," Energy, Elsevier, vol. 247(C).
  18. Peña, Juan Ignacio & Rodríguez, Rosa & Mayoral, Silvia, 2020. "Tail risk of electricity futures," Energy Economics, Elsevier, vol. 91(C).
  19. Florentina Paraschiv & Dima Mohamad, 2020. "The Nuclear Power Dilemma—Between Perception and Reality," Energies, MDPI, vol. 13(22), pages 1-19, November.
  20. Gaudard, Ludovic & Avanzi, Francesco & De Michele, Carlo, 2018. "Seasonal aspects of the energy-water nexus: The case of a run-of-the-river hydropower plant," Applied Energy, Elsevier, vol. 210(C), pages 604-612.
  21. Huisman, Ronald & Stet, Cristian, 2022. "The dependence of quantile power prices on supply from renewables," Energy Economics, Elsevier, vol. 105(C).
  22. Attila Bai & Péter Balogh & Adrián Nagy & Zoltán Csedő & Botond Sinóros-Szabó & Gábor Pintér & Sanjeev Kumar Prajapati & Amit Singh & Zoltán Gabnai, 2023. "Economic Evaluation of a 1 MW el Capacity Power-to-Biomethane System," Energies, MDPI, vol. 16(24), pages 1-27, December.
  23. Emma Viviani & Luca Di Persio & Matthias Ehrhardt, 2021. "Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case," Energies, MDPI, vol. 14(2), pages 1-33, January.
  24. Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
  25. Jens Baetens & Jeroen D. M. De Kooning & Greet Van Eetvelde & Lieven Vandevelde, 2020. "A Two-Stage Stochastic Optimisation Methodology for the Operation of a Chlor-Alkali Electrolyser under Variable DAM and FCR Market Prices," Energies, MDPI, vol. 13(21), pages 1-19, October.
  26. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
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