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Florentina Paraschiv

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Hagfors, Lars Ivar & Kamperud , Hilde Horthe & Paraschiv, Florentina & Prokopczuk, Marcel & Sator, Alma & Westgaard, Sjur, 2016. "Prediction of Extreme Price Occurrences in the German Day-ahead Electricity Market," Working Papers on Finance 1622, University of St. Gallen, School of Finance.

    Cited by:

    1. Guo, Bowei & Newbery, David, 2021. "The cost of uncoupling GB interconnectors," Energy Policy, Elsevier, vol. 158(C).
    2. Hinderks, W.J. & Wagner, A., 2019. "Pricing German Energiewende products: Intraday cap/floor futures," Energy Economics, Elsevier, vol. 81(C), pages 287-296.
    3. Maciejowska, Katarzyna, 2020. "Assessing the impact of renewable energy sources on the electricity price level and variability – A quantile regression approach," Energy Economics, Elsevier, vol. 85(C).
    4. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
    5. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
    6. 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.
    7. Bartosz Uniejewski & Rafal Weron, 2018. "Efficient forecasting of electricity spot prices with expert and LASSO models," HSC Research Reports HSC/18/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    8. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(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. Ritmeester, Tim & Meyer-Ortmanns, Hildegard, 2021. "Minority games played by arbitrageurs on the energy market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    11. Liu, Luyao & Bai, Feifei & Su, Chenyu & Ma, Cuiping & Yan, Ruifeng & Li, Hailong & Sun, Qie & Wennersten, Ronald, 2022. "Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model," Energy, Elsevier, vol. 247(C).
    12. Peña, Juan Ignacio & Rodríguez, Rosa & Mayoral, Silvia, 2020. "Tail risk of electricity futures," Energy Economics, Elsevier, vol. 91(C).
    13. Florentina Paraschiv & Dima Mohamad, 2020. "The Nuclear Power Dilemma—Between Perception and Reality," Energies, MDPI, vol. 13(22), pages 1-19, November.
    14. Huisman, Ronald & Stet, Cristian, 2022. "The dependence of quantile power prices on supply from renewables," Energy Economics, Elsevier, vol. 105(C).
    15. Attila Bai & Péter Balogh & Adrián Nagy & Zoltán Csedő & Botond Sinóros-Szabó & Gábor Pintér & Sanjeev Kumar Prajapati & Amit Singh & Zoltán Gabnai, 2023. "Economic Evaluation of a 1 MW el Capacity Power-to-Biomethane System," Energies, MDPI, vol. 16(24), pages 1-27, December.
    16. 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.
    17. Nikkinen, Jussi & Rothovius, Timo, 2019. "Market specific seasonal trading behavior in NASDAQ OMX electricity options," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 16-29.
    18. Tselika, Kyriaki, 2022. "The impact of variable renewables on the distribution of hourly electricity prices and their variability: A panel approach," Energy Economics, Elsevier, vol. 113(C).
    19. Mayer, Klaus & Trück, Stefan, 2018. "Electricity markets around the world," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 77-100.
    20. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    21. Gaudard, Ludovic & Avanzi, Francesco & De Michele, Carlo, 2018. "Seasonal aspects of the energy-water nexus: The case of a run-of-the-river hydropower plant," Applied Energy, Elsevier, vol. 210(C), pages 604-612.
    22. Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
    23. Jens Baetens & Jeroen D. M. De Kooning & Greet Van Eetvelde & Lieven Vandevelde, 2020. "A Two-Stage Stochastic Optimisation Methodology for the Operation of a Chlor-Alkali Electrolyser under Variable DAM and FCR Market Prices," Energies, MDPI, vol. 13(21), pages 1-19, October.
    24. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  2. Paraschiv, Florentina & Bunn, Derek & Westgaard, Sjur, 2016. "Estimation and Application of Fully Parametric Multifactor Quantile Regression with Dynamic Coefficients," Working Papers on Finance 1607, University of St. Gallen, School of Finance.

    Cited by:

    1. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    2. Georg Wolff & Stefan Feuerriegel, 2019. "Emissions Trading System of the European Union: Emission Allowances and EPEX Electricity Prices in Phase III," Energies, MDPI, vol. 12(15), pages 1-15, July.
    3. Li, Wei & Paraschiv, Florentina, 2022. "Modelling the evolution of wind and solar power infeed forecasts," Journal of Commodity Markets, Elsevier, vol. 25(C).
    4. Florentina Paraschiv & Dima Mohamad, 2020. "The Nuclear Power Dilemma—Between Perception and Reality," Energies, MDPI, vol. 13(22), pages 1-19, November.
    5. Westgaard, Sjur & Fleten, Stein-Erik & Negash, Ahlmahz & Botterud, Audun & Bogaard, Katinka & Verling, Trude Haugsvaer, 2021. "Performing price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity market," Energy, Elsevier, vol. 214(C).
    6. Rüdiger Kiesel & Florentina Paraschiv & Audun Sætherø, 2019. "On the construction of hourly price forward curves for electricity prices," Computational Management Science, Springer, vol. 16(1), pages 345-369, February.
    7. Sapio, Alessandro, 2019. "Greener, more integrated, and less volatile? A quantile regression analysis of Italian wholesale electricity prices," Energy Policy, Elsevier, vol. 126(C), pages 452-469.
    8. Peter Leoni & Pieter Segaert & Sven Serneels & Tim Verdonck, 2018. "Multivariate constrained robust M‐regression for shaping forward curves in electricity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1391-1406, November.
    9. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  3. Kiesel, Ruediger & Paraschiv, Florentina, 2015. "Econometric Analysis of 15-minute Intraday Electricity Prices," Working Papers on Finance 1521, University of St. Gallen, School of Finance.

