Grzegorz Marcjasz : Citation Profile

Are you Grzegorz Marcjasz?

Politechnika Wrocławska

9

H index

9

i10 index

258

Citations

RESEARCH PRODUCTION:

12

Articles

15

Papers

RESEARCH ACTIVITY:

   6 years (2016 - 2022). See details.
   Cites by year: 43
   Journals where Grzegorz Marcjasz has often published
   Relations with other researchers
   Recent citing documents: 82.    Total self citations: 19 (6.86 %)

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   Permalink: http://citec.repec.org/pma2533
   Updated: 2023-03-25    RAS profile: 2022-11-17    
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Relations with other researchers

Works with:

Weron, Rafał (23)

Uniejewski, Bartosz (10)

Serafin, Tomasz (3)

Jędrzejewski, Arkadiusz (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Grzegorz Marcjasz.

Is cited by:

Weron, Rafał (44)

Uniejewski, Bartosz (39)

Maciejowska, Katarzyna (32)

Nitka, Weronika (21)

Serafin, Tomasz (21)

Weron, Tomasz (17)

Janczura, Joanna (11)

Grossi, Luigi (4)

Thomakos, Dimitrios (3)

Clements, Michael (3)

Shang, Han Lin (3)

Cites to:

Weron, Rafał (277)

Nowotarski, Jakub (96)

Uniejewski, Bartosz (81)

Trueck, Stefan (29)

Maciejowska, Katarzyna (25)

Misiorek, Adam (24)

Hong, Tao (20)

Hyndman, Rob (17)

Serafin, Tomasz (16)

Lisi, Francesco (15)

Nan, Fany (13)

Main data

Where Grzegorz Marcjasz has published?

Journals with more than one article published# docs
Energies4
International Journal of Forecasting3
PLOS ONE2
Energy Economics2

Working Papers Series with more than one paper published# docs
HSC Research Reports / Hugo Steinhaus Center, Wroclaw University of Technology6
WORking papers in Management Science (WORMS) / Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology5
Papers / arXiv.org4

Recent works citing Grzegorz Marcjasz (2022 and 2021)

YearTitle of citing document
2021Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) method. (2021). Sotiros, Dimitrios ; Serafin, Tomasz ; Nitka, Weronika. In: WORking papers in Management Science (WORMS). RePEc:ahh:wpaper:worms2106.

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2021Day-ahead electricity prices prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling. (2021). Becker, Denis Mike ; Li, Wei. In: Papers. RePEc:arx:papers:2101.05249.

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2022Optimal bidding on hourly and quarter-hourly day-ahead electricity price auctions: trading large volumes of power with market impact and transaction costs. (2021). Narajewski, Michal ; Ziel, Florian. In: Papers. RePEc:arx:papers:2104.14204.

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2021National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?. (2021). Cho, Youngsang ; Lee, Juyong. In: Papers. RePEc:arx:papers:2107.06174.

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2022Calibration window selection based on change-point detection for forecasting electricity prices. (2022). Weron, Rafal ; Nitka, Weronika ; Nasiadka, Julia. In: Papers. RePEc:arx:papers:2204.00872.

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2022From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting. (2022). Kruger, Fabian ; Kachele, Fabian ; Grothe, Oliver. In: Papers. RePEc:arx:papers:2204.10154.

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2022Forecasting Electricity Prices. (2022). Weron, Rafał ; Uniejewski, Bartosz ; Maciejowska, Katarzyna. In: Papers. RePEc:arx:papers:2204.11735.

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2022A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets. (2022). Maciejowska, Katarzyna. In: Papers. RePEc:arx:papers:2205.00975.

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2022Probabilistic forecasting of German electricity imbalance prices. (2022). Narajewski, Michal. In: Papers. RePEc:arx:papers:2205.11439.

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2022LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling. (2022). Maciejowska, Katarzyna ; Uniejewski, Bartosz. In: Papers. RePEc:arx:papers:2207.04794.

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2023Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices. (2023). Uniejewski, Bartosz. In: Papers. RePEc:arx:papers:2302.00411.

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2021The cost of uncoupling GB interconnectors. (2021). Newbery, D ; Guo, B. In: Cambridge Working Papers in Economics. RePEc:cam:camdae:2118.

