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Grzegorz Marcjasz

Citations

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Working papers

  1. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.

    Cited by:

    1. Simon Hirsch, 2025. "Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting," Papers 2504.02518, arXiv.org, revised Sep 2026.
    2. Weronika Nitka & Rafa{l} Weron, 2023. "Combining predictive distributions of electricity prices: Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?," Papers 2308.15443, arXiv.org.
    3. David P. Brown & Daniel O. Cajueiro & Andrew Eckert & Douglas Silveira, 2024. "Evaluating the Role of Information Disclosure on Bidding Behavior in Wholesale Electricity Markets," Working Papers 2024-02, University of Alberta, Department of Economics.
    4. Pan, Wenchao & Guo, Zhichen & Zhang, Jiayan Shi Yaxuan & Luo, Lingle, 2024. "Forecasting of coal and electricity prices in China: Evidence from the quantum bee colony-support vector regression neural network," Energy Economics, Elsevier, vol. 134(C).
    5. Arkadiusz Lipiecki & Bartosz Uniejewski & Rafa{l} Weron, 2024. "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Papers 2404.02270, arXiv.org, revised Oct 2024.
    6. Nickelsen, Daniel & Müller, Gernot, 2025. "Bayesian hierarchical probabilistic forecasting of intraday electricity prices," Applied Energy, Elsevier, vol. 380(C).
    7. Cerasa, Andrea & Zani, Alessandro, 2025. "Enhancing electricity price forecasting accuracy: A novel filtering strategy for improved out-of-sample predictions," Applied Energy, Elsevier, vol. 383(C).
    8. Francesco Lisi & Ismail Shah, 2024. "Joint Component Estimation for Electricity Price Forecasting Using Functional Models," Energies, MDPI, vol. 17(14), pages 1-18, July.
    9. Serafin, Tomasz & Weron, Rafał, 2025. "Loss functions in regression models: Impact on profits and risk in day-ahead electricity trading," Energy Economics, Elsevier, vol. 148(C).
    10. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
    11. Hugo Gobato Souto, 2026. "Evaluating the Efficacy of NHITS for Forecasting Stock Realized Volatility: A Comparative Analysis with Established Models," Computational Economics, Springer;Society for Computational Economics, vol. 67(2), pages 1291-1348, February.
    12. 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).
    13. Forgetta, Anthony & Godin, Frédéric & Augustyniak, Maciej, 2025. "Distributional forecasting of electricity DART spreads with a covariate-dependent mixture model," Energy Economics, Elsevier, vol. 144(C).
    14. Hilger, Hannes & Witthaut, Dirk & Dahmen, Manuel & Rydin Gorjão, Leonardo & Trebbien, Julius & Cramer, Eike, 2024. "Multivariate scenario generation of day-ahead electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 367(C).
    15. Ciaran O'Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets," Papers 2511.05523, arXiv.org.
    16. Berrisch, Jonathan & Ziel, Florian, 2024. "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1568-1586.
    17. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
    18. Ghelasi, Paul & Ziel, Florian, 2025. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 217(C).
    19. Mascarenhas, Maria Margarida & De Blauwe, Jilles & Amelin, Mikael & Kazmi, Hussain, 2026. "Leveraging asynchronous cross-border market data for improved day-ahead electricity price forecasting in European markets," Applied Energy, Elsevier, vol. 404(C).
    20. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
    21. Uniejewski, Bartosz, 2025. "Smoothing quantile regression averaging: A new approach to probabilistic forecasting of electricity prices," Journal of Commodity Markets, Elsevier, vol. 39(C).
    22. Ben Amor, Souhir & Ziel, Florian, 2026. "Recurrent neural networks with linear structures for electricity price forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 231(C).
    23. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    24. Jakub Micha'nk'ow, 2025. "Forecasting Probability Distributions of Financial Returns with Deep Neural Networks," Papers 2508.18921, arXiv.org, revised Aug 2025.
    25. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    26. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Apr 2026.
    27. Dariusz Borkowski & Michał Jaśkiewicz, 2025. "Forecasting Electricity Prices Three Days in Advance: Comparison Between Multilayer Perceptron and Support Vector Machine Networks," Energies, MDPI, vol. 18(17), pages 1-25, September.
    28. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
    29. Tomasz Serafin & Bartosz Uniejewski, 2024. "Ranking probabilistic forecasting models with different loss functions," Papers 2411.17743, arXiv.org.
    30. Hanus, Luboš & Baruník, Jozef, 2025. "Learning the probability distributions of day-ahead electricity prices," Energy Economics, Elsevier, vol. 152(C).
    31. Rashmita Saran & Bharath Supra & G. P. Girish & Sweta Singh, 2024. "Has Real Time Spot Electricity Market in India Impacted Day-Ahead Spot Electricity Market?," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, vol. 14(5), pages 347-355, September.
    32. Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2024. "Forecasting the Occurrence of Electricity Price Spikes: A Statistical-Economic Investigation Study," Forecasting, MDPI, vol. 6(1), pages 1-23, February.
    33. Ghimire, Sujan & Nguyen-Huy, Thong & Deo, Ravinesh C. & Casillas-Pérez, David & Masrur Ahmed, A.A. & Salcedo-Sanz, Sancho, 2025. "Novel deep hybrid model for electricity price prediction based on dual decomposition," Applied Energy, Elsevier, vol. 395(C).
    34. Max Kleinebrahm & Jonathan Berrisch & Philipp Eiser & Wolf Fichtner & Veit Hagenmeyer & Matthias Hertel & Nils Koster & Sebastian Lerch & Ralf Mikut & Jan Priesmann & Melanie Schienle & Benjamin Schae, 2026. "Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting," Papers 2604.24705, arXiv.org.
    35. Katarzyna Maciejowska & Arkadiusz Lipiecki & Bartosz Uniejewski, 2025. "Statistical and economic evaluation of forecasts in electricity markets: beyond RMSE and MAE," Papers 2511.13616, arXiv.org, revised Mar 2026.
    36. Ciaran O’Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "A Review of Electricity Price Forecasting Models in the Day-Ahead, Intra-Day, and Balancing Markets," Energies, MDPI, vol. 18(12), pages 1-40, June.
    37. Li, Ke & Mu, Yuchen & Yang, Fan & Wang, Haiyang & Yan, Yi & Zhang, Chenghui, 2024. "Joint forecasting of source-load-price for integrated energy system based on multi-task learning and hybrid attention mechanism," Applied Energy, Elsevier, vol. 360(C).
    38. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    39. Shao, Zhen & Zhu, Guowei & Han, Yating & Zha, Jianrui & Yang, Changhui & Li, Fangyi, 2025. "Multi-distribution fusion based Bayesian deep neural network for short-term probabilistic electricity price forecasting," Applied Energy, Elsevier, vol. 401(PB).
    40. Brusaferri, Alessandro & Ballarino, Andrea & Grossi, Luigi & Laurini, Fabrizio, 2025. "On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices," Applied Energy, Elsevier, vol. 398(C).
    41. Paul Ghelasi & Florian Ziel, 2024. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Papers 2406.00326, arXiv.org, revised Aug 2024.
    42. Runyao Yu & Derek W. Bunn & Julia Lin & Jochen Stiasny & Fabian Leimgruber & Tara Esterl & Yuchen Tao & Lianlian Qi & Yujie Chen & Wentao Wang & Jochen L. Cremer, 2026. "Deep Learning for Electricity Price Forecasting: A Review of Day-Ahead, Intraday, and Balancing Electricity Markets," Papers 2602.10071, arXiv.org, revised May 2026.

  2. Arkadiusz Jk{e}drzejewski & Jesus Lago & Grzegorz Marcjasz & Rafa{l} Weron, 2022. "Electricity Price Forecasting: The Dawn of Machine Learning," Papers 2204.00883, arXiv.org.

    Cited by:

    1. David P. Brown & Daniel O. Cajueiro & Andrew Eckert & Douglas Silveira, 2024. "Evaluating the Role of Information Disclosure on Bidding Behavior in Wholesale Electricity Markets," Working Papers 2024-02, University of Alberta, Department of Economics.
    2. My Thi Diem Phan & Trung Tuyen Truong & Hoai Phuong Ha & Dat Thanh Nguyen, 2026. "Electricity price forecasting across Norway's five bidding zones in the post-crisis era," Papers 2604.26634, arXiv.org, revised Jun 2026.
    3. Hilger, Hannes & Witthaut, Dirk & Dahmen, Manuel & Rydin Gorjão, Leonardo & Trebbien, Julius & Cramer, Eike, 2024. "Multivariate scenario generation of day-ahead electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 367(C).
    4. Ciaran O'Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets," Papers 2511.05523, arXiv.org.
    5. Hanus, Luboš & Baruník, Jozef, 2025. "Learning the probability distributions of day-ahead electricity prices," Energy Economics, Elsevier, vol. 152(C).
    6. Shiva Madadkhani & Nils Sturma & Mathias Drton & Svetlana Ikonnikova, 2026. "Mapping the causal structure of price formation in Texas's transitioning electricity market," Papers 2604.14257, arXiv.org, revised Jun 2026.
    7. Cramer, Eike & Witthaut, Dirk & Mitsos, Alexander & Dahmen, Manuel, 2023. "Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 346(C).
    8. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
    9. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    10. Brusaferri, Alessandro & Ballarino, Andrea & Grossi, Luigi & Laurini, Fabrizio, 2025. "On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices," Applied Energy, Elsevier, vol. 398(C).
    11. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    12. Runyao Yu & Derek W. Bunn & Julia Lin & Jochen Stiasny & Fabian Leimgruber & Tara Esterl & Yuchen Tao & Lianlian Qi & Yujie Chen & Wentao Wang & Jochen L. Cremer, 2026. "Deep Learning for Electricity Price Forecasting: A Review of Day-Ahead, Intraday, and Balancing Electricity Markets," Papers 2602.10071, arXiv.org, revised May 2026.