    Cited by:

    1. Piccirilli, Marco & Schmeck, Maren Diane & Vargiolu, Tiziano, 2019. "Capturing the power options smile by an additive two-factor model for overlapping futures prices," Center for Mathematical Economics Working Papers 625, Center for Mathematical Economics, Bielefeld University.
    2. Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
    3. Kramer, Anke & Kiesel, Rüdiger, 2021. "Exogenous factors for order arrivals on the intraday electricity market," Energy Economics, Elsevier, vol. 97(C).
    4. Renato Fernandes & Isabel Soares, 2022. "Reviewing Explanatory Methodologies of Electricity Markets: An Application to the Iberian Market," Energies, MDPI, vol. 15(14), pages 1-17, July.
    5. Ren'e Aid & Andrea Cosso & Huy^en Pham, 2020. "Equilibrium price in intraday electricity markets," Papers 2010.09285, arXiv.org.
    6. 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).
    7. Jan Niklas Buescher & Daria Gottwald & Florian Momm & Alexander Zureck, 2022. "Impact of the COVID-19 Pandemic Crisis on the Efficiency of European Intraday Electricity Markets," Energies, MDPI, vol. 15(10), pages 1-21, May.
    8. Karl Frauendorfer & Florentina Paraschiv & Michael Schürle, 2018. "Cross-Border Effects on Swiss Electricity Prices in the Light of the Energy Transition," Energies, MDPI, vol. 11(9), pages 1-30, August.
    9. Katarzyna Maciejowska, 2022. "A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets," Papers 2205.00975, arXiv.org.
    10. Latini, Luca & Piccirilli, Marco & Vargiolu, Tiziano, 2019. "Mean-reverting no-arbitrage additive models for forward curves in energy markets," Energy Economics, Elsevier, vol. 79(C), pages 157-170.
    11. Micha{l} Narajewski & Florian Ziel, 2021. "Optimal bidding in hourly and quarter-hourly electricity price auctions: trading large volumes of power with market impact and transaction costs," Papers 2104.14204, arXiv.org, revised Feb 2022.
    12. Cassandra Milbradt & Dorte Kreher, 2022. "A cross-border market model with limited transmission capacities," Papers 2207.01939, arXiv.org, revised May 2023.
    13. Facchini, Angelo & Rubino, Alessandro & Caldarelli, Guido & Di Liddo, Giuseppe, 2019. "Changes to Gate Closure and its impact on wholesale electricity prices: The case of the UK," Energy Policy, Elsevier, vol. 125(C), pages 110-121.
    14. Benjamin Favetto, 2019. "The European intraday electricity market : a modeling based on the Hawkes process," Working Papers hal-02089289, HAL.
    15. Knaut, Andreas & Paschmann, Martin, 2017. "Price Volatility in Commodity Markets with Restricted Participation," EWI Working Papers 2017-2, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    16. Thomas Deschatre & Xavier Warin, 2023. "A Common Shock Model for multidimensional electricity intraday price modelling with application to battery valuation," Papers 2307.16619, arXiv.org.
    17. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
    18. 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.
    19. Christopher Kath & Florian Ziel, 2020. "Optimal Order Execution in Intraday Markets: Minimizing Costs in Trade Trajectories," Papers 2009.07892, arXiv.org, revised Oct 2020.
    20. Keles, Dogan & Dehler-Holland, Joris & Densing, Martin & Panos, Evangelos & Hack, Felix, 2020. "Cross-border effects in interconnected electricity markets - an analysis of the Swiss electricity prices," Energy Economics, Elsevier, vol. 90(C).
    21. van Leeuwen, Charlotte & Mulder, Machiel, 2018. "Power-to-gas in electricity markets dominated by renewables," Applied Energy, Elsevier, vol. 232(C), pages 258-272.
    22. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    23. Jérôme Collet & Olivier Féron & Peter Tankov, 2017. "Optimal management of a wind power plant with storage capacity," Working Papers 2017-87, Center for Research in Economics and Statistics.
    24. 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.
    25. Sergei Kulakov, 2020. "X-Model: Further Development and Possible Modifications," Forecasting, MDPI, vol. 2(1), pages 1-16, February.
    26. Marco Piccirilli & Tiziano Vargiolu, 2018. "Optimal Portfolio in Intraday Electricity Markets Modelled by L\'evy-Ornstein-Uhlenbeck Processes," Papers 1807.01979, arXiv.org.
    27. Chen Wang & Kaile Zhou & Lanlan Li & Shanlin Yang, 2018. "Multi-agent simulation-based residential electricity pricing schemes design and user selection decision-making," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(3), pages 1309-1327, February.
    28. 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.
    29. Koch, Christopher & Hirth, Lion, 2019. "Short-term electricity trading for system balancing: An empirical analysis of the role of intraday trading in balancing Germany's electricity system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    30. Li, Wei & Paraschiv, Florentina, 2022. "Modelling the evolution of wind and solar power infeed forecasts," Journal of Commodity Markets, Elsevier, vol. 25(C).
    31. Karel Janda & Michaela Koscova, 2018. "Photovoltaics and the Slovak Electricity Market," Working Papers IES 2018/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2018.
    32. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    33. Christopher Kath, 2019. "Modeling Intraday Markets under the New Advances of the Cross-Border Intraday Project (XBID): Evidence from the German Intraday Market," Energies, MDPI, vol. 12(22), pages 1-35, November.
    34. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    35. 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.
    36. Giorgia Callegaro & Andrea Mazzoran & Carlo Sgarra, 2019. "A Self-Exciting Modelling Framework for Forward Prices in Power Markets," Papers 1910.13286, arXiv.org.
    37. 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).
    38. Thomas Deschatre & Pierre Gruet, 2021. "Electricity intraday price modeling with marked Hawkes processes," Papers 2103.07407, arXiv.org, revised Mar 2021.
    39. Spodniak, Petr & Ollikka, Kimmo & Honkapuro, Samuli, 2019. "The Relevance of Wholesale Electricity Market Places: The Nordic Case," Working Papers 126, VATT Institute for Economic Research.
    40. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Contract durations in the electricity market: Causal impact of 15min trading on the EPEX SPOT market," Energy Economics, Elsevier, vol. 69(C), pages 367-378.
    41. 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 Technology.
    42. 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.
    43. 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).
    44. Le, Hong Lam & Ilea, Valentin & Bovo, Cristian, 2019. "Integrated European intra-day electricity market: Rules, modeling and analysis," Applied Energy, Elsevier, vol. 238(C), pages 258-273.
    45. Rüdiger Kiesel & Florentina Paraschiv & Audun Sætherø, 2019. "On the construction of hourly price forward curves for electricity prices," Computational Management Science, Springer, vol. 16(1), pages 345-369, February.
    46. Ilkay Oksuz & Umut Ugurlu, 2019. "Neural Network Based Model Comparison for Intraday Electricity Price Forecasting," Energies, MDPI, vol. 12(23), pages 1-14, November.
    47. Joanna Janczura & Aleksandra Michalak, 2020. "Optimization of Electric Energy Sales Strategy Based on Probabilistic Forecasts," Energies, MDPI, vol. 13(5), pages 1-16, February.
    48. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    49. 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).
    50. Hagfors, Lars Ivar & Kamperud , Hilde Horthe & Paraschiv, Florentina & Prokopczuk, Marcel & Sator, Alma & Westgaard, Sjur, 2016. "Prediction of Extreme Price Occurrences in the German Day-ahead Electricity Market," Working Papers on Finance 1622, University of St. Gallen, School of Finance.
    51. 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.
    52. Ocker, Fabian & Jaenisch, Vincent, 2020. "The way towards European electricity intraday auctions – Status quo and future developments," Energy Policy, Elsevier, vol. 145(C).
    53. 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).
    54. Riccardo Brignone & Carlo Sgarra, 2020. "Asian options pricing in Hawkes-type jump-diffusion models," Annals of Finance, Springer, vol. 16(1), pages 101-119, March.
    55. Croonenbroeck, Carsten & Hüttel, Silke, 2017. "Quantifying the economic efficiency impact of inaccurate renewable energy price forecasts," Energy, Elsevier, vol. 134(C), pages 767-774.
    56. Nikkinen, Jussi & Rothovius, Timo, 2019. "Market specific seasonal trading behavior in NASDAQ OMX electricity options," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 16-29.
    57. Thomas Kuppelwieser & David Wozabal, 2023. "Intraday power trading: toward an arms race in weather forecasting?," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 57-83, March.
    58. 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.
    59. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    60. Olivier Féron & Peter Tankov & Laura Tinsi, 2020. "Price Formation and Optimal Trading in Intraday Electricity Markets with a Major Player," Risks, MDPI, vol. 8(4), pages 1-21, December.
    61. 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.
    62. Fred Espen Benth & Marco Piccirilli & Tiziano Vargiolu, 2017. "Additive energy forward curves in a Heath-Jarrow-Morton framework," Papers 1709.03310, arXiv.org, revised Jun 2018.
    63. Christopher Koch & Philipp Maskos, 2020. "Passive Balancing Through Intraday Trading: Whether Interactions Between Short-term Trading and Balancing Stabilize Germany s Electricity System," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 101-112.
    64. Jérôme Collet & Olivier Féron & Peter Tankov, 2017. "Optimal management of a wind power plant with storage capacity," Working Papers hal-01627593, HAL.
    65. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    66. Huisman, Ronald & Koolen, Derck & Stet, Cristian, 2021. "Pricing forward contracts in power markets with variable renewable energy sources," Renewable Energy, Elsevier, vol. 180(C), pages 1260-1265.
    67. 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 Technology.
    68. 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.
    69. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    70. Kath, Christopher & Ziel, Florian, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Energy Economics, Elsevier, vol. 76(C), pages 411-423.
    71. 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 Technology.
    72. Olivier F'eron & Peter Tankov & Laura Tinsi, 2020. "Price formation and optimal trading in intraday electricity markets," Papers 2009.04786, arXiv.org, revised Jun 2021.
    73. 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.
    74. Gürtler, Marc & Paulsen, Thomas, 2018. "The effect of wind and solar power forecasts on day-ahead and intraday electricity prices in Germany," Energy Economics, Elsevier, vol. 75(C), pages 150-162.
    75. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    76. Janda, Karel, 2018. "Slovak electricity market and the price merit order effect of photovoltaics," Energy Policy, Elsevier, vol. 122(C), pages 551-562.
    77. Micha{l} Narajewski & Florian Ziel, 2018. "Econometric modelling and forecasting of intraday electricity prices," Papers 1812.09081, arXiv.org, revised Sep 2019.
    78. Knaut, Andreas & Paschmann, Martin, 2019. "Price volatility in commodity markets with restricted participation," Energy Economics, Elsevier, vol. 81(C), pages 37-51.
    79. Obermüller, Frank, 2017. "Explaining Electricity Forward Premiums - Evidence for the Weather Uncertainty Effect," EWI Working Papers 2017-10, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    80. 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).
    81. Peter Tankov & Laura Tinsi, 2021. "Decision making with dynamic probabilistic forecasts," Papers 2106.16047, arXiv.org.
    82. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    83. Olivier F'eron & Peter Tankov & Laura Tinsi, 2020. "Price formation and optimal trading in intraday electricity markets with a major player," Papers 2011.07655, arXiv.org.
    84. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).