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2021Multi-Day-Ahead Electricity Price Forecasting: A Comparison of fundamental, econometric and hybrid Models. (2021). Vogler, Arne ; Beran, Philip. In: EWL Working Papers. RePEc:dui:wpaper:2102.

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2022Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?. (2022). Liu, Xiaohui ; Jiang, Lan ; Fan, Yawen ; Yang, Yang. In: Annals of Tourism Research. RePEc:eee:anture:v:93:y:2022:i:c:s0160738322000160.

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2021Data augmentation for time series regression: Applying transformations, autoencoders and adversarial networks to electricity price forecasting. (2021). Paterakis, Nikolaos G ; Kok, Koen ; Mincev, Krystof ; Demir, Sumeyra. In: Applied Energy. RePEc:eee:appene:v:304:y:2021:i:c:s0306261921010527.

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2022Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia. (2022). Zhu, Jianguo ; Lei, Gang ; Qiu, Jing ; Lu, Xin. In: Applied Energy. RePEc:eee:appene:v:308:y:2022:i:c:s0306261921015555.

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2022Electricity price forecasting on the day-ahead market using machine learning. (2022). Robardet, Celine ; Plantevit, Marc ; Pierre, Erwan ; Tschora, Leonard. In: Applied Energy. RePEc:eee:appene:v:313:y:2022:i:c:s0306261922002057.

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2022A pattern classification methodology for interval forecasts of short-term electricity prices based on hybrid deep neural networks: A comparative analysis. (2022). Zhou, Kaile ; Zheng, Qingru ; Yang, Yudie ; Shao, Zhen ; Liu, Chen. In: Applied Energy. RePEc:eee:appene:v:327:y:2022:i:c:s0306261922013721.

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2022Deviations from the majority: A local flip model. (2022). Galam, Serge ; Toth, Gabor. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:159:y:2022:i:c:s096007792200340x.

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2022Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming. (2022). Ziel, Florian ; Gonsch, Jochen ; Finnah, Benedikt. In: European Journal of Operational Research. RePEc:eee:ejores:v:301:y:2022:i:2:p:726-746.

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2021An analysis of electricity congestion price patterns in North America. (2021). Ibrahim, Zinatu ; Godin, Frederic. In: Energy Economics. RePEc:eee:eneeco:v:102:y:2021:i:c:s0140988321003893.

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2021Application of bagging in day-ahead electricity price forecasting and factor augmentation. (2021). Yildirim, Dilem ; Ozen, Kadir. In: Energy Economics. RePEc:eee:eneeco:v:103:y:2021:i:c:s0140988321004448.

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2022Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account. (2022). Herwartz, Helmut ; Scheller, Fabian ; Lehna, Malte. In: Energy Economics. RePEc:eee:eneeco:v:106:y:2022:i:c:s0140988321005879.

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2022Short-term risk management of electricity retailers under rising shares of decentralized solar generation. (2022). Keles, Dogan ; Bertsch, Valentin ; Kraft, Emil ; Russo, Marianna. In: Energy Economics. RePEc:eee:eneeco:v:109:y:2022:i:c:s0140988322001323.

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2022Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs. (2022). Ziel, Florian ; Narajewski, Micha. In: Energy Economics. RePEc:eee:eneeco:v:110:y:2022:i:c:s0140988322001505.

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2022Dynamic 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. (2022). Wojcik, Edyta ; Janczura, Joanna. In: Energy Economics. RePEc:eee:eneeco:v:110:y:2022:i:c:s0140988322001840.

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2023Multivariable short-term electricity price forecasting using artificial intelligence and multi-input multi-output scheme. (2023). Huang, Xiaojia ; Wang, Jianzhou ; Nie, Ying ; Jiang, Ping. In: Energy Economics. RePEc:eee:eneeco:v:117:y:2023:i:c:s0140988322006004.

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2021Regularized quantile regression averaging for probabilistic electricity price forecasting. (2021). Weron, Rafał ; Uniejewski, Bartosz. In: Energy Economics. RePEc:eee:eneeco:v:95:y:2021:i:c:s0140988321000268.