  3. Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.

    Cited by:

    1. Jiang, He & Dong, Yawei & Dong, Yao & Wang, Jianzhou, 2025. "Probabilistic electricity price forecasting by integrating interpretable model," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    2. Hu, Zhiyuan & Yang, Rui & Fang, Liang & Wang, Zhuo & Zhao, Yinghua, 2024. "Research on vehicle speed prediction model based on traffic flow information fusion," Energy, Elsevier, vol. 292(C).
    3. Alex Twinomuhwezi & Benjamin Musiita & Frederick Nsambu Kijjambu, 2025. "Macro-Financial Determinants of Electricity Power Loss in Uganda," Journal of Economics and Behavioral Studies, AMH International, vol. 17(1), pages 96-107.
    4. Hugo Gobato Souto, 2026. "Evaluating the Efficacy of NHITS for Forecasting Stock Realized Volatility: A Comparative Analysis with Established Models," Computational Economics, Springer;Society for Computational Economics, vol. 67(2), pages 1291-1348, February.
    5. Behmiri, Niaz Bashiri & Fezzi, Carlo & Ravazzolo, Francesco, 2026. "Renewable sources and short-to-mid-term electricity price forecasting," Journal of Commodity Markets, Elsevier, vol. 41(C).
    6. Lu, Hongkun & Gao, Xiaoxia & Yu, Jinxiao & Zhao, Qiansheng & Zhu, Xiaoxun & Ma, Wanli & Cao, Jingyuan & Wang, Yu, 2025. "Analysis and prediction of incoming wind speed for turbines in complex wind farm: Accounting for meteorological factors and spatiotemporal characteristics of wind farm," Applied Energy, Elsevier, vol. 381(C).
    7. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    8. Ayben Koy & Andaç Batur Çolak, 2026. "Electricity Price Prediction using Artificial Neural Network Models: A New and Comparative Analysis with Diverse Industry Production Indices," Computational Economics, Springer;Society for Computational Economics, vol. 68(1), pages 549-577, July.
    9. Uniejewski, Bartosz, 2025. "Smoothing quantile regression averaging: A new approach to probabilistic forecasting of electricity prices," Journal of Commodity Markets, Elsevier, vol. 39(C).
    10. Olivares, Kin G. & Meetei, O. Nganba & Ma, Ruijun & Reddy, Rohan & Cao, Mengfei & Dicker, Lee, 2024. "Probabilistic hierarchical forecasting with deep Poisson mixtures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 470-489.
    11. Sun, Wenjie & Wu, Chengke & Xie, Chengde & Wang, Xikang & Guo, Yuanjun & Tang, Yongbing & Zhang, Yanhui & Li, Kang & Du, Guanhao & Yang, Zhile & Yao, Wenjiao, 2025. "Fine-tuning enables state of health estimation for lithium-ion batteries via a time series foundation model," Energy, Elsevier, vol. 318(C).
    12. Seman, Laio Oriel & Stefenon, Stefano Frizzo & Yow, Kin-Choong & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2026. "Multi-step short-term solar energy forecasting using Fourier-enhanced BiLSTM and neural additive models," Renewable Energy, Elsevier, vol. 257(C).
    13. Wang, Yong & Fan, Neng & Wen, Shixiong & Kuang, Wenyu & Yang, Zhongsen & Xiao, Wenlian & Li, Hong-Li & Narayanan, Govindasami & Sapnken, Flavian Emmanuel, 2025. "A novel structural adaptive discrete grey Euler model and its application in clean energy production and consumption," Energy, Elsevier, vol. 323(C).
    14. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
    15. Yang, Liuyu & An, Yuan & Zhang, Gang & Xie, Tuo & Liu, Mengxin, 2026. "Day-ahead electricity price forecasting method integrating multi-scale hypergraph features and dual-layer transformer," Applied Energy, Elsevier, vol. 407(C).
    16. Lipiecki, Arkadiusz & Uniejewski, Bartosz & Weron, Rafał, 2024. "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Energy Economics, Elsevier, vol. 139(C).
    17. Ghimire, Sujan & Deo, Ravinesh C. & Liu, Hangyue & Hopf, Konstantin & Nguyen-Huy, Thong & Casillas-Pérez, David & Pérez-Aracil, Jorge & Salcedo-Sanz, Sancho, 2026. "Explainable Singular Spectrum Analysis deep learning model for half-hourly electricity price prediction," Applied Energy, Elsevier, vol. 410(C).
    18. Hussain, Shahid & Teni, Abhishek Prasad & Hussain, Ihtisham & Hussain, Zakir & Pallonetto, Fabiano & Eichman, Josh & Irshad, Reyazur Rashid & Alwayle, Ibrahim M. & Alharby, Maher & Hussain, Md Asdaque, 2024. "Enhancing electric vehicle charging efficiency at the aggregator level: A deep-weighted ensemble model for wholesale electricity price forecasting," Energy, Elsevier, vol. 308(C).
    19. Brusaferri, Alessandro & Ballarino, Andrea & Grossi, Luigi & Laurini, Fabrizio, 2025. "On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices," Applied Energy, Elsevier, vol. 398(C).
    20. Abbas, Muhammad & Che, Yanbo & Khan, Inam Ullah, 2025. "A novel stacked ensemble framework with the Kolmogorov-Arnold Network for short-term electric load forecasting," Energy, Elsevier, vol. 332(C).
    21. Lin Wang & Wuyue An & Feng‐Ting Li, 2024. "Text‐based corn futures price forecasting using improved neural basis expansion network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2042-2063, September.
    22. Saâdaoui, Foued & Ben Jabeur, Sami, 2023. "Analyzing the influence of geopolitical risks on European power prices using a multiresolution causal neural network," Energy Economics, Elsevier, vol. 124(C).
    23. Runyao Yu & Derek W. Bunn & Julia Lin & Jochen Stiasny & Fabian Leimgruber & Tara Esterl & Yuchen Tao & Lianlian Qi & Yujie Chen & Wentao Wang & Jochen L. Cremer, 2026. "Deep Learning for Electricity Price Forecasting: A Review of Day-Ahead, Intraday, and Balancing Electricity Markets," Papers 2602.10071, arXiv.org, revised May 2026.
    24. Sahaj Raj Malla, 2026. "Kalimati Vegetable Price Index Forecasting with a Momentum Corrected Online Stacking Ensemble," Papers 2605.30720, arXiv.org.
    25. Marco Zanotti, 2025. "Do global forecasting models require frequent retraining?," Working Papers 551, University of Milano-Bicocca, Department of Economics.

  4. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafal Weron, 2021. "Erratum to 'Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark' [Appl. Energy 293 (2021) 116983]," WORking papers in Management Science (WORMS) WORMS/21/12, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.

    Cited by:

    1. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    2. Tomasz Zema & Adam Sulich, 2022. "Models of Electricity Price Forecasting: Bibliometric Research," Energies, MDPI, vol. 15(15), pages 1-18, August.
    3. Nikola Mišnić & Bojan Pejović & Jelena Jovović & Sunčica Rogić & Vladimir Đurišić, 2022. "The Economic Viability of PV Power Plant Based on a Neural Network Model of Electricity Prices Forecast: A Case of a Developing Market," Energies, MDPI, vol. 15(17), pages 1-14, August.
    4. Grzegorz Dudek, 2022. "A Comprehensive Study of Random Forest for Short-Term Load Forecasting," Energies, MDPI, vol. 15(20), pages 1-19, October.
    5. Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
    6. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
    7. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    8. Stephen Haben & Julien Caudron & Jake Verma, 2021. "Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain," Forecasting, MDPI, vol. 3(3), pages 1-37, August.
    9. Fang Guo & Shangyun Deng & Weijia Zheng & An Wen & Jinfeng Du & Guangshan Huang & Ruiyang Wang, 2022. "Short-Term Electricity Price Forecasting Based on the Two-Layer VMD Decomposition Technique and SSA-LSTM," Energies, MDPI, vol. 15(22), pages 1-20, November.
    10. Vladimir Franki & Darin Majnarić & Alfredo Višković, 2023. "A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector," Energies, MDPI, vol. 16(3), pages 1-35, January.
    11. Ivan Borisov Todorov & Fernando Sánchez Lasheras, 2022. "Forecasting Applied to the Electricity, Energy, Gas and Oil Industries: A Systematic Review," Mathematics, MDPI, vol. 10(21), pages 1-15, October.
    12. Stefano Frizzo Stefenon & Laio Oriel Seman & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2023. "Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices," Energies, MDPI, vol. 16(3), pages 1-18, January.
    13. Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
    14. Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
    15. Julia Nasiadka & Weronika Nitka & Rafa{l} Weron, 2022. "Calibration window selection based on change-point detection for forecasting electricity prices," Papers 2204.00872, arXiv.org.
    16. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu & Athanasios Ioannis Arvanitidis & Lefteri H. Tsoukalas, 2022. "Error Compensation Enhanced Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 15(4), pages 1-21, February.
    17. Nazila Pourhaji & Mohammad Asadpour & Ali Ahmadian & Ali Elkamel, 2022. "The Investigation of Monthly/Seasonal Data Clustering Impact on Short-Term Electricity Price Forecasting Accuracy: Ontario Province Case Study," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    18. Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
    19. Jethro Browell & Ciaran Gilbert, 2022. "Predicting Electricity Imbalance Prices and Volumes: Capabilities and Opportunities," Energies, MDPI, vol. 15(10), pages 1-7, May.
    20. Joanna Janczura, 2025. "Expectile regression averaging method for probabilistic forecasting of electricity prices," Computational Statistics, Springer, vol. 40(2), pages 683-700, February.
    21. Roman V. Klyuev & Irbek D. Morgoev & Angelika D. Morgoeva & Oksana A. Gavrina & Nikita V. Martyushev & Egor A. Efremenkov & Qi Mengxu, 2022. "Methods of Forecasting Electric Energy Consumption: A Literature Review," Energies, MDPI, vol. 15(23), pages 1-33, November.
    22. Diankai Wang & Inna Gryshova & Mykola Kyzym & Tetiana Salashenko & Viktoriia Khaustova & Maryna Shcherbata, 2022. "Electricity Price Instability over Time: Time Series Analysis and Forecasting," Sustainability, MDPI, vol. 14(15), pages 1-24, July.
    23. Aris Dimeas & George Kiokes, 2022. "PV Penetration under Market Environment and with System Constraints," Energies, MDPI, vol. 15(22), pages 1-11, November.
    24. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    25. Hakan Acaroğlu & Fausto Pedro García Márquez, 2021. "Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy," Energies, MDPI, vol. 14(22), pages 1-23, November.
    26. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).

  5. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.

    Cited by:

    1. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    2. Gaurav Kapoor & Nuttanan Wichitaksorn & Mengheng Li & Wenjun Zhang, 2025. "Forecasting Half-Hourly Electricity Prices Using a Mixed-Frequency Structural VAR Framework," Econometrics, MDPI, vol. 13(1), pages 1-26, January.
    3. Tomasz Zema & Adam Sulich, 2022. "Models of Electricity Price Forecasting: Bibliometric Research," Energies, MDPI, vol. 15(15), pages 1-18, August.
    4. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    5. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    6. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
    7. Ghelasi, Paul & Ziel, Florian, 2025. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 217(C).
    8. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
    9. Pablo Alejandro Mendez-Santos & Nathalia Alexandra Chacón-Reino & Luis Fernando Guerrero-Vásquez & Jorge Osmani Ordoñez-Ordoñez & Paul Andrés Chasi-Pesantez, 2025. "Estimation and Forecasting of the Average Unit Cost of Energy Supply in a Distribution System Using Multiple Linear Regression and ARIMAX Modeling in Ecuador," Energies, MDPI, vol. 18(14), pages 1-33, July.
    10. Nazila Pourhaji & Mohammad Asadpour & Ali Ahmadian & Ali Elkamel, 2022. "The Investigation of Monthly/Seasonal Data Clustering Impact on Short-Term Electricity Price Forecasting Accuracy: Ontario Province Case Study," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    11. Paul Ghelasi & Florian Ziel, 2024. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Papers 2406.00326, arXiv.org, revised Aug 2024.
    12. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.

  6. Tomasz Serafin & Grzegorz Marcjasz & Rafal Weron, 2020. "Trading on short-term path forecasts of intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/17, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.

    Cited by:

    1. Runyao Yu & Yuchen Tao & Fabian Leimgruber & Tara Esterl & Jochen Stiasny & Derek W. Bunn & Qingsong Wen & Hongye Guo & Jochen L. Cremer, 2025. "OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting," Papers 2502.06830, arXiv.org, revised May 2026.
    2. Di Persio, Luca & Garbelli, Matteo & Giordano, Luca Maria, 2025. "Reinforcement learning for bidding strategy optimization in day-ahead energy market," Energy Economics, Elsevier, vol. 149(C).
    3. Ciaran O'Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets," Papers 2511.05523, arXiv.org.
    4. Antoine Pesenti & Aidan O'Sullivan, 2026. "Analysing drivers and interdependencies in European electricity markets using XAI," Papers 2606.19118, arXiv.org.
    5. Krishna, Attoti Bharath & Abhyankar, Abhijit R., 2023. "Time-coupled day-ahead wind power scenario generation: A combined regular vine copula and variance reduction method," Energy, Elsevier, vol. 265(C).
    6. Ciaran O’Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "A Review of Electricity Price Forecasting Models in the Day-Ahead, Intra-Day, and Balancing Markets," Energies, MDPI, vol. 18(12), pages 1-40, June.
    7. Joanna Janczura, 2025. "Expectile regression averaging method for probabilistic forecasting of electricity prices," Computational Statistics, Springer, vol. 40(2), pages 683-700, February.
    8. Cramer, Eike & Witthaut, Dirk & Mitsos, Alexander & Dahmen, Manuel, 2023. "Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 346(C).
    9. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    10. Carrión, Miguel & Domínguez, Ruth & Oggioni, Giorgia, 2025. "Optimal participation of wind power producers in a hybrid intraday market: A multi-stage stochastic approach," Energy Economics, Elsevier, vol. 144(C).
    11. Rainer Baule & Michael Naumann, 2022. "Flexible Short-Term Electricity Certificates—An Analysis of Trading Strategies on the Continuous Intraday Market," Energies, MDPI, vol. 15(17), pages 1-28, August.

  7. Grzegorz Marcjasz & Jesus Lago & Rafa{l} Weron, 2020. "Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs," Papers 2008.08006, arXiv.org.

    Cited by:

    1. Li, Wei & Becker, Denis Mike, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Energy, Elsevier, vol. 237(C).
    2. Fangze Zhou & Hui Zhou & Zhaoyan Li & Kai Zhao, 2022. "Multi-Step Ahead Short-Term Electricity Load Forecasting Using VMD-TCN and Error Correction Strategy," Energies, MDPI, vol. 15(15), pages 1-18, July.
    3. Wei Li & Denis Mike Becker, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Papers 2101.05249, arXiv.org, revised Jul 2021.
    4. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu & Athanasios Ioannis Arvanitidis & Lefteri H. Tsoukalas, 2022. "Error Compensation Enhanced Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 15(4), pages 1-21, February.
    5. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).

  8. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.

    Cited by:

    1. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    2. Grzegorz Marcjasz, 2020. "Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme," Energies, MDPI, vol. 13(18), pages 1-18, September.
    3. Nickelsen, Daniel & Müller, Gernot, 2025. "Bayesian hierarchical probabilistic forecasting of intraday electricity prices," Applied Energy, Elsevier, vol. 380(C).
    4. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    5. Timoth'ee Hornek & Sergio Potenciano Menci & Ivan Pavi'c, 2025. "Directional Price Forecasting in the Continuous Intraday Market under Consideration of Neighboring Products and Limit Order Books," Papers 2509.04452, arXiv.org.
    6. Kadir Özen & Dilem Yıldırım, 2021. "Application of Bagging in Day-Ahead Electricity Price Forecasting and Factor Augmentation," ERC Working Papers 2101, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
    7. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    8. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
    9. Yuriy Bilan & Serhiy Kozmenko & Alex Plastun, 2022. "Price Forecasting in Energy Market," Energies, MDPI, vol. 15(24), pages 1-6, December.
    10. Kaiyao Jiang & Yuji Yamada, 2025. "A Comprehensive Analysis of Imbalance Signal Prediction in the Japanese Electricity Market Using Machine Learning Techniques," Energies, MDPI, vol. 18(11), pages 1-28, May.
    11. Grzegorz Marcjasz & Jesus Lago & Rafa{l} Weron, 2020. "Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs," Papers 2008.08006, arXiv.org.
    12. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    13. Hugo Siqueira & Mariana Macedo & Yara de Souza Tadano & Thiago Antonini Alves & Sergio L. Stevan & Domingos S. Oliveira & Manoel H.N. Marinho & Paulo S.G. de Mattos Neto & João F. L. de Oliveira & Ive, 2020. "Selection of Temporal Lags for Predicting Riverflow Series from Hydroelectric Plants Using Variable Selection Methods," Energies, MDPI, vol. 13(16), pages 1-35, August.
    14. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    15. Kuppelwieser, Thomas & Wozabal, David, 2021. "Liquidity costs on intraday power markets: Continuous trading versus auctions," Energy Policy, Elsevier, vol. 154(C).
    16. Yiming Zhang & Wolfgang Ridinger & David Wozabal, 2025. "Joint Bidding on Intraday and Frequency Containment Reserve Markets," Papers 2510.03209, arXiv.org.
    17. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    18. Philip Beran & Arne Vogler, 2021. "Multi-Day-Ahead Electricity Price Forecasting: A Comparison of fundamental, econometric and hybrid Models," EWL Working Papers 2102, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2021.
    19. Adela Bara & Simona-Vasilica Oprea & Andreea-Mihaela Niculae, "undated". "Electricity Price Evolution and the Disruptive Economic and Geopolitical Context on the Spot Market. A Romanian Case Study," BASIQ Conference Proceedings 2023:002, Bucharest University of Economic Studies.