  4. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.

    Cited by:

    1. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.

  5. Paraschiv, Florentina, 2013. "Price Dynamics in Electricity Markets," Working Papers on Finance 1314, University of St. Gallen, School of Finance.

    Cited by:

    1. Karl Frauendorfer & Florentina Paraschiv & Michael Schürle, 2018. "Cross-Border Effects on Swiss Electricity Prices in the Light of the Energy Transition," Energies, MDPI, vol. 11(9), pages 1-30, August.
    2. Pircalabu, A. & Benth, F.E., 2017. "A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets," Energy Economics, Elsevier, vol. 68(C), pages 283-302.
    3. Morales, Lucía & Hanly, Jim, 2018. "European power markets–A journey towards efficiency," Energy Policy, Elsevier, vol. 116(C), pages 78-85.
    4. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    5. Giorgia Callegaro & Andrea Mazzoran & Carlo Sgarra, 2019. "A Self-Exciting Modelling Framework for Forward Prices in Power Markets," Papers 1910.13286, arXiv.org.
    6. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
    7. Benth, Fred Espen & Paraschiv, Florentina, 2018. "A space-time random field model for electricity forward prices," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 203-216.
    8. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
    9. Amal Abdel Razzac & Linda Salahaldin & Salah Eddine Elayoubi & Yezekael Hayel & Tijani Chahed, 2017. "A Game Theoretical Real Options Framework for Investment Decisions in Mobile TV Infrastructure," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-34, August.
    10. Keles, Dogan & Scelle, Jonathan & Paraschiv, Florentina & Fichtner, Wolf, 2016. "Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks," Applied Energy, Elsevier, vol. 162(C), pages 218-230.
    11. Mangirdas Morkunas & Gintaras Cernius & Gintare Giriuniene, 2019. "Assessing Business Risks of Natural Gas Trading Companies: Evidence from GET Baltic," Energies, MDPI, vol. 12(14), pages 1-14, July.

  6. Stein-Erik, Fleten & Paraschiv, Florentina & Schürle, Michel, 2013. "Spot-forward Model for Electricity Prices," Working Papers on Finance 1311, University of St. Gallen, School of Finance.