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2021Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices. (2021). Weron, Tomasz ; Nitka, Weronika ; Maciejowska, Katarzyna. In: Energy Economics. RePEc:eee:eneeco:v:99:y:2021:i:c:s014098832100178x.

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2021Liquidity costs on intraday power markets: Continuous trading versus auctions. (2021). Wozabal, David ; Kuppelwieser, Thomas. In: Energy Policy. RePEc:eee:enepol:v:154:y:2021:i:c:s0301421521001683.

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2021The cost of uncoupling GB interconnectors. (2021). Newbery, David M ; Guo, Bowei. In: Energy Policy. RePEc:eee:enepol:v:158:y:2021:i:c:s0301421521004390.

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2021Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition. (2021). Dowling, Alexander W ; Elmore, Clay T. In: Energy. RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012615.

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2021Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling. (2021). Becker, Denis Mike ; Li, Wei. In: Energy. RePEc:eee:energy:v:237:y:2021:i:c:s0360544221017916.

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2022National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?. (2022). Cho, Youngsang ; Lee, Juyong. In: Energy. RePEc:eee:energy:v:239:y:2022:i:pd:s0360544221026153.

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2022Probabilistic load forecasting with a non-crossing sparse-group Lasso-quantile regression deep neural network. (2022). Kusiak, Andrew ; Liu, Yezheng ; Jiang, Cuixia ; Xu, Qifa ; Lu, Shixiang. In: Energy. RePEc:eee:energy:v:242:y:2022:i:c:s0360544221032047.

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2022Neural network dynamic differential control for long-term price guidance mechanism of flexible energy service providers. (2022). Yin, Linfei ; Qiu, Yao. In: Energy. RePEc:eee:energy:v:255:y:2022:i:c:s036054422201461x.

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2021Conformal prediction interval estimation and applications to day-ahead and intraday power markets. (2021). Ziel, Florian ; Kath, Christopher. In: International Journal of Forecasting. RePEc:eee:intfor:v:37:y:2021:i:2:p:777-799.

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2022Classification-based model selection in retail demand forecasting. (2022). Pesch, Robert ; Langrock, Roland ; Jahnke, Hermann ; Ulrich, Matthias ; Senge, Robin. In: International Journal of Forecasting. RePEc:eee:intfor:v:38:y:2022:i:1:p:209-223.

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2022Forecasting: theory and practice. (2022). Shang, Han Lin ; Rubaszek, Michał ; Martinez, Andrew ; Grossi, Luigi ; Franses, Philip Hans ; Fiszeder, Piotr ; Clements, Michael ; Castle, Jennifer ; Carnevale, Claudio ; Kolassa, Stephan ; Thorarinsdottir, Thordis ; Guo, Xiaojia ; Reade, James J ; Petropoulos, Fotios ; Nikolopoulos, Konstantinos ; Koehler, Anne B ; Thomakos, Dimitrios ; Browell, Jethro ; Rapach, David E ; Modis, Theodore ; Kang, Yanfei ; Tashman, Len ; Boylan, John E ; Gunter, Ulrich ; Ramos, Patricia ; Ellison, Joanne ; Meeran, Sheik ; Richmond, Victor ; Talagala, Thiyanga S ; Bijak, Jakub ; Guidolin, Massimo ; Pinson, Pierre ; Dokumentov, Alexander ; Jeon, Jooyoung ; Bessa, Ricardo J ; Pedregal, Diego J ; de Baets, Shari ; Ziel, Florian ; Syntetos, Aris A ; Bergmeir, Christoph
2022Modelling the evolution of wind and solar power infeed forecasts. (2022). Paraschiv, Florentina ; Li, Wei. In: Journal of Commodity Markets. RePEc:eee:jocoma:v:25:y:2022:i:c:s2405851321000234.

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2022Short- and long-term forecasting of electricity prices using embedding of calendar information in neural networks. (2022). Michaeli, Hendrik ; Schirra, Florian ; Ramentol, Enislay ; Wagner, Andreas. In: Journal of Commodity Markets. RePEc:eee:jocoma:v:28:y:2022:i:c:s2405851322000046.