  9. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.

    Cited by:

    1. Simon Hirsch, 2025. "Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting," Papers 2504.02518, arXiv.org, revised Sep 2026.
    2. Gomez, William & Wang, Fu-Kwun & Sheu, Shey-Huei, 2025. "Short-term smart grid energy forecasting using a hybrid deep learning method on univariate and multivariate data sets," Energy, Elsevier, vol. 335(C).
    3. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    4. Shiva Zamani & Alireza Moslemi Haghighi & Hamid Arian, 2023. "Temporal Volatility Surface Projection: Parametric Surface Projection Method for Derivatives Portfolio Risk Management," Papers 2311.14985, arXiv.org.
    5. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    6. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    7. Francesco Ravazzolo & Luca Rossini & Andrea Viselli, 2025. "Modeling European electricity market integration during turbulent times," Working Papers 2025.25, Fondazione Eni Enrico Mattei.
    8. Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
    9. Tomasz Zema & Adam Sulich, 2022. "Models of Electricity Price Forecasting: Bibliometric Research," Energies, MDPI, vol. 15(15), pages 1-18, August.
    10. Lehna, Malte & Scheller, Fabian & Herwartz, Helmut, 2022. "Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account," Energy Economics, Elsevier, vol. 106(C).
    11. Weronika Nitka & Rafa{l} Weron, 2023. "Combining predictive distributions of electricity prices: Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?," Papers 2308.15443, arXiv.org.
    12. Stylianos Loizidis & Georgios Konstantinidis & Spyros Theocharides & Andreas Kyprianou & George E. Georghiou, 2023. "Electricity Day-Ahead Market Conditions and Their Effect on the Different Supervised Algorithms for Market Price Forecasting," Energies, MDPI, vol. 16(12), pages 1-29, June.
    13. Nikola Mišnić & Bojan Pejović & Jelena Jovović & Sunčica Rogić & Vladimir Đurišić, 2022. "The Economic Viability of PV Power Plant Based on a Neural Network Model of Electricity Prices Forecast: A Case of a Developing Market," Energies, MDPI, vol. 15(17), pages 1-14, August.
    14. Ciaran O'Connor & Joseph Collins & Steven Prestwich & Andrea Visentin, 2024. "Electricity Price Forecasting in the Irish Balancing Market," Papers 2402.06714, arXiv.org.
    15. Daniel Foronda-Pascual & Andrés M. Alonso, 2023. "Prediction of Matching Prices in Electricity Markets through Curve Representation," Energies, MDPI, vol. 16(23), pages 1-20, November.
    16. Grzegorz Dudek, 2022. "A Comprehensive Study of Random Forest for Short-Term Load Forecasting," Energies, MDPI, vol. 15(20), pages 1-19, October.
    17. Thakur, Jagruti & Hesamzadeh, Mohammad Reza & Date, Paresh & Bunn, Derek, 2023. "Pricing and hedging wind power prediction risk with binary option contracts," Energy Economics, Elsevier, vol. 126(C).
    18. Dong, Zhu & Shi, Hui, 2023. "Does natural resources efficiency provide roadmap for economic development in China? Evidence from econometric analysis," Resources Policy, Elsevier, vol. 86(PB).
    19. Jiang, Ping & Nie, Ying & Wang, Jianzhou & Huang, Xiaojia, 2023. "Multivariable short-term electricity price forecasting using artificial intelligence and multi-input multi-output scheme," Energy Economics, Elsevier, vol. 117(C).
    20. Arkadiusz Lipiecki & Bartosz Uniejewski & Rafa{l} Weron, 2024. "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Papers 2404.02270, arXiv.org, revised Oct 2024.
    21. Prakash, Abhijith & Bruce, Anna & MacGill, Iain, 2025. "The scheduling role of future pricing information in electricity markets with rising deployments of energy storage: An Australian National Electricity Market case study," Energy Economics, Elsevier, vol. 142(C).
    22. Krishna Prakash N. & Jai Govind Singh, 2023. "Electricity price forecasting using hybrid deep learned networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1750-1771, November.
    23. Cerasa, Andrea & Zani, Alessandro, 2025. "Enhancing electricity price forecasting accuracy: A novel filtering strategy for improved out-of-sample predictions," Applied Energy, Elsevier, vol. 383(C).
    24. Francesco Lisi & Ismail Shah, 2024. "Joint Component Estimation for Electricity Price Forecasting Using Functional Models," Energies, MDPI, vol. 17(14), pages 1-18, July.
    25. Aamer A. Shah & Almani A. Aftab & Xueshan Han & Mazhar Hussain Baloch & Mohamed Shaik Honnurvali & Sohaib Tahir Chauhdary, 2023. "Prediction Error-Based Power Forecasting of Wind Energy System Using Hybrid WT–ROPSO–NARMAX Model," Energies, MDPI, vol. 16(7), pages 1-15, April.
    26. Firuz Kamalov & Hana Sulieman & Sherif Moussa & Jorge Avante Reyes & Murodbek Safaraliev, 2024. "Powering Electricity Forecasting with Transfer Learning," Energies, MDPI, vol. 17(3), pages 1-13, January.
    27. Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
    28. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    29. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
    30. Serafin, Tomasz & Weron, Rafał, 2025. "Loss functions in regression models: Impact on profits and risk in day-ahead electricity trading," Energy Economics, Elsevier, vol. 148(C).
    31. My Thi Diem Phan & Trung Tuyen Truong & Hoai Phuong Ha & Dat Thanh Nguyen, 2026. "Electricity price forecasting across Norway's five bidding zones in the post-crisis era," Papers 2604.26634, arXiv.org, revised Jun 2026.
    32. Gokavarapu, Kamal Nikhil & Gore, Nidhish Abhijit & Ohri, Chirag & Carbonara, Joaquin & Ahmed, Saquib, 2025. "Machine learning analysis of New York clean energy trends," Energy Economics, Elsevier, vol. 152(C).
    33. Failing, J.M. & Segarra-Tamarit, J. & Cardo-Miota, J. & Beltran, H., 2026. "Deep learning-based prediction models for spot electricity market prices in the Spanish market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 240(C), pages 96-104.
    34. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
    35. Hilger, Hannes & Witthaut, Dirk & Dahmen, Manuel & Rydin Gorjão, Leonardo & Trebbien, Julius & Cramer, Eike, 2024. "Multivariate scenario generation of day-ahead electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 367(C).
    36. Ciaran O'Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets," Papers 2511.05523, arXiv.org.
    37. Belenguer, E. & Segarra-Tamarit, J. & Pérez, E. & Vidal-Albalate, R., 2025. "Short-term electricity price forecasting through demand and renewable generation prediction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 229(C), pages 350-361.
    38. Behmiri, Niaz Bashiri & Fezzi, Carlo & Ravazzolo, Francesco, 2026. "Renewable sources and short-to-mid-term electricity price forecasting," Journal of Commodity Markets, Elsevier, vol. 41(C).
    39. Dorel Mihai Paraschiv & Narciz Balasoiu & Souhir Ben-Amor & Raul Cristian Bag, 2023. "Hybridising Neurofuzzy Model the Seasonal Autoregressive Models for Electricity Price Forecasting on Germany’s Spot Market," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(63), pages 463-463, April.
    40. Kaya, Anil & Conejo, Antonio J. & Rebennack, Steffen, 2026. "Fifty years of power systems optimization," European Journal of Operational Research, Elsevier, vol. 329(1), pages 1-23.
    41. Wagner, Andreas & Ramentol, Enislay & Schirra, Florian & Michaeli, Hendrik, 2022. "Short- and long-term forecasting of electricity prices using embedding of calendar information in neural networks," Journal of Commodity Markets, Elsevier, vol. 28(C).
    42. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    43. Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    44. Karol Pilot & Alicja Ganczarek-Gamrot & Krzysztof Kania, 2024. "Dealing with Anomalies in Day-Ahead Market Prediction Using Machine Learning Hybrid Model," Energies, MDPI, vol. 17(17), pages 1-20, September.
    45. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    46. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
    47. Mao, Xuehui & Chen, Shanlin & Yu, Hanxin & Duan, Liwu & He, Yingjie & Chu, Yinghao, 2025. "Simplicity in dynamic and competitive electricity markets: A case study on enhanced linear models versus complex deep-learning models for day-ahead electricity price forecasting," Applied Energy, Elsevier, vol. 383(C).
    48. Konstantinos Plakas & Ioannis Karampinis & Panayiotis Alefragis & Alexios Birbas & Michael Birbas & Alex Papalexopoulos, 2023. "A Predictive Fuzzy Logic Model for Forecasting Electricity Day-Ahead Market Prices for Scheduling Industrial Applications," Energies, MDPI, vol. 16(10), pages 1-21, May.
    49. Demir, Sumeyra & Mincev, Krystof & Kok, Koen & Paterakis, Nikolaos G., 2021. "Data augmentation for time series regression: Applying transformations, autoencoders and adversarial networks to electricity price forecasting," Applied Energy, Elsevier, vol. 304(C).
    50. Yin, Linfei & Qiu, Yao, 2022. "Neural network dynamic differential control for long-term price guidance mechanism of flexible energy service providers," Energy, Elsevier, vol. 255(C).
    51. Stephen Haben & Julien Caudron & Jake Verma, 2021. "Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain," Forecasting, MDPI, vol. 3(3), pages 1-37, August.
    52. Westö, Johan & Pörn, Ray & Dahal, Ashish & Borg, Mats, 2025. "Evaluating running strategies for a P2X2P plant," Applied Energy, Elsevier, vol. 391(C).
    53. Mascarenhas, Maria Margarida & De Blauwe, Jilles & Amelin, Mikael & Kazmi, Hussain, 2026. "Leveraging asynchronous cross-border market data for improved day-ahead electricity price forecasting in European markets," Applied Energy, Elsevier, vol. 404(C).
    54. Koechlin, Guillaume & Bovera, Filippo & Secchi, Piercesare, 2025. "Strategic bidding in pay-as-bid power reserve markets: A machine learning approach," Energy Economics, Elsevier, vol. 150(C).
    55. Fang Guo & Shangyun Deng & Weijia Zheng & An Wen & Jinfeng Du & Guangshan Huang & Ruiyang Wang, 2022. "Short-Term Electricity Price Forecasting Based on the Two-Layer VMD Decomposition Technique and SSA-LSTM," Energies, MDPI, vol. 15(22), pages 1-20, November.
    56. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
    57. Ben Amor, Souhir & Ziel, Florian, 2026. "Recurrent neural networks with linear structures for electricity price forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 231(C).
    58. Antoine Pesenti & Aidan O'Sullivan, 2026. "Analysing drivers and interdependencies in European electricity markets using XAI," Papers 2606.19118, arXiv.org.
    59. Juan M. Lujano-Rojas & Rodolfo Dufo-López & Jesús Sergio Artal-Sevil & Eduardo García-Paricio, 2023. "Searching for Promisingly Trained Artificial Neural Networks," Forecasting, MDPI, vol. 5(3), pages 1-26, September.
    60. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    61. Vladimir Franki & Darin Majnarić & Alfredo Višković, 2023. "A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector," Energies, MDPI, vol. 16(3), pages 1-35, January.
    62. Ivan Borisov Todorov & Fernando Sánchez Lasheras, 2022. "Forecasting Applied to the Electricity, Energy, Gas and Oil Industries: A Systematic Review," Mathematics, MDPI, vol. 10(21), pages 1-15, October.
    63. Stefano Frizzo Stefenon & Laio Oriel Seman & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2023. "Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices," Energies, MDPI, vol. 16(3), pages 1-18, January.
    64. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    65. Karamolegkos, Spyridon & Koulouriotis, Dimitrios E., 2025. "Advancing short-term load forecasting with decomposed Fourier ARIMA: A case study on the Greek energy market," Energy, Elsevier, vol. 325(C).
    66. Li, Jin & Wen, Xin & Jia, Li & Cao, Ruochen & Zhang, Xiao & Hao, Yanrong & Gao, Chengxin & Cao, Rui, 2025. "A Transformer-based model fusing temporal dependence and variable correlation for short and medium-term electricity price forecasting," Energy, Elsevier, vol. 338(C).
    67. Alberto Mozo & Stanislav Vakaruk & J. Enrique Sierra-García & Antonio Pastor, 2024. "Anticipatory analysis of AGV trajectory in a 5G network using machine learning," Journal of Intelligent Manufacturing, Springer, vol. 35(4), pages 1541-1569, April.
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  10. Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018. "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports HSC/18/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