    Cited by:

    1. Erdogdu, Erkan, 2016. "Asymmetric volatility in European day-ahead power markets: A comparative microeconomic analysis," Energy Economics, Elsevier, vol. 56(C), pages 398-409.
    2. Florian Ziel, 2015. "Forecasting Electricity Spot Prices using Lasso: On Capturing the Autoregressive Intraday Structure," Papers 1509.01966, arXiv.org, revised Jan 2016.
    3. Kiesel, Rüdiger & Paraschiv, Florentina, 2017. "Econometric analysis of 15-minute intraday electricity prices," Energy Economics, Elsevier, vol. 64(C), pages 77-90.

  7. Paraschiv, Florentina & Qin, Minzi, 2013. "Extreme Spillover Between Shadow Banking and Regular Banking," Working Papers on Finance 1312, University of St. Gallen, School of Finance.

    Cited by:

    1. Chen, Ting-Hsuan & Lee, Chien-Chiang, 2020. "Spatial analysis of liquidity risk in China," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

  8. Kovacevic, Raimund M. & Paraschiv, Florentina, 2012. "Medium-term Planning for Thermal Electricity Production," Working Papers on Finance 1220, University of St. Gallen, School of Finance.

    Cited by:

    1. Karl Frauendorfer & Florentina Paraschiv & Michael Schürle, 2018. "Cross-Border Effects on Swiss Electricity Prices in the Light of the Energy Transition," Energies, MDPI, vol. 11(9), pages 1-30, August.
    2. Kovacevic, Raimund M. & Pflug, Georg Ch., 2014. "Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches," European Journal of Operational Research, Elsevier, vol. 237(2), pages 389-403.
    3. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
    4. Paraschiv, Florentina & Fleten, Stein-Erik & Schürle, Michael, 2015. "A spot-forward model for electricity prices with regime shifts," Energy Economics, Elsevier, vol. 47(C), pages 142-153.
    5. Hagfors, Lars Ivar & Kamperud , Hilde Horthe & Paraschiv, Florentina & Prokopczuk, Marcel & Sator, Alma & Westgaard, Sjur, 2016. "Prediction of Extreme Price Occurrences in the German Day-ahead Electricity Market," Working Papers on Finance 1622, University of St. Gallen, School of Finance.
    6. Raimund M. Kovacevic, 2019. "Valuation and pricing of electricity delivery contracts: the producer’s view," Annals of Operations Research, Springer, vol. 275(2), pages 421-460, April.
    7. Andreas Welling, 2017. "Green Finance: Recent developments, characteristics and important actors," FEMM Working Papers 170002, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    8. Hannes Schwarz & Valentin Bertsch & Wolf Fichtner, 2018. "Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 265-310, January.

  9. Paraschiv, Florentina, 2012. "Adjustment Policy of Deposit Rates in the Case of Swiss non-Maturing Savings Accounts," Working Papers on Finance 1219, University of St. Gallen, School of Finance.

    Cited by:

    1. Kiesel, Rüdiger & Paraschiv, Florentina, 2017. "Econometric analysis of 15-minute intraday electricity prices," Energy Economics, Elsevier, vol. 64(C), pages 77-90.

Articles

  1. Kiesel, Rüdiger & Paraschiv, Florentina, 2017. "Econometric analysis of 15-minute intraday electricity prices," Energy Economics, Elsevier, vol. 64(C), pages 77-90.
    See citations under working paper version above.
  2. Lars Ivar Hagfors & Hilde Hørthe Kamperud & Florentina Paraschiv & Marcel Prokopczuk & Alma Sator & Sjur Westgaard, 2016. "Prediction of extreme price occurrences in the German day-ahead electricity market," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1929-1948, December.
    See citations under working paper version above.
  3. Keles, Dogan & Scelle, Jonathan & Paraschiv, Florentina & Fichtner, Wolf, 2016. "Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks," Applied Energy, Elsevier, vol. 162(C), pages 218-230.