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2021Opinion evolution in the Sznajd model on interdependent chains. (2021). Su, Zhan ; Ai, Jun ; Zhao, Mingming ; Shang, Lihui. In: Physica A: Statistical Mechanics and its Applications. RePEc:eee:phsmap:v:565:y:2021:i:c:s0378437120308566.

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2022The role of data frequency and method selection in electricity price estimation: Comparative evidence from Turkey in pre-pandemic and pandemic periods. (2022). Ertugrul, Hasan ; Depren, Ozer ; Erturul, Hasan Murat ; Kartal, Mustafa Tevfik. In: Renewable Energy. RePEc:eee:renene:v:186:y:2022:i:c:p:217-225.

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2022Sustainable microgrid design with multiple demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties. (2022). , Jatinder ; Anh, Thi Huynh ; Yu, Vincent F. In: Renewable and Sustainable Energy Reviews. RePEc:eee:rensus:v:161:y:2022:i:c:s1364032122002556.

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2022Artificial Intelligence for Electricity Supply Chain automation. (2022). Lenk, Steve ; Klaiber, Stefan ; Dreher, Alexander ; Scholz, Christoph ; Marchand, Sophie ; Lehna, Malte ; Richter, Lucas. In: Renewable and Sustainable Energy Reviews. RePEc:eee:rensus:v:163:y:2022:i:c:s1364032122003653.

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2021Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy. (2021). Garcia, Fausto Pedro ; Acarolu, Hakan. In: Energies. RePEc:gam:jeners:v:14:y:2021:i:22:p:7473-:d:675237.

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2021Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market. (2021). Naumann, Michael ; Baule, Rainer. In: Energies. RePEc:gam:jeners:v:14:y:2021:i:22:p:7531-:d:676816.

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2021Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case. (2021). Ehrhardt, Matthias ; di Persio, Luca ; Viviani, Emma. In: Energies. RePEc:gam:jeners:v:14:y:2021:i:2:p:364-:d:478401.

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2021A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings. (2021). Zmeureanu, Radu ; Runge, Jason. In: Energies. RePEc:gam:jeners:v:14:y:2021:i:3:p:608-:d:486810.

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2021A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics. (2021). Schlipf, David ; Guo, Feng. In: Energies. RePEc:gam:jeners:v:14:y:2021:i:9:p:2492-:d:544353.

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2022Predicting Electricity Imbalance Prices and Volumes: Capabilities and Opportunities. (2022). Gilbert, Ciaran ; Browell, Jethro. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:10:p:3645-:d:816810.

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2022Probabilistic Forecasting of German Electricity Imbalance Prices. (2022). Narajewski, Micha. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:14:p:4976-:d:857870.

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2022Multi-Step Ahead Short-Term Electricity Load Forecasting Using VMD-TCN and Error Correction Strategy. (2022). Li, Zhaoyan ; Zhou, Hui ; Zhao, Kai. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:15:p:5375-:d:871030.

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2022Models of Electricity Price Forecasting: Bibliometric Research. (2022). Sulich, Adam ; Zema, Tomasz. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:15:p:5642-:d:879688.

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2022The Economic Viability of PV Power Plant Based on a Neural Network Model of Electricity Prices Forecast: A Case of a Developing Market. (2022). Jovovi, Jelena ; Pejovi, Bojan ; Mini, Nikola ; Urii, Vladimir ; Rogi, Sunica. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:17:p:6219-:d:898525.

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2022Flexible Short-Term Electricity Certificates—An Analysis of Trading Strategies on the Continuous Intraday Market. (2022). Naumann, Michael ; Baule, Rainer. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:17:p:6344-:d:902361.

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2022A Comprehensive Study of Random Forest for Short-Term Load Forecasting. (2022). Dudek, Grzegorz. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:20:p:7547-:d:941080.

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2022Short-Term Electricity Price Forecasting Based on the Two-Layer VMD Decomposition Technique and SSA-LSTM. (2022). Guo, Fang ; Deng, Shangyun ; Zheng, Weijia ; Wen, AN ; Du, Jinfeng ; Huang, Guangshan ; Wang, Ruiyang. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:22:p:8445-:d:969965.

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2022PV Penetration under Market Environment and with System Constraints. (2022). Kiokes, George ; Dimeas, Aris. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:22:p:8673-:d:977254.