    Cited by:

    1. Grzegorz Marcjasz, 2020. "Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme," Energies, MDPI, vol. 13(18), pages 1-18, September.
    2. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
    3. Yousef Adeli Sadabad & Mohammad Reza Hesamzadeh & Gyorgy Dan & Matin Bagherpour & Darryl R. Biggar, 2025. "Driver Identification and PCA Augmented Selection Shrinkage Framework for Nordic System Price Forecasting," Papers 2509.18887, arXiv.org.
    4. Firuz Kamalov & Hana Sulieman & Sherif Moussa & Jorge Avante Reyes & Murodbek Safaraliev, 2024. "Powering Electricity Forecasting with Transfer Learning," Energies, MDPI, vol. 17(3), pages 1-13, January.
    5. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
    6. Raffaele Sgarlato, 2023. "Statistical electricity price forecasting: A structural approach," Papers 2306.14186, arXiv.org.
    7. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    8. Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    9. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    10. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    11. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    12. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    13. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemysław Zaleski & Rafał Weron, 2020. "Balancing Generation from Renewable Energy Sources: Profitability of an Energy Trader," Energies, MDPI, vol. 13(1), pages 1-15, January.
    14. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    15. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019. "Balancing RES generation: Profitability of an energy trader," HSC Research Reports HSC/19/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    16. Weronika Nitka & Tomasz Serafin & Dimitrios Sotiros, 2021. "Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) method," WORking papers in Management Science (WORMS) WORMS/21/06, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    17. Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
    18. Chun-Yao Lee & Chang-En Wu, 2020. "Short-Term Electricity Price Forecasting Based on Similar Day-Based Neural Network," Energies, MDPI, vol. 13(17), pages 1-15, August.
    19. Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018. "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 11(9), pages 1-20, September.
    20. Kath, Christopher & Ziel, Florian, 2021. "Conformal prediction interval estimation and applications to day-ahead and intraday power markets," International Journal of Forecasting, Elsevier, vol. 37(2), pages 777-799.
    21. Tomasz Serafin & Bartosz Uniejewski & Rafał Weron, 2019. "Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 12(13), pages 1-12, July.
    22. Grzegorz Marcjasz & Jesus Lago & Rafa{l} Weron, 2020. "Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs," Papers 2008.08006, arXiv.org.
    23. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    24. Firuz Kamalov & Inga Zicmane & Murodbek Safaraliev & Linda Smail & Mihail Senyuk & Pavel Matrenin, 2024. "Attention-Based Load Forecasting with Bidirectional Finetuning," Energies, MDPI, vol. 17(18), pages 1-16, September.
    25. Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1533-1547.
    26. 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.
    27. Joanna Janczura & Aleksandra Michalak, 2020. "Optimization of Electric Energy Sales Strategy Based on Probabilistic Forecasts," Energies, MDPI, vol. 13(5), pages 1-16, February.
    28. Bartosz Uniejewski & Rafal Weron, 2019. "Regularized Quantile Regression Averaging for probabilistic electricity price forecasting," HSC Research Reports HSC/19/04, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

  11. Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2018. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," HSC Research Reports HSC/18/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

    Cited by:

    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    3. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    4. Liu, Keliang & Chen, Jian & Li, Wu & Li, Rui & Chen, Qi, 2026. "Spatio-temporal characteristics and related factors of urban on-street parking violations: A nonlinear perspective," Journal of Transport Geography, Elsevier, vol. 130(C).
    5. Lu, Xin & Qiu, Jing & Lei, Gang & Zhu, Jianguo, 2022. "Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia," Applied Energy, Elsevier, vol. 308(C).
    6. Runyao Yu & Yuchen Tao & Fabian Leimgruber & Tara Esterl & Jochen Stiasny & Derek W. Bunn & Qingsong Wen & Hongye Guo & Jochen L. Cremer, 2025. "OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting," Papers 2502.06830, arXiv.org, revised May 2026.
    7. Yang, Yang & Fan, Yawen & Jiang, Lan & Liu, Xiaohui, 2022. "Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?," Annals of Tourism Research, Elsevier, vol. 93(C).
    8. Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
    9. Li, Wei & Paraschiv, Florentina, 2022. "Modelling the evolution of wind and solar power infeed forecasts," Journal of Commodity Markets, Elsevier, vol. 25(C).
    10. Tim Janke & Florian Steinke, 2019. "Forecasting the Price Distribution of Continuous Intraday Electricity Trading," Energies, MDPI, vol. 12(22), pages 1-14, November.
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    25. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    26. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
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    31. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    32. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    33. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemysław Zaleski & Rafał Weron, 2020. "Balancing Generation from Renewable Energy Sources: Profitability of an Energy Trader," Energies, MDPI, vol. 13(1), pages 1-15, January.
    34. Kadir Özen & Dilem Yıldırım, 2021. "Application of Bagging in Day-Ahead Electricity Price Forecasting and Factor Augmentation," ERC Working Papers 2101, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
    35. He Jiang & Yao Dong & Jianzhou Wang, 2024. "Electricity price forecasting using quantile regression averaging with nonconvex regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1859-1879, September.
    36. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    37. Juraj Čurpek, 2019. "Time Evolution of Hurst Exponent: Czech Wholesale Electricity Market Study," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2019(3), pages 25-44.
    38. Lu, Shixiang & Xu, Qifa & Jiang, Cuixia & Liu, Yezheng & Kusiak, Andrew, 2022. "Probabilistic load forecasting with a non-crossing sparse-group Lasso-quantile regression deep neural network," Energy, Elsevier, vol. 242(C).
    39. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019. "Balancing RES generation: Profitability of an energy trader," HSC Research Reports HSC/19/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    40. Micha{l} Narajewski & Florian Ziel, 2018. "Econometric modelling and forecasting of intraday electricity prices," Papers 1812.09081, arXiv.org, revised Sep 2019.
    41. Simon Hirsch & Florian Ziel, 2024. "Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution," The Energy Journal, , vol. 45(3), pages 87-124, May.
    42. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
    43. Paul Ghelasi & Florian Ziel, 2025. "A data-driven merit order: Learning a fundamental electricity price model," Papers 2501.02963, arXiv.org, revised Nov 2025.
    44. Feng Guo & David Schlipf, 2021. "A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics," Energies, MDPI, vol. 14(9), pages 1-19, April.
    45. Nazila Pourhaji & Mohammad Asadpour & Ali Ahmadian & Ali Elkamel, 2022. "The Investigation of Monthly/Seasonal Data Clustering Impact on Short-Term Electricity Price Forecasting Accuracy: Ontario Province Case Study," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    46. Narajewski, Michał & Ziel, Florian, 2022. "Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs," Energy Economics, Elsevier, vol. 110(C).
    47. Ghelasi, Paul & Ziel, Florian, 2026. "A data-driven merit order: Learning a fundamental electricity price model," Energy Economics, Elsevier, vol. 154(C).
    48. Michał Narajewski & Florian Ziel, 2019. "Estimation and Simulation of the Transaction Arrival Process in Intraday Electricity Markets," Energies, MDPI, vol. 12(23), pages 1-16, November.
    49. Ciaran O’Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "A Review of Electricity Price Forecasting Models in the Day-Ahead, Intra-Day, and Balancing Markets," Energies, MDPI, vol. 18(12), pages 1-40, June.
    50. Bâra, Adela & Georgescu, Irina Alexandra & Oprea, Simona-Vasilica, 2025. "The role of generation mix, demand fluctuations and sequential markets in shaping intraday electricity prices. Evidence from Romania," Renewable Energy, Elsevier, vol. 255(C).
    51. Ayşe Özmen, 2023. "Sparse regression modeling for short- and long‐term natural gas demand prediction," Annals of Operations Research, Springer, vol. 322(2), pages 921-946, March.
    52. Christopher Kath & Florian Ziel, 2020. "Optimal Order Execution in Intraday Markets: Minimizing Costs in Trade Trajectories," Papers 2009.07892, arXiv.org, revised Oct 2020.
    53. Ismael Ahrazem Dfuf & José Manuel Mira McWilliams & María Camino González Fernández, 2019. "Multi-Output Conditional Inference Trees Applied to the Electricity Market: Variable Importance Analysis," Energies, MDPI, vol. 12(6), pages 1-24, March.
    54. Marcel Kremer & Rüdiger Kiesel & Florentina Paraschiv, 2020. "Intraday Electricity Pricing of Night Contracts," Energies, MDPI, vol. 13(17), pages 1-14, September.
    55. Yafen Ye & Renyong Chi & Yuan-Hai Shao & Chun-Na Li & Xiangyu Hua, 2022. "Indicator Selection of Index Construction by Adaptive Lasso with a Generic $$\varepsilon $$ ε -Insensitive Loss," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 971-990, October.
    56. Ilkay Oksuz & Umut Ugurlu, 2019. "Neural Network Based Model Comparison for Intraday Electricity Price Forecasting," Energies, MDPI, vol. 12(23), pages 1-14, November.
    57. Mingming Hu & Xin Zhao & Jingfei Ren & Doris Chenguang Wu, 2025. "A novel big data-based multicollinearity-eliminating feature extraction method for tourism demand forecasting," Tourism Economics, , vol. 31(7), pages 1371-1401, November.
    58. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).
    59. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    60. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    61. Yiming Zhang & Wolfgang Ridinger & David Wozabal, 2025. "Joint Bidding on Intraday and Frequency Containment Reserve Markets," Papers 2510.03209, arXiv.org.
    62. Rainer Baule & Michael Naumann, 2021. "Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market," Energies, MDPI, vol. 14(22), pages 1-24, November.
    63. 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.
    64. Karpinska, Lilia & Śmiech, Sławomir, 2020. "Conceptualising housing costs: The hidden face of energy poverty in Poland," Energy Policy, Elsevier, vol. 147(C).
    65. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    66. Joanna Janczura & Aleksandra Michalak, 2020. "Optimization of Electric Energy Sales Strategy Based on Probabilistic Forecasts," Energies, MDPI, vol. 13(5), pages 1-16, February.
    67. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    68. Micha{l} Narajewski & Florian Ziel, 2019. "Estimation and simulation of the transaction arrival process in intraday electricity markets," Papers 1901.09729, arXiv.org, revised Dec 2019.
    69. Hakan Acaroğlu & Fausto Pedro García Márquez, 2021. "Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy," Energies, MDPI, vol. 14(22), pages 1-23, November.

  12. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

    Cited by:

    1. James W. Taylor & Xiaochun Meng, 2026. "Angular Combining of Forecasts of Probability Distributions," Management Science, INFORMS, vol. 72(3), pages 2111-2133, March.
    2. Lehna, Malte & Scheller, Fabian & Herwartz, Helmut, 2022. "Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account," Energy Economics, Elsevier, vol. 106(C).
    3. Weronika Nitka & Rafa{l} Weron, 2023. "Combining predictive distributions of electricity prices: Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?," Papers 2308.15443, arXiv.org.
    4. Lee, Juyong & Cho, Youngsang, 2022. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Energy, Elsevier, vol. 239(PD).
    5. Jiang, Ping & Nie, Ying & Wang, Jianzhou & Huang, Xiaojia, 2023. "Multivariable short-term electricity price forecasting using artificial intelligence and multi-input multi-output scheme," Energy Economics, Elsevier, vol. 117(C).
    6. Arkadiusz Lipiecki & Bartosz Uniejewski & Rafa{l} Weron, 2024. "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Papers 2404.02270, arXiv.org, revised Oct 2024.
    7. Arne Vogler & Florian Ziel, "undated". "On The Evaluation Of Binary Event Probability Predictions In Electricity Price Forecasting," EWL Working Papers 1911, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    8. Cerasa, Andrea & Zani, Alessandro, 2025. "Enhancing electricity price forecasting accuracy: A novel filtering strategy for improved out-of-sample predictions," Applied Energy, Elsevier, vol. 383(C).
    9. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
    10. Juyong Lee & Youngsang Cho, 2021. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Papers 2107.06174, arXiv.org.
    11. Hilger, Hannes & Witthaut, Dirk & Dahmen, Manuel & Rydin Gorjão, Leonardo & Trebbien, Julius & Cramer, Eike, 2024. "Multivariate scenario generation of day-ahead electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 367(C).
    12. Ciaran O'Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets," Papers 2511.05523, arXiv.org.
    13. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    14. Emrah Gulay & Serkan Aras, 2024. "Does a meta-combining method lead to more accurate forecasts in the decision-making process?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(3), pages 101-124.
    15. Berrisch, Jonathan & Ziel, Florian, 2024. "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1568-1586.
    16. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    17. Stephen Haben & Julien Caudron & Jake Verma, 2021. "Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain," Forecasting, MDPI, vol. 3(3), pages 1-37, August.
    18. Uniejewski, Bartosz, 2025. "Smoothing quantile regression averaging: A new approach to probabilistic forecasting of electricity prices," Journal of Commodity Markets, Elsevier, vol. 39(C).
    19. He Jiang & Yao Dong & Jianzhou Wang, 2024. "Electricity price forecasting using quantile regression averaging with nonconvex regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1859-1879, September.
    20. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    21. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    22. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
    23. Daniel Manfre Jaimes & Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2023. "A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes," Forecasting, MDPI, vol. 5(3), pages 1-23, July.
    24. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
    25. Tomasz Serafin & Bartosz Uniejewski, 2024. "Ranking probabilistic forecasting models with different loss functions," Papers 2411.17743, arXiv.org.
    26. Hanus, Luboš & Baruník, Jozef, 2025. "Learning the probability distributions of day-ahead electricity prices," Energy Economics, Elsevier, vol. 152(C).
    27. Monjazeb, Mohammad Reza & Amiri, Hossein & Movahedi, Akram, 2024. "Wholesale electricity price forecasting by Quantile Regression and Kalman Filter method," Energy, Elsevier, vol. 290(C).
    28. Katarzyna Maciejowska & Arkadiusz Lipiecki & Bartosz Uniejewski, 2025. "Statistical and economic evaluation of forecasts in electricity markets: beyond RMSE and MAE," Papers 2511.13616, arXiv.org, revised Mar 2026.
    29. Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
    30. Nie, Ying & Li, Ping & Wang, Jianzhou & Zhang, Lifang, 2024. "A novel multivariate electrical price bi-forecasting system based on deep learning, a multi-input multi-output structure and an operator combination mechanism," Applied Energy, Elsevier, vol. 366(C).
    31. Cramer, Eike & Witthaut, Dirk & Mitsos, Alexander & Dahmen, Manuel, 2023. "Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 346(C).
    32. Tomasz Serafin & Bartosz Uniejewski & Rafał Weron, 2019. "Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 12(13), pages 1-12, July.
    33. Arkadiusz Lipiecki & Bartosz Uniejewski, 2025. "Isotonic Quantile Regression Averaging for uncertainty quantification of electricity price forecasts," Papers 2507.15079, arXiv.org.
    34. Elmore, Clay T. & Dowling, Alexander W., 2021. "Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition," Energy, Elsevier, vol. 232(C).
    35. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    36. Saâdaoui, Foued & Ben Jabeur, Sami, 2023. "Analyzing the influence of geopolitical risks on European power prices using a multiresolution causal neural network," Energy Economics, Elsevier, vol. 124(C).
    37. Mira Watermeyer & Thomas Mobius & Oliver Grothe & Felix Musgens, 2023. "A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling," Papers 2304.09336, arXiv.org.
    38. Arne Vogler & Florian Ziel, 2021. "Event-Based Evaluation of Electricity Price Ensemble Forecasts," Forecasting, MDPI, vol. 4(1), pages 1-21, December.
    39. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    40. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).