    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. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2016. "Day-ahead electricity price forecasting via the application of artificial neural network based models," Applied Energy, Elsevier, vol. 172(C), pages 132-151.
    3. Guo, Bowei & Newbery, David, 2021. "The cost of uncoupling GB interconnectors," Energy Policy, Elsevier, vol. 158(C).
    4. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    5. Lago, Jesus & De Ridder, Fjo & Vrancx, Peter & De Schutter, Bart, 2018. "Forecasting day-ahead electricity prices in Europe: The importance of considering market integration," Applied Energy, Elsevier, vol. 211(C), pages 890-903.
    6. Fanelli, Viviana & Maddalena, Lucia & Musti, Silvana, 2016. "Modelling electricity futures prices using seasonal path-dependent volatility," Applied Energy, Elsevier, vol. 173(C), pages 92-102.
    7. 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).
    8. Ding, Zhikun & Chen, Weilin & Hu, Ting & Xu, Xiaoxiao, 2021. "Evolutionary double attention-based long short-term memory model for building energy prediction: Case study of a green building," Applied Energy, Elsevier, vol. 288(C).
    9. Jesus Lago & Fjo De Ridder & Peter Vrancx & Bart De Schutter, 2017. "Forecasting day-ahead electricity prices in Europe: the importance of considering market integration," Papers 1708.07061, arXiv.org, revised Dec 2017.
    10. Kempitiya, Thimal & Sierla, Seppo & De Silva, Daswin & Yli-Ojanperä, Matti & Alahakoon, Damminda & Vyatkin, Valeriy, 2020. "An Artificial Intelligence framework for bidding optimization with uncertainty in multiple frequency reserve markets," Applied Energy, Elsevier, vol. 280(C).
    11. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    12. Agustín A. Sánchez de la Nieta & Virginia González & Javier Contreras, 2016. "Portfolio Decision of Short-Term Electricity Forecasted Prices through Stochastic Programming," Energies, MDPI, vol. 9(12), pages 1-19, December.
    13. Heydari, Azim & Majidi Nezhad, Meysam & Pirshayan, Elmira & Astiaso Garcia, Davide & Keynia, Farshid & De Santoli, Livio, 2020. "Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm," Applied Energy, Elsevier, vol. 277(C).
    14. Wang, Bin & Wang, Jun, 2021. "Energy futures price prediction and evaluation model with deep bidirectional gated recurrent unit neural network and RIF-based algorithm," Energy, Elsevier, vol. 216(C).
    15. Miguel A. Jaramillo-Morán & Agustín García-García, 2019. "Applying Artificial Neural Networks to Forecast European Union Allowance Prices: The Effect of Information from Pollutant-Related Sectors," Energies, MDPI, vol. 12(23), pages 1-18, November.
    16. Jasiński, Tomasz, 2019. "Modeling electricity consumption using nighttime light images and artificial neural networks," Energy, Elsevier, vol. 179(C), pages 831-842.
    17. Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
    18. Simon Pezzutto & Gianluca Grilli & Stefano Zambotti & Stefan Dunjic, 2018. "Forecasting Electricity Market Price for End Users in EU28 until 2020—Main Factors of Influence," Energies, MDPI, vol. 11(6), pages 1-18, June.
    19. Bartosz Uniejewski & Jakub Nowotarski & Rafał Weron, 2016. "Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 9(8), pages 1-22, August.
    20. 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 Technology.
    21. 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.
    22. 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.
    23. Hasan Murat Ertuğrul & Mustafa Tevfik Kartal & Serpil Kılıç Depren & Uğur Soytaş, 2022. "Determinants of Electricity Prices in Turkey: An Application of Machine Learning and Time Series Models," Energies, MDPI, vol. 15(20), pages 1-17, October.
    24. Shahzad Aslam & Nasir Ayub & Umer Farooq & Muhammad Junaid Alvi & Fahad R. Albogamy & Gul Rukh & Syed Irtaza Haider & Ahmad Taher Azar & Rasool Bukhsh, 2021. "Towards Electric Price and Load Forecasting Using CNN-Based Ensembler in Smart Grid," Sustainability, MDPI, vol. 13(22), pages 1-28, November.
    25. Bartosz Uniejewski & Rafal Weron, 2018. "Efficient forecasting of electricity spot prices with expert and LASSO models," HSC Research Reports HSC/18/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    26. Luo, Shuman & Weng, Yang, 2019. "A two-stage supervised learning approach for electricity price forecasting by leveraging different data sources," Applied Energy, Elsevier, vol. 242(C), pages 1497-1512.
    27. Léonard Tschora & Erwan Pierre & Marc Plantevit & Céline Robardet, 2022. "Electricity price forecasting on the day-ahead market using machine learning," Post-Print hal-03621974, HAL.
    28. Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    29. Heilmann, Erik, 2023. "The impact of transparency policies on local flexibility markets in electric distribution networks," Utilities Policy, Elsevier, vol. 83(C).
    30. 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).
    31. Lee, Juyong & Cho, Youngsang, 2022. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Energy, Elsevier, vol. 239(PD).
    32. Baruník, Jozef & Malinská, Barbora, 2016. "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, vol. 164(C), pages 366-379.
    33. Umut Ugurlu & Ilkay Oksuz & Oktay Tas, 2018. "Electricity Price Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 11(5), pages 1-23, May.
    34. 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.
    35. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    36. Alexandre Lucas & Konstantinos Pegios & Evangelos Kotsakis & Dan Clarke, 2020. "Price Forecasting for the Balancing Energy Market Using Machine-Learning Regression," Energies, MDPI, vol. 13(20), pages 1-16, October.
    37. Liu, Weiping & Wang, Chengzhu & Li, Yonggang & Liu, Yishun & Huang, Keke, 2021. "Ensemble forecasting for product futures prices using variational mode decomposition and artificial neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    38. Miguel A. Jaramillo-Morán & Daniel Fernández-Martínez & Agustín García-García & Diego Carmona-Fernández, 2021. "Improving Artificial Intelligence Forecasting Models Performance with Data Preprocessing: European Union Allowance Prices Case Study," Energies, MDPI, vol. 14(23), pages 1-23, November.
    39. Bekiroglu, Korkut & Duru, Okan & Gulay, Emrah & Su, Rong & Lagoa, Constantino, 2018. "Predictive analytics of crude oil prices by utilizing the intelligent model search engine," Applied Energy, Elsevier, vol. 228(C), pages 2387-2397.
    40. Dedinec, Aleksandra & Filiposka, Sonja & Dedinec, Aleksandar & Kocarev, Ljupco, 2016. "Deep belief network based electricity load forecasting: An analysis of Macedonian case," Energy, Elsevier, vol. 115(P3), pages 1688-1700.
    41. 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.
    42. Chen, Ying & Chua, Wee Song & Koch, Thorsten, 2018. "Forecasting day-ahead high-resolution natural-gas demand and supply in Germany," Applied Energy, Elsevier, vol. 228(C), pages 1091-1110.
    43. Crespo-Vazquez, Jose L. & Carrillo, C. & Diaz-Dorado, E. & Martinez-Lorenzo, Jose A. & Noor-E-Alam, Md., 2018. "A machine learning based stochastic optimization framework for a wind and storage power plant participating in energy pool market," Applied Energy, Elsevier, vol. 232(C), pages 341-357.
    44. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
    45. Chen, Ying & Xu, Xiuqin & Koch, Thorsten, 2020. "Day-ahead high-resolution forecasting of natural gas demand and supply in Germany with a hybrid model," Applied Energy, Elsevier, vol. 262(C).
    46. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    47. Kılıç Depren, Serpil & Kartal, Mustafa Tevfik & Ertuğrul, Hasan Murat & Depren, Özer, 2022. "The role of data frequency and method selection in electricity price estimation: Comparative evidence from Turkey in pre-pandemic and pandemic periods," Renewable Energy, Elsevier, vol. 186(C), pages 217-225.
    48. Şahin, Utkucan & Ballı, Serkan & Chen, Yan, 2021. "Forecasting seasonal electricity generation in European countries under Covid-19-induced lockdown using fractional grey prediction models and machine learning methods," Applied Energy, Elsevier, vol. 302(C).
    49. 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.
    50. Brusaferri, Alessandro & Matteucci, Matteo & Portolani, Pietro & Vitali, Andrea, 2019. "Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices," Applied Energy, Elsevier, vol. 250(C), pages 1158-1175.
    51. Umut Ugurlu & Oktay Tas & Aycan Kaya & Ilkay Oksuz, 2018. "The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company," Energies, MDPI, vol. 11(8), pages 1-19, August.
    52. Bilin Shao & Yichuan Yan & Huibin Zeng, 2022. "VMD-WSLSTM Load Prediction Model Based on Shapley Values," Energies, MDPI, vol. 15(2), pages 1-18, January.
    53. Xuejiao Ma & Dandan Liu, 2016. "Comparative Study of Hybrid Models Based on a Series of Optimization Algorithms and Their Application in Energy System Forecasting," Energies, MDPI, vol. 9(8), pages 1-34, August.
    54. 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).
    55. Lu, Renzhi & Bai, Ruichang & Huang, Yuan & Li, Yuting & Jiang, Junhui & Ding, Yuemin, 2021. "Data-driven real-time price-based demand response for industrial facilities energy management," Applied Energy, Elsevier, vol. 283(C).
    56. 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.
    57. Jakub Nowotarski & Rafal Weron, 2016. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting," HSC Research Reports HSC/16/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    58. 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 Technology.
    59. 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.
    60. Lu, Renzhi & Hong, Seung Ho, 2019. "Incentive-based demand response for smart grid with reinforcement learning and deep neural network," Applied Energy, Elsevier, vol. 236(C), pages 937-949.
    61. Avci, Ezgi & Ketter, Wolfgang & van Heck, Eric, 2018. "Managing electricity price modeling risk via ensemble forecasting: The case of Turkey," Energy Policy, Elsevier, vol. 123(C), pages 390-403.
    62. Zeng, Sheng & Su, Bin & Zhang, Minglong & Gao, Yuan & Liu, Jun & Luo, Song & Tao, Qingmei, 2021. "Analysis and forecast of China's energy consumption structure," Energy Policy, Elsevier, vol. 159(C).
    63. Emil Kraft & Dogan Keles & Wolf Fichtner, 2020. "Modeling of frequency containment reserve prices with econometrics and artificial intelligence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1179-1197, December.
    64. Jiseong Noh & Hyun-Ji Park & Jong Soo Kim & Seung-June Hwang, 2020. "Gated Recurrent Unit with Genetic Algorithm for Product Demand Forecasting in Supply Chain Management," Mathematics, MDPI, vol. 8(4), pages 1-14, April.
    65. Leerbeck, Kenneth & Bacher, Peder & Junker, Rune Grønborg & Goranović, Goran & Corradi, Olivier & Ebrahimy, Razgar & Tveit, Anna & Madsen, Henrik, 2020. "Short-term forecasting of CO2 emission intensity in power grids by machine learning," Applied Energy, Elsevier, vol. 277(C).
    66. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Prediction and explanation of the formation of the Spanish day-ahead electricity price through machine learning regression," Applied Energy, Elsevier, vol. 239(C), pages 610-625.
    67. Akarsh Kainth & Ranik Raaen Wahlstrøm, 2021. "Do IFRS Promote Transparency? Evidence from the Bankruptcy Prediction of Privately Held Swedish and Norwegian Companies," JRFM, MDPI, vol. 14(3), pages 1-15, March.
    68. Elmore, Clay T. & Dowling, Alexander W., 2021. "Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition," Energy, Elsevier, vol. 232(C).
    69. Qiao, Weibiao & Yang, Zhe, 2020. "Forecast the electricity price of U.S. using a wavelet transform-based hybrid model," Energy, Elsevier, vol. 193(C).
    70. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    71. Chuntian Cheng & Bin Luo & Shumin Miao & Xinyu Wu, 2016. "Mid-Term Electricity Market Clearing Price Forecasting with Sparse Data: A Case in Newly-Reformed Yunnan Electricity Market," Energies, MDPI, vol. 9(10), pages 1-22, October.
    72. Zhou, Wenhao & Li, Hailin & Zhang, Zhiwei, 2022. "A novel seasonal fractional grey model for predicting electricity demand: A case study of Zhejiang in China," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 200(C), pages 128-147.
    73. Simon Schnurch & Andreas Wagner, 2019. "Machine Learning on EPEX Order Books: Insights and Forecasts," Papers 1906.06248, arXiv.org, revised Sep 2019.
    74. 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 Technology.
    75. Gersema, Gerke & Wozabal, David, 2018. "Risk-optimized pooling of intermittent renewable energy sources," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 217-230.
    76. 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.
    77. Jasiński, Tomasz, 2020. "Use of new variables based on air temperature for forecasting day-ahead spot electricity prices using deep neural networks: A new approach," Energy, Elsevier, vol. 213(C).
    78. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Technology.
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  4. Paraschiv, Florentina & Fleten, Stein-Erik & Schürle, Michael, 2015. "A spot-forward model for electricity prices with regime shifts," Energy Economics, Elsevier, vol. 47(C), pages 142-153.