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2022Methods of Forecasting Electric Energy Consumption: A Literature Review. (2022). Efremenkov, Egor A ; Martyushev, Nikita V ; Gavrina, Oksana A ; Morgoeva, Angelika D ; Klyuev, Roman V ; Mengxu, QI. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:23:p:8919-:d:984103.

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2022Price Forecasting in Energy Market. (2022). Plastun, Alex ; Kozmenko, Serhiy ; Bilan, Yuriy. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:24:p:9625-:d:1007804.

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2022Error Compensation Enhanced Day-Ahead Electricity Price Forecasting. (2022). Daskalopulu, Aspassia ; Bargiotas, Dimitrios ; Kontogiannis, Dimitrios ; Tsoukalas, Lefteri H ; Arvanitidis, Athanasios Ioannis. In: Energies. RePEc:gam:jeners:v:15:y:2022:i:4:p:1466-:d:751301.

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2023ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation. (2023). Janczura, Joanna ; Pu, Andrzej. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:2:p:807-:d:1031193.

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2023A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector. (2023). Vikovi, Alfredo ; Majnari, Darin ; Franki, Vladimir. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:3:p:1077-:d:1040228.

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2023Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices. (2023). Santos, Leandro Dos ; Mariani, Viviana Cocco ; Seman, Laio Oriel ; Stefenon, Stefano Frizzo. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:3:p:1371-:d:1049947.

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2021Short-Term Electricity Price Forecasting by Employing Ensemble Empirical Mode Decomposition and Extreme Learning Machine. (2021). Mustafa, Iqra ; Aslam, Shahzad ; Khan, Sajjad. In: Forecasting. RePEc:gam:jforec:v:3:y:2021:i:3:p:28-477:d:580060.

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2021Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain. (2021). Verma, Jake ; Caudron, Julien ; Haben, Stephen. In: Forecasting. RePEc:gam:jforec:v:3:y:2021:i:3:p:38-632:d:623967.

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2021Event-Based Evaluation of Electricity Price Ensemble Forecasts. (2021). Ziel, Florian ; Vogler, Arne. In: Forecasting. RePEc:gam:jforec:v:4:y:2021:i:1:p:4-71:d:713504.

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2022Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices. (2022). Pelagatti, Matteo ; Grossi, Luigi ; Golia, Silvia. In: Forecasting. RePEc:gam:jforec:v:5:y:2022:i:1:p:3-101:d:1020016.

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2022Electricity Price Instability over Time: Time Series Analysis and Forecasting. (2022). Kyzym, Mykola ; Gryshova, Inna ; Wang, Diankai ; Shcherbata, Maryna ; Khaustova, Viktoriia ; Salashenko, Tetiana. In: Sustainability. RePEc:gam:jsusta:v:14:y:2022:i:15:p:9081-:d:870788.

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2022Performance Analysis of Machine Learning Algorithms for Energy Demand–Supply Prediction in Smart Grids. (2022). Isaac, Sherrin John ; Onumanyi, Adeiza James ; Cebekhulu, Eric. In: Sustainability. RePEc:gam:jsusta:v:14:y:2022:i:5:p:2546-:d:755932.

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2022The Investigation of Monthly/Seasonal Data Clustering Impact on Short-Term Electricity Price Forecasting Accuracy: Ontario Province Case Study. (2022). Ahmadian, Ali ; Asadpour, Mohammad ; Pourhaji, Nazila ; Elkamel, Ali. In: Sustainability. RePEc:gam:jsusta:v:14:y:2022:i:5:p:3063-:d:765213.

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2022Indicator Selection of Index Construction by Adaptive Lasso with a Generic $$\varepsilon $$ ? -Insensitive Loss. (2022). Chi, Renyong ; Ye, Yafen ; Shao, Yuan-Hai ; Li, Chun-Na ; Hua, Xiangyu. In: Computational Economics. RePEc:kap:compec:v:60:y:2022:i:3:d:10.1007_s10614-021-10175-w.

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2021Application of Bagging in Day-Ahead Electricity Price Forecasting and Factor Augmentation. (2021). Yildirim, Dilem ; Ozen, Kadir. In: ERC Working Papers. RePEc:met:wpaper:2101.

