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Modeling the UK electricity price distributions using quantile regression

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  1. Derek W. Bunn & Angelica Gianfreda & Stefan Kermer, 2018. "A Trading-Based Evaluation of Density Forecasts in a Real-Time Electricity Market," Energies, MDPI, vol. 11(10), pages 1-13, October.
  2. 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).
  3. Ekaterina Abramova & Derek Bunn, 2021. "Optimal Daily Trading of Battery Operations Using Arbitrage Spreads," Energies, MDPI, vol. 14(16), pages 1-23, August.
  4. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
  5. Gianfreda, Angelica & Scandolo, Giacomo, 2023. "A worldwide analysis of the energy regulatory tasks and activities through the lenses of entropy and unsupervised statistical learning," Energy, Elsevier, vol. 271(C).
  6. 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).
  7. Uribe, Jorge M. & Guillen, Montserrat & Mosquera-López, Stephania, 2018. "Uncovering the nonlinear predictive causality between natural gas and electricity prices," Energy Economics, Elsevier, vol. 74(C), pages 904-916.
  8. Ajanaku, Bolarinwa A. & Collins, Alan R., 2024. "“Comparing merit order effects of wind penetration across wholesale electricity markets”," Renewable Energy, Elsevier, vol. 226(C).
  9. Zheng, Kedi & Chen, Huiyao & Wang, Yi & Chen, Qixin, 2022. "Data-driven financial transmission right scenario generation and speculation," Energy, Elsevier, vol. 238(PC).
  10. Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego F., 2018. "Effect of stopping hydroelectric power generation on the dynamics of electricity prices: An event study approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 456-467.
  11. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
  12. Sergio Cantillo-Luna & Ricardo Moreno-Chuquen & Jesus Lopez-Sotelo & David Celeita, 2023. "An Intra-Day Electricity Price Forecasting Based on a Probabilistic Transformer Neural Network Architecture," Energies, MDPI, vol. 16(19), pages 1-24, September.
  13. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
  14. Sapio, Alessandro, 2019. "Greener, more integrated, and less volatile? A quantile regression analysis of Italian wholesale electricity prices," Energy Policy, Elsevier, vol. 126(C), pages 452-469.
  15. He, Yaoyao & Zheng, Yaya, 2018. "Short-term power load probability density forecasting based on Yeo-Johnson transformation quantile regression and Gaussian kernel function," Energy, Elsevier, vol. 154(C), pages 143-156.
  16. Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
  17. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Prediction and explanation of the formation of the Spanish day-ahead electricity price through machine learning regression," Applied Energy, Elsevier, vol. 239(C), pages 610-625.
  18. Juan Ignacio Pe~na & Rosa Rodriguez & Silvia Mayoral, 2022. "Tail Risk of Electricity Futures," Papers 2202.01732, arXiv.org.
  19. Wang, Di & Zhang, Zhiyuan & Yang, Xiaodi & Zhang, Yanfang & Li, Yuman & Zhao, Yueying, 2021. "Multi-scenario simulation on the impact of China's electricity bidding policy based on complex networks model," Energy Policy, Elsevier, vol. 158(C).
  20. Chen, Ying & Zhu, Xuehong & Li, Hailing, 2022. "The asymmetric effects of oil price shocks and uncertainty on non-ferrous metal market: Based on quantile regression," Energy, Elsevier, vol. 246(C).
  21. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
  22. Jasiński, Tomasz, 2020. "Use of new variables based on air temperature for forecasting day-ahead spot electricity prices using deep neural networks: A new approach," Energy, Elsevier, vol. 213(C).
  23. Peña, Juan Ignacio & Rodríguez, Rosa & Mayoral, Silvia, 2020. "Tail risk of electricity futures," Energy Economics, Elsevier, vol. 91(C).
  24. Gabrielli, Paolo & Wüthrich, Moritz & Blume, Steffen & Sansavini, Giovanni, 2022. "Data-driven modeling for long-term electricity price forecasting," Energy, Elsevier, vol. 244(PB).
  25. Sirin, Selahattin Murat & Yilmaz, Berna N., 2020. "Variable renewable energy technologies in the Turkish electricity market: Quantile regression analysis of the merit-order effect," Energy Policy, Elsevier, vol. 144(C).
  26. Huisman, Ronald & Stet, Cristian, 2022. "The dependence of quantile power prices on supply from renewables," Energy Economics, Elsevier, vol. 105(C).
  27. Uribe, Jorge M. & Mosquera-López, Stephania & Arenas, Oscar J., 2022. "Assessing the relationship between electricity and natural gas prices in European markets in times of distress," Energy Policy, Elsevier, vol. 166(C).
  28. Uribe, Jorge M. & Mosquera-López, Stephanía & Guillen, Montserrat, 2020. "Characterizing electricity market integration in Nord Pool," Energy, Elsevier, vol. 208(C).
  29. Monjazeb, Mohammad Reza & Amiri, Hossein & Movahedi, Akram, 2024. "Wholesale electricity price forecasting by Quantile Regression and Kalman Filter method," Energy, Elsevier, vol. 290(C).
  30. Westgaard, Sjur & Fleten, Stein-Erik & Negash, Ahlmahz & Botterud, Audun & Bogaard, Katinka & Verling, Trude Haugsvaer, 2021. "Performing price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity market," Energy, Elsevier, vol. 214(C).
  31. He, Yaoyao & Liu, Rui & Li, Haiyan & Wang, Shuo & Lu, Xiaofen, 2017. "Short-term power load probability density forecasting method using kernel-based support vector quantile regression and Copula theory," Applied Energy, Elsevier, vol. 185(P1), pages 254-266.
  32. Antonio Bello & Derek Bunn & Javier Reneses & Antonio Muñoz, 2016. "Parametric Density Recalibration of a Fundamental Market Model to Forecast Electricity Prices," Energies, MDPI, vol. 9(11), pages 1-15, November.
  33. Sirin, Selahattin Murat & Yilmaz, Berna N., 2021. "The impact of variable renewable energy technologies on electricity markets: An analysis of the Turkish balancing market," Energy Policy, Elsevier, vol. 151(C).
  34. Gaurav Kapoor & Nuttanan Wichitaksorn & Wenjun Zhang, 2023. "Analyzing and forecasting electricity price using regime‐switching models: The case of New Zealand market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2011-2026, December.
  35. Crespo-Vazquez, Jose L. & Carrillo, C. & Diaz-Dorado, E. & Martinez-Lorenzo, Jose A. & Noor-E-Alam, Md., 2018. "A machine learning based stochastic optimization framework for a wind and storage power plant participating in energy pool market," Applied Energy, Elsevier, vol. 232(C), pages 341-357.
  36. Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego Fernando, 2017. "Nonlinear empirical pricing in electricity markets using fundamental weather factors," Energy, Elsevier, vol. 139(C), pages 594-605.
  37. Gökgöz, Fazıl & Yücel, Öykü, 2024. "Merit-order of dispatchable and variable renewable energy sources in Turkey's day-ahead electricity market," Utilities Policy, Elsevier, vol. 88(C).
  38. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
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