    Cited by:

    1. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    2. Stein-Erik Fleten & Ronald Huisman & Mehtap Kilic & Enrico Pennings & Sjur Westgaard, 2014. "Electricity futures prices: time varying sensitivity to fundamentals," Working Papers 2014/21, Institut d'Economia de Barcelona (IEB).
    3. Berk, K. & Hoffmann, A. & Müller, A., 2018. "Probabilistic forecasting of industrial electricity load with regime switching behavior," International Journal of Forecasting, Elsevier, vol. 34(2), pages 147-162.
    4. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    5. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
    6. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
    7. Bartosz Uniejewski & Jakub Nowotarski & Rafał Weron, 2016. "Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 9(8), pages 1-22, August.
    8. Ida Bakke & Stein-Erik Fleten & Lars Ivar Hagfors & Verena Hagspiel & Beate Norheim & Sonja Wogrin, 2016. "Investment in electric energy storage under uncertainty: a real options approach," Computational Management Science, Springer, vol. 13(3), pages 483-500, July.
    9. Erdogdu, Erkan, 2016. "Asymmetric volatility in European day-ahead power markets: A comparative microeconomic analysis," Energy Economics, Elsevier, vol. 56(C), pages 398-409.
    10. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    11. Hörnlein, Lena, 2019. "The value of gas-fired power plants in markets with high shares of renewable energy," Energy Economics, Elsevier, vol. 81(C), pages 1078-1098.
    12. Benth, Fred Espen & Paraschiv, Florentina, 2018. "A space-time random field model for electricity forward prices," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 203-216.
    13. Carlo Mari & Emiliano Mari, 2021. "Gaussian clustering and jump-diffusion models of electricity prices: a deep learning analysis," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1039-1062, December.
    14. Rüdiger Kiesel & Florentina Paraschiv & Audun Sætherø, 2019. "On the construction of hourly price forward curves for electricity prices," Computational Management Science, Springer, vol. 16(1), pages 345-369, February.
    15. Marí, L. & Nabona, N. & Pagès-Bernaus, A., 2017. "Medium-term power planning in electricity markets with pool and bilateral contracts," European Journal of Operational Research, Elsevier, vol. 260(2), pages 432-443.
    16. Luisa Andreis & Maria Flora & Fulvio Fontini & Tiziano Vargiolu, 2019. "Pricing Reliability Options under different electricity prices' regimes," Papers 1909.05761, arXiv.org.
    17. Florian Ziel, 2015. "Forecasting Electricity Spot Prices using Lasso: On Capturing the Autoregressive Intraday Structure," Papers 1509.01966, arXiv.org, revised Jan 2016.
    18. Hagfors, Lars Ivar & Kamperud , Hilde Horthe & Paraschiv, Florentina & Prokopczuk, Marcel & Sator, Alma & Westgaard, Sjur, 2016. "Prediction of Extreme Price Occurrences in the German Day-ahead Electricity Market," Working Papers on Finance 1622, University of St. Gallen, School of Finance.
    19. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    20. Kiesel, Rüdiger & Paraschiv, Florentina, 2017. "Econometric analysis of 15-minute intraday electricity prices," Energy Economics, Elsevier, vol. 64(C), pages 77-90.
    21. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    22. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    23. Rick Steinert & Florian Ziel, 2018. "Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures," Papers 1801.10583, arXiv.org.
    24. Kostrzewski, Maciej & Kostrzewska, Jadwiga, 2019. "Probabilistic electricity price forecasting with Bayesian stochastic volatility models," Energy Economics, Elsevier, vol. 80(C), pages 610-620.
    25. Islyaev, Suren & Date, Paresh, 2015. "Electricity futures price models: Calibration and forecasting," European Journal of Operational Research, Elsevier, vol. 247(1), pages 144-154.
    26. Pape, Christian & Hagemann, Simon & Weber, Christoph, 2016. "Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market," Energy Economics, Elsevier, vol. 54(C), pages 376-387.
    27. Caldana, Ruggero & Fusai, Gianluca & Roncoroni, Andrea, 2017. "Electricity forward curves with thin granularity: Theory and empirical evidence in the hourly EPEXspot market," European Journal of Operational Research, Elsevier, vol. 261(2), pages 715-734.
    28. Obermüller, Frank, 2017. "Explaining Electricity Forward Premiums - Evidence for the Weather Uncertainty Effect," EWI Working Papers 2017-10, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
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    30. 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.