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2022Collective narratives catalyse cooperation. (2022). Frean, Marcus ; Bulbulia, Joseph ; Gokhale, Chaitanya S. In: Palgrave Communications. RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01095-7.

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2021Forecasting Electricity Prices with Expert, Linear and Non-Linear Models. (2021). Ravazzolo, Francesco ; del Grosso, Filippo ; Gianfreda, Angelica ; Bille, Anna Gloria. In: Working Paper series. RePEc:rim:rimwps:21-20.

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2022Multistage optimization filter for trend?based short?term forecasting. (2022). Vinogradov, Dmitri ; Kellard, Neil ; Zafar, Usman. In: Journal of Forecasting. RePEc:wly:jforec:v:41:y:2022:i:2:p:345-360.

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2021Short-term risk management for electricity retailers under rising shares of decentralized solar generation. (2021). Keles, Dogan ; Bertsch, Valentin ; Kraft, Emil ; Russo, Marianna. In: Working Paper Series in Production and Energy. RePEc:zbw:kitiip:57.

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2022An electricity price modeling framework for renewable-dominant markets. (2022). Hain, Martin ; Kargus, Tobias ; Schermeyer, Hans ; Uhrig-Homburg, Marliese ; Fichtner, Wolf. In: Working Paper Series in Production and Energy. RePEc:zbw:kitiip:65.

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Works by Grzegorz Marcjasz:

YearTitleTypeCited
2020Beating the naive: Combining LASSO with naive intraday electricity price forecasts In: WORking papers in Management Science (WORMS).
[Full Text][Citation analysis]		paper11
2020Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts.(2020) In: Energies.
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This paper has another version. Agregated cites: 11		article
2020Trading on short-term path forecasts of intraday electricity prices In: WORking papers in Management Science (WORMS).
[Full Text][Citation analysis]		paper1
2022Trading on short-term path forecasts of intraday electricity prices.(2022) In: Energy Economics.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 1		article
2021Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO In: WORking papers in Management Science (WORMS).
[Full Text][Citation analysis]		paper5
2021Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO.(2021) In: Energies.
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This paper has another version. Agregated cites: 5		article
2021Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx In: WORking papers in Management Science (WORMS).
[Full Text][Citation analysis]		paper0
2021Erratum 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] In: WORking papers in Management Science (WORMS).
[Full Text][Citation analysis]		paper22
2020Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark In: Papers.
[Full Text][Citation analysis]		paper35
2021Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark.(2021) In: Applied Energy.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 35		article
2020Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs In: Papers.
[Full Text][Citation analysis]		paper4
2022Electricity Price Forecasting: The Dawn of Machine Learning In: Papers.
[Full Text][Citation analysis]		paper1
2022Distributional neural networks for electricity price forecasting In: Papers.
[Full Text][Citation analysis]		paper1
2019On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting In: Energy Economics.
[Full Text][Citation analysis]		article31
2017On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting.(2017) In: HSC Research Reports.
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This paper has another version. Agregated cites: 31		paper
2019On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks In: International Journal of Forecasting.
[Full Text][Citation analysis]		article23
2019Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO In: International Journal of Forecasting.
[Full Text][Citation analysis]		article45
2018Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO.(2018) In: HSC Research Reports.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 45		paper
2020Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts? In: International Journal of Forecasting.
[Full Text][Citation analysis]		article15
2018Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?.(2018) In: HSC Research Reports.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 15		paper
2018Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting In: Energies.
[Full Text][Citation analysis]		article29
2018Selection of calibration windows for day-ahead electricity price forecasting.(2018) In: HSC Research Reports.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 29		paper
2020Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme In: Energies.
[Full Text][Citation analysis]		article8
2016The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles In: PLOS ONE.
[Full Text][Citation analysis]		article2
2018Think then act or act then think? In: PLOS ONE.
[Full Text][Citation analysis]		article1
2017Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models In: HSC Research Reports.
[Full Text][Citation analysis]		paper7
2018A note on averaging day-ahead electricity price forecasts across calibration windows In: HSC Research Reports.
[Full Text][Citation analysis]		paper17

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