  13. Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2018. "Selection of calibration windows for day-ahead electricity price forecasting," HSC Research Reports HSC/18/06, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

    Cited by:

    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Grzegorz Marcjasz, 2020. "Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme," Energies, MDPI, vol. 13(18), pages 1-18, September.
    3. Thomas Mobius & Mira Watermeyer & Oliver Grothe & Felix Musgens, 2023. "Enhancing Energy System Models Using Better Load Forecasts," Papers 2302.11017, arXiv.org.
    4. Maciejowska, Katarzyna & Nitka, Weronika & Weron, Tomasz, 2021. "Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices," Energy Economics, Elsevier, vol. 99(C).
    5. Cerasa, Andrea & Zani, Alessandro, 2025. "Enhancing electricity price forecasting accuracy: A novel filtering strategy for improved out-of-sample predictions," Applied Energy, Elsevier, vol. 383(C).
    6. Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
    7. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
    8. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
    9. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
    10. Berrisch, Jonathan & Ziel, Florian, 2024. "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1568-1586.
    11. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    12. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
    13. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    14. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    15. Bartosz Uniejewski & Katarzyna Maciejowska, 2022. "LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling," Papers 2207.04794, arXiv.org.
    16. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    17. Mascarenhas, Maria Margarida & De Blauwe, Jilles & Amelin, Mikael & Kazmi, Hussain, 2026. "Leveraging asynchronous cross-border market data for improved day-ahead electricity price forecasting in European markets," Applied Energy, Elsevier, vol. 404(C).
    18. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
    19. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemysław Zaleski & Rafał Weron, 2020. "Balancing Generation from Renewable Energy Sources: Profitability of an Energy Trader," Energies, MDPI, vol. 13(1), pages 1-15, January.
    20. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    21. Rodrigo A. de Marcos & Antonio Bello & Javier Reneses, 2019. "Short-Term Electricity Price Forecasting with a Composite Fundamental-Econometric Hybrid Methodology," Energies, MDPI, vol. 12(6), pages 1-15, March.
    22. 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.
    23. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
    24. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019. "Balancing RES generation: Profitability of an energy trader," HSC Research Reports HSC/19/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    25. Weronika Nitka & Tomasz Serafin & Dimitrios Sotiros, 2021. "Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) method," WORking papers in Management Science (WORMS) WORMS/21/06, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    26. Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
    27. Kath, Christopher & Ziel, Florian, 2021. "Conformal prediction interval estimation and applications to day-ahead and intraday power markets," International Journal of Forecasting, Elsevier, vol. 37(2), pages 777-799.
    28. Katarzyna Maciejowska & Arkadiusz Lipiecki & Bartosz Uniejewski, 2025. "Statistical and economic evaluation of forecasts in electricity markets: beyond RMSE and MAE," Papers 2511.13616, arXiv.org, revised Mar 2026.
    29. Cornell, Cameron & Dinh, Nam Trong & Pourmousavi, S. Ali, 2024. "A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1421-1437.
    30. Vasileios Laitsos & Georgios Vontzos & Paschalis Paraschoudis & Eleftherios Tsampasis & Dimitrios Bargiotas & Lefteri H. Tsoukalas, 2024. "The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market," Energies, MDPI, vol. 17(22), pages 1-37, November.
    31. Tomasz Serafin & Bartosz Uniejewski & Rafał Weron, 2019. "Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 12(13), pages 1-12, July.
    32. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    33. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    34. 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.
    35. Mira Watermeyer & Thomas Mobius & Oliver Grothe & Felix Musgens, 2023. "A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling," Papers 2304.09336, arXiv.org.
    36. Rodrigo A. de Marcos & Derek W. Bunn & Antonio Bello & Javier Reneses, 2020. "Short-Term Electricity Price Forecasting with Recurrent Regimes and Structural Breaks," Energies, MDPI, vol. 13(20), pages 1-14, October.
    37. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    38. Joanna Janczura & Aleksandra Michalak, 2020. "Optimization of Electric Energy Sales Strategy Based on Probabilistic Forecasts," Energies, MDPI, vol. 13(5), pages 1-16, February.
    39. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    40. Miguel Pinhão & Miguel Fonseca & Ricardo Covas, 2022. "Electricity Spot Price Forecast by Modelling Supply and Demand Curve," Mathematics, MDPI, vol. 10(12), pages 1-20, June.
    41. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
    42. Hakan Acaroğlu & Fausto Pedro García Márquez, 2021. "Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy," Energies, MDPI, vol. 14(22), pages 1-23, November.
    43. Philip Beran & Arne Vogler, 2021. "Multi-Day-Ahead Electricity Price Forecasting: A Comparison of fundamental, econometric and hybrid Models," EWL Working Papers 2102, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2021.

  14. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports HSC/17/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

    Cited by:

    1. Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018. "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports HSC/18/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    2. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    3. Ismail Shah & Hasnain Iftikhar & Sajid Ali & Depeng Wang, 2019. "Short-Term Electricity Demand Forecasting Using Components Estimation Technique," Energies, MDPI, vol. 12(13), pages 1-17, July.
    4. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    5. Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
    6. Rinne, Sonja, 2018. "Radioinactive: Are nuclear power plant outages in France contagious to the German electricity price?," CIW Discussion Papers 3/2018, University of Münster, Center for Interdisciplinary Economics (CIW).
    7. Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018. "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 11(9), pages 1-20, September.
    8. 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.
    9. Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.
    10. Florian Ziel & Rafal Weron, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Papers 1805.06649, arXiv.org.
    11. Christian Giovanelli & Seppo Sierla & Ryutaro Ichise & Valeriy Vyatkin, 2018. "Exploiting Artificial Neural Networks for the Prediction of Ancillary Energy Market Prices," Energies, MDPI, vol. 11(7), pages 1-22, July.

  15. Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2017. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting," HSC Research Reports HSC/17/02, Hugo Steinhaus Center, Wroclaw University of Science and Technology.

    Cited by:

    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Lu, Xin & Qiu, Jing & Lei, Gang & Zhu, Jianguo, 2022. "Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia," Applied Energy, Elsevier, vol. 308(C).
    3. Tomasz Zema & Adam Sulich, 2022. "Models of Electricity Price Forecasting: Bibliometric Research," Energies, MDPI, vol. 15(15), pages 1-18, August.
    4. Guo, Bowei & Newbery, David, 2021. "The cost of uncoupling GB interconnectors," Energy Policy, Elsevier, vol. 158(C).
    5. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    6. Jiang, He & Dong, Yawei & Dong, Yao & Wang, Jianzhou, 2025. "Probabilistic electricity price forecasting by integrating interpretable model," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    7. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    8. Stylianos Loizidis & Georgios Konstantinidis & Spyros Theocharides & Andreas Kyprianou & George E. Georghiou, 2023. "Electricity Day-Ahead Market Conditions and Their Effect on the Different Supervised Algorithms for Market Price Forecasting," Energies, MDPI, vol. 16(12), pages 1-29, June.
    9. Shao, Zhen & Zheng, Qingru & Yang, Shanlin & Gao, Fei & Cheng, Manli & Zhang, Qiang & Liu, Chen, 2020. "Modeling and forecasting the electricity clearing price: A novel BELM based pattern classification framework and a comparative analytic study on multi-layer BELM and LSTM," Energy Economics, Elsevier, vol. 86(C).
    10. Macedo, Daniela Pereira & Marques, António Cardoso & Damette, Olivier, 2020. "The impact of the integration of renewable energy sources in the electricity price formation: is the Merit-Order Effect occurring in Portugal?," Utilities Policy, Elsevier, vol. 66(C).
    11. Maciejowska, Katarzyna & Nitka, Weronika & Weron, Tomasz, 2021. "Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices," Energy Economics, Elsevier, vol. 99(C).
    12. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    13. Ciaran O'Connor & Mohamed Bahloul & Steven Prestwich & Andrea Visentin, 2025. "The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets," Papers 2511.05523, arXiv.org.
    14. Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018. "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports HSC/18/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    15. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    16. Nijolė MAKNICKIENĖ & Jelena STANKEVIČIENĖ & Algirdas MAKNICKAS, 2020. "Comparison of Forex Market Forecasting Tools Based on Evolino Ensemble and Technical Analysis Indicators," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 134-148, September.
    17. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    18. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    19. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    20. Ghelasi, Paul & Ziel, Florian, 2025. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 217(C).
    21. Stephen Haben & Julien Caudron & Jake Verma, 2021. "Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain," Forecasting, MDPI, vol. 3(3), pages 1-37, August.
    22. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    23. Uniejewski, Bartosz, 2025. "Smoothing quantile regression averaging: A new approach to probabilistic forecasting of electricity prices," Journal of Commodity Markets, Elsevier, vol. 39(C).
    24. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    25. Ismail Shah & Hasnain Iftikhar & Sajid Ali & Depeng Wang, 2019. "Short-Term Electricity Demand Forecasting Using Components Estimation Technique," Energies, MDPI, vol. 12(13), pages 1-17, July.
    26. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    27. Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports HSC/17/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    28. Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
    29. Ghimire, Sujan & Deo, Ravinesh C. & Casillas-Pérez, David & Sharma, Ekta & Salcedo-Sanz, Sancho & Barua, Prabal Datta & Rajendra Acharya, U., 2024. "Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach," Applied Energy, Elsevier, vol. 374(C).
    30. Hanus, Luboš & Baruník, Jozef, 2025. "Learning the probability distributions of day-ahead electricity prices," Energy Economics, Elsevier, vol. 152(C).
    31. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Determination of Electricity Demand by Personal Light Electric Vehicles (PLEVs): An Example of e-Motor Scooters in the Context of Large City Management in Poland," Energies, MDPI, vol. 13(1), pages 1-18, January.
    32. Rinne, Sonja, 2018. "Radioinactive: Are nuclear power plant outages in France contagious to the German electricity price?," CIW Discussion Papers 3/2018, University of Münster, Center for Interdisciplinary Economics (CIW).
    33. Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018. "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 11(9), pages 1-20, September.
    34. 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.
    35. Narajewski, Michał & Ziel, Florian, 2022. "Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs," Energy Economics, Elsevier, vol. 110(C).
    36. Lipiecki, Arkadiusz & Uniejewski, Bartosz & Weron, Rafał, 2024. "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Energy Economics, Elsevier, vol. 139(C).
    37. Tomasz Serafin & Bartosz Uniejewski & Rafał Weron, 2019. "Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 12(13), pages 1-12, July.
    38. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).
    39. Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.
    40. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    41. Mira Watermeyer & Thomas Mobius & Oliver Grothe & Felix Musgens, 2023. "A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling," Papers 2304.09336, arXiv.org.
    42. Arne Vogler & Florian Ziel, 2021. "Event-Based Evaluation of Electricity Price Ensemble Forecasts," Forecasting, MDPI, vol. 4(1), pages 1-21, December.
    43. Florian Ziel & Rafal Weron, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Papers 1805.06649, arXiv.org.
    44. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    45. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    46. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
    47. Christian Giovanelli & Seppo Sierla & Ryutaro Ichise & Valeriy Vyatkin, 2018. "Exploiting Artificial Neural Networks for the Prediction of Ancillary Energy Market Prices," Energies, MDPI, vol. 11(7), pages 1-22, July.
    48. Usman Zafar & Neil Kellard & Dmitri Vinogradov, 2022. "Multistage optimization filter for trend‐based short‐term forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 345-360, March.

Articles

  1. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
    See citations under working paper version above.
  2. Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
    See citations under working paper version above.
  3. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    See citations under working paper version above.
  4. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).
    See citations under working paper version above.
  5. Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
    See citations under working paper version above.
  6. Grzegorz Marcjasz, 2020. "Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme," Energies, MDPI, vol. 13(18), pages 1-18, September.

    Cited by:

    1. Sajjad Khan & Shahzad Aslam & Iqra Mustafa & Sheraz Aslam, 2021. "Short-Term Electricity Price Forecasting by Employing Ensemble Empirical Mode Decomposition and Extreme Learning Machine," Forecasting, MDPI, vol. 3(3), pages 1-18, June.
    2. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    3. Behnam Talebjedi & Ali Khosravi & Timo Laukkanen & Henrik Holmberg & Esa Vakkilainen & Sanna Syri, 2020. "Energy Modeling of a Refiner in Thermo-Mechanical Pulping Process Using ANFIS Method," Energies, MDPI, vol. 13(19), pages 1-26, October.
    4. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    5. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    6. Jason Runge & Radu Zmeureanu, 2021. "A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings," Energies, MDPI, vol. 14(3), pages 1-26, January.
    7. Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
    8. Hanus, Luboš & Baruník, Jozef, 2025. "Learning the probability distributions of day-ahead electricity prices," Energy Economics, Elsevier, vol. 152(C).
    9. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu & Athanasios Ioannis Arvanitidis & Lefteri H. Tsoukalas, 2022. "Error Compensation Enhanced Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 15(4), pages 1-21, February.
    10. Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
    11. Lipiecki, Arkadiusz & Uniejewski, Bartosz & Weron, Rafał, 2024. "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Energy Economics, Elsevier, vol. 139(C).
    12. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    13. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).

  7. Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2020. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 466-479.
    See citations under working paper version above.
  8. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
    See citations under working paper version above.
  9. Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1533-1547.
    See citations under working paper version above.
  10. Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.

    Cited by:

    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Tomasz Zema & Adam Sulich, 2022. "Models of Electricity Price Forecasting: Bibliometric Research," Energies, MDPI, vol. 15(15), pages 1-18, August.
    3. Grzegorz Marcjasz, 2020. "Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme," Energies, MDPI, vol. 13(18), pages 1-18, September.
    4. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
    5. Guo, Bowei & Newbery, David, 2021. "The cost of uncoupling GB interconnectors," Energy Policy, Elsevier, vol. 158(C).
    6. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    7. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    8. Abdelrahman E. E. Eltoukhy & Ibrahim Abdelfadeel Shaban & Felix T. S. Chan & Mohammad A. M. Abdel-Aal, 2020. "Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations," IJERPH, MDPI, vol. 17(19), pages 1-25, September.
    9. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
    10. Belenguer, E. & Segarra-Tamarit, J. & Pérez, E. & Vidal-Albalate, R., 2025. "Short-term electricity price forecasting through demand and renewable generation prediction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 229(C), pages 350-361.
    11. Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018. "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports HSC/18/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    12. Behmiri, Niaz Bashiri & Fezzi, Carlo & Ravazzolo, Francesco, 2026. "Renewable sources and short-to-mid-term electricity price forecasting," Journal of Commodity Markets, Elsevier, vol. 41(C).
    13. Wagner, Andreas & Ramentol, Enislay & Schirra, Florian & Michaeli, Hendrik, 2022. "Short- and long-term forecasting of electricity prices using embedding of calendar information in neural networks," Journal of Commodity Markets, Elsevier, vol. 28(C).
    14. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    15. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    16. Ethem Çanakoğlu & Esra Adıyeke, 2020. "Comparison of Electricity Spot Price Modelling and Risk Management Applications," Energies, MDPI, vol. 13(18), pages 1-22, September.
    17. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
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    20. Anshuman Satapathy & Niranjan Nayak & Tanmoy Parida, 2022. "Real-Time Power Quality Enhancement in a Hybrid Micro-Grid Using Nonlinear Autoregressive Neural Network," Energies, MDPI, vol. 15(23), pages 1-35, November.
    21. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
    22. Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting," Energy Economics, Elsevier, vol. 79(C), pages 171-182.
    23. Ismail Shah & Hasnain Iftikhar & Sajid Ali & Depeng Wang, 2019. "Short-Term Electricity Demand Forecasting Using Components Estimation Technique," Energies, MDPI, vol. 12(13), pages 1-17, July.
    24. Yu, Vincent F. & Le, Thi Huynh Anh & Gupta, Jatinder N.D., 2022. "Sustainable microgrid design with multiple demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
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    27. Daniel Manfre Jaimes & Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2023. "A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes," Forecasting, MDPI, vol. 5(3), pages 1-23, July.
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  11. Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting," Energy Economics, Elsevier, vol. 79(C), pages 171-182.
    See citations under working paper version above.
  12. Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Paul R Nail & Katarzyna Sznajd-Weron, 2018. "Think then act or act then think?," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-19, November.

    Cited by:

    1. Galam, Serge, 2023. "Identifying a would-be terrorist: An ineradicable error in the data processing?," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Toth, Gabor & Galam, Serge, 2022. "Deviations from the majority: A local flip model," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    3. Johannes Falk & Edwin Eichler & Katja Windt & Marc-Thorsten Hütt, 2024. "Nucleation transitions in polycontextural networks toward consensus," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(11), pages 1-10, November.

  13. Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018. "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 11(9), pages 1-20, September.
    See citations under working paper version above.
  14. Rafał Apriasz & Tyll Krueger & Grzegorz Marcjasz & Katarzyna Sznajd-Weron, 2016. "The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-19, November.

    Cited by:

    1. Chaitanya S. Gokhale & Joseph Bulbulia & Marcus Frean, 2022. "Collective narratives catalyse cooperation," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    2. Shang, Lihui & Zhao, Mingming & Ai, Jun & Su, Zhan, 2021. "Opinion evolution in the Sznajd model on interdependent chains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

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