  5. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.

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    1. Galán-Gutiérrez, Juan Antonio & Martín-García, Rodrigo, 2021. "Cointegration between the structure of copper futures prices and Brexit," Resources Policy, Elsevier, vol. 71(C).
    2. Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
    3. Florentina Paraschiv & Stine Marie Reese & Margrethe Ringkjøb Skjelstad, 2020. "Portfolio stress testing applied to commodity futures," Computational Management Science, Springer, vol. 17(2), pages 203-240, June.
    4. Qadan, Mahmoud & Idilbi, Yasmeen, 2022. "Presidential honeymoons, political cycles and the commodity market," Resources Policy, Elsevier, vol. 77(C).
    5. Robert J. Powell & Duc H. Vo, 2020. "A Comprehensive Stability Indicator for Banks," Risks, MDPI, vol. 8(1), pages 1-15, February.
    6. Papa Gueye Fam & Rachida Hennani & Nicolas Huchet, 2017. "U.S. Monetary Policy, Commodity Prices And The Financialization Hypothesis," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 20, pages 53-77, December.
    7. Gimet, Céline & Lagoarde-Segot, Thomas & Reyes-Ortiz, Luis, 2019. "Financialization and the macroeconomy. Theory and empirical evidence," Economic Modelling, Elsevier, vol. 81(C), pages 89-110.
    8. Spada, Matteo & Paraschiv, Florentina & Burgherr, Peter, 2018. "A comparison of risk measures for accidents in the energy sector and their implications on decision-making strategies," Energy, Elsevier, vol. 154(C), pages 277-288.

  6. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.

    Cited by:

    1. Loutfi, Ahmad Amine & Sun, Mengtao & Loutfi, Ijlal & Solibakke, Per Bjarte, 2022. "Empirical study of day-ahead electricity spot-price forecasting: Insights into a novel loss function for training neural networks," Applied Energy, Elsevier, vol. 319(C).
    2. João Estevão & Clara Raposo & José Dias Lopes, 2018. "The Paris Agreement and electricity markets outside the EU," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(4), December.
    3. Gunther Glenk & Stefan Reichelstein, 2020. "Synergistic Value in Vertically Integrated Power‐to‐Gas Energy Systems," Production and Operations Management, Production and Operations Management Society, vol. 29(3), pages 526-546, March.
    4. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    5. Hinderks, W.J. & Wagner, A., 2019. "Pricing German Energiewende products: Intraday cap/floor futures," Energy Economics, Elsevier, vol. 81(C), pages 287-296.
    6. Maciejowska, Katarzyna, 2020. "Assessing the impact of renewable energy sources on the electricity price level and variability – A quantile regression approach," Energy Economics, Elsevier, vol. 85(C).
    7. Sánchez de la Nieta, A.A. & Contreras, J., 2020. "Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case," Energy Economics, Elsevier, vol. 90(C).
    8. Karl Frauendorfer & Florentina Paraschiv & Michael Schürle, 2018. "Cross-Border Effects on Swiss Electricity Prices in the Light of the Energy Transition," Energies, MDPI, vol. 11(9), pages 1-30, August.
    9. Alasseur, C. & Féron, O., 2018. "Structural price model for coupled electricity markets," Energy Economics, Elsevier, vol. 75(C), pages 104-119.
    10. Prata, Ricardo & Carvalho, Pedro M.S. & Azevedo, Inês L., 2018. "Distributional costs of wind energy production in Portugal under the liberalized Iberian market regime," Energy Policy, Elsevier, vol. 113(C), pages 500-512.
    11. Hartner, Michael & Permoser, Andreas, 2018. "Through the valley: The impact of PV penetration levels on price volatility and resulting revenues for storage plants," Renewable Energy, Elsevier, vol. 115(C), pages 1184-1195.
    12. Coester, Andreas & Hofkes, Marjan W. & Papyrakis, Elissaios, 2018. "An optimal mix of conventional power systems in the presence of renewable energy: A new design for the German electricity market," Energy Policy, Elsevier, vol. 116(C), pages 312-322.
    13. Finke, Jonas & Bertsch, Valentin & Di Cosmo, Valeria, 2023. "Exploring the feasibility of Europe’s renewable expansion plans based on their profitability in the market," Energy Policy, Elsevier, vol. 177(C).
    14. Natalia Naval & Jose M. Yusta, 2020. "Water-Energy Management for Demand Charges and Energy Cost Optimization of a Pumping Stations System under a Renewable Virtual Power Plant Model," Energies, MDPI, vol. 13(11), pages 1-21, June.
    15. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
    16. Zarnikau, J. & Tsai, C.H. & Woo, C.K., 2020. "Determinants of the wholesale prices of energy and ancillary services in the U.S. Midcontinent electricity market," Energy, Elsevier, vol. 195(C).
    17. Woo, C.K. & Shiu, A. & Liu, Y. & Luo, X. & Zarnikau, J., 2018. "Consumption effects of an electricity decarbonization policy: Hong Kong," Energy, Elsevier, vol. 144(C), pages 887-902.
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    21. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
    22. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
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    24. Figueiredo, Nuno Carvalho & Silva, Patrícia Pereira da, 2019. "The “Merit-order effect” of wind and solar power: Volatility and determinants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 54-62.
    25. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
    26. Cyril Martin de Lagarde & Frédéric Lantz, 2017. "Impact of Variable Renewable Production on Electriciy Prices in Germany : A Markov Switching Model," Working Papers hal-03187020, HAL.
    27. Juan Ignacio Pe~na & Rosa Rodriguez & Silvia Mayoral, 2022. "Tail Risk of Electricity Futures," Papers 2202.01732, arXiv.org.
    28. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    29. Angelo Maiorino & Adrián Mota-Babiloni & Manuel Gesù Del Duca & Ciro Aprea, 2021. "Scheduling Optimization of a Cabinet Refrigerator Incorporating a Phase Change Material to Reduce Its Indirect Environmental Impact," Energies, MDPI, vol. 14(8), pages 1-17, April.
    30. Hasan Murat Ertuğrul & Mustafa Tevfik Kartal & Serpil Kılıç Depren & Uğur Soytaş, 2022. "Determinants of Electricity Prices in Turkey: An Application of Machine Learning and Time Series Models," Energies, MDPI, vol. 15(20), pages 1-17, October.
    31. 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.
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    36. 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.
    37. Jessica Raasch, "undated". "Flexible Use of Residential Heat Pumps - Possibilities and Limits of Market Participation," EWL Working Papers 1802, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Mar 2018.
    38. Haxhimusa, Adhurim, 2018. "The Effects of German Wind and Solar Electricity on French Spot Price Volatility: An Empirical Investigation," Department of Economics Working Paper Series 258, WU Vienna University of Economics and Business.
    39. Peña, Juan Ignacio & Rodríguez, Rosa & Mayoral, Silvia, 2020. "Tail risk of electricity futures," Energy Economics, Elsevier, vol. 91(C).
    40. Clémence Alasseur & Imen Ben Taher & Anis Matoussi, 2020. "An Extended Mean Field Game for Storage in Smart Grids," Journal of Optimization Theory and Applications, Springer, vol. 184(2), pages 644-670, February.
    41. Ozan Korkmaz & Bihrat Önöz, 2022. "Modelling the Potential Impacts of Nuclear Energy and Renewables in the Turkish Energy System," Energies, MDPI, vol. 15(4), pages 1-25, February.
    42. Florentina Paraschiv & Dima Mohamad, 2020. "The Nuclear Power Dilemma—Between Perception and Reality," Energies, MDPI, vol. 13(22), pages 1-19, November.
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    44. Sousa, Joana & Soares, Isabel, 2022. "Demand response potential: An economic analysis for MIBEL and EEX," Energy, Elsevier, vol. 244(PA).
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    46. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    47. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    48. Hörnlein, Lena, 2019. "The value of gas-fired power plants in markets with high shares of renewable energy," Energy Economics, Elsevier, vol. 81(C), pages 1078-1098.
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    51. Peña, Juan Ignacio & Rodríguez, Rosa & Mayoral, Silvia, 2022. "Cannibalization, depredation, and market remuneration of power plants," Energy Policy, Elsevier, vol. 167(C).
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    55. Benth, Fred Espen & Paraschiv, Florentina, 2018. "A space-time random field model for electricity forward prices," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 203-216.
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    57. Mwampashi, Muthe Mathias & Nikitopoulos, Christina Sklibosios & Konstandatos, Otto & Rai, Alan, 2021. "Wind generation and the dynamics of electricity prices in Australia," Energy Economics, Elsevier, vol. 103(C).
    58. De Siano, Rita & Sapio, Alessandro, 2022. "Spatial merit order effects of renewables in the Italian power exchange," Energy Economics, Elsevier, vol. 108(C).
    59. Bean, Patrick & Blazquez, Jorge & Nezamuddin, Nora, 2017. "Assessing the cost of renewable energy policy options – A Spanish wind case study," Renewable Energy, Elsevier, vol. 103(C), pages 180-186.
    60. Gunther Glenk & Stefan Reichelstein, 2022. "Reversible Power-to-Gas systems for energy conversion and storage," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    61. Francesco Mancini & Benedetto Nastasi, 2020. "Solar Energy Data Analytics: PV Deployment and Land Use," Energies, MDPI, vol. 13(2), pages 1-18, January.
    62. Sapio, Alessandro, 2015. "The effects of renewables in space and time: A regime switching model of the Italian power price," Energy Policy, Elsevier, vol. 85(C), pages 487-499.
    63. Mulder, Machiel & Scholtens, Bert, 2016. "A plant-level analysis of the spill-over effects of the German Energiewende," Applied Energy, Elsevier, vol. 183(C), pages 1259-1271.
    64. Westgaard, Sjur & Fleten, Stein-Erik & Negash, Ahlmahz & Botterud, Audun & Bogaard, Katinka & Verling, Trude Haugsvaer, 2021. "Performing price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity market," Energy, Elsevier, vol. 214(C).
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    67. Rüdiger Kiesel & Florentina Paraschiv & Audun Sætherø, 2019. "On the construction of hourly price forward curves for electricity prices," Computational Management Science, Springer, vol. 16(1), pages 345-369, February.
    68. Ederer, Nikolaus, 2015. "The market value and impact of offshore wind on the electricity spot market: Evidence from Germany," Applied Energy, Elsevier, vol. 154(C), pages 805-814.
    69. Mosquera-López, Stephania & Uribe, Jorge M., 2022. "Pricing the risk due to weather conditions in small variable renewable energy projects," Applied Energy, Elsevier, vol. 322(C).
    70. Ignacio Blanco & Daniela Guericke & Anders N. Andersen & Henrik Madsen, 2018. "Operational Planning and Bidding for District Heating Systems with Uncertain Renewable Energy Production," Energies, MDPI, vol. 11(12), pages 1-26, November.
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  7. Florentina Paraschiv, 2013. "Adjustment Policy of Deposit Rates in the Case of Swiss Non-maturing Savings Accounts," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 3(3), pages 1-19.
    See citations under working paper version above.

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