Details about Grzegorz Marcjasz

Access statistics for papers by Grzegorz Marcjasz.

Last updated 2024-08-09. Update your information in the RePEc Author Service.

Short-id: pma2533

Working Papers

2023

1. Trading on short-term path forecasts of intraday electricity prices. Part II -- Distributional Deep Neural Networks
   WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology

2022

2. Distributional neural networks for electricity price forecasting
   Papers, arXiv.org View citations (3)
   See also Journal Article Distributional neural networks for electricity price forecasting, Energy Economics, Elsevier (2023) View citations (10) (2023)
3. Electricity Price Forecasting: The Dawn of Machine Learning
   Papers, arXiv.org View citations (4)

2021

4. Erratum to 'Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark' [Appl. Energy 293 (2021) 116983]
   WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology View citations (25)
5. Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO
   WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology View citations (7)
   See also Journal Article Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO, Energies, MDPI (2021) View citations (7) (2021)
6. Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
   WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology View citations (1)
   See also Journal Article Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx, International Journal of Forecasting, Elsevier (2023) View citations (4) (2023)

2020

7. Beating the naive: Combining LASSO with naive intraday electricity price forecasts
   WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology View citations (5)
   See also Journal Article Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts, Energies, MDPI (2020) View citations (14) (2020)
8. Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark
   Papers, arXiv.org View citations (2)
   See also Journal Article Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark, Applied Energy, Elsevier (2021) View citations (84) (2021)
9. Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs
   Papers, arXiv.org View citations (5)
10. Trading on short-term path forecasts of intraday electricity prices
    WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology
    See also Journal Article Trading on short-term path forecasts of intraday electricity prices, Energy Economics, Elsevier (2022) View citations (4) (2022)

2018

11. A note on averaging day-ahead electricity price forecasts across calibration windows
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology View citations (30)
12. Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology View citations (4)
    See also Journal Article Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?, International Journal of Forecasting, Elsevier (2020) View citations (28) (2020)
13. Selection of calibration windows for day-ahead electricity price forecasting
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology View citations (39)
    See also Journal Article Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting, Energies, MDPI (2018) View citations (39) (2018)
14. Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology View citations (5)
    See also Journal Article Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO, International Journal of Forecasting, Elsevier (2019) View citations (55) (2019)

2017

15. Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology View citations (11)
16. On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology View citations (16)
    See also Journal Article On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting, Energy Economics, Elsevier (2019) View citations (38) (2019)

Journal Articles

2023

1. Distributional neural networks for electricity price forecasting
   Energy Economics, 2023, 125, (C) View citations (10)
   See also Working Paper Distributional neural networks for electricity price forecasting, Papers (2022) View citations (3) (2022)
2. Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
   International Journal of Forecasting, 2023, 39, (2), 884-900 View citations (4)
   See also Working Paper Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx, WORking papers in Management Science (WORMS) (2021) View citations (1) (2021)

2022

3. Trading on short-term path forecasts of intraday electricity prices
   Energy Economics, 2022, 112, (C) View citations (4)
   See also Working Paper Trading on short-term path forecasts of intraday electricity prices, WORking papers in Management Science (WORMS) (2020) (2020)

2021

4. Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark
   Applied Energy, 2021, 293, (C) View citations (84)
   See also Working Paper Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark, Papers (2020) View citations (2) (2020)
5. Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO
   Energies, 2021, 14, (11), 1-17 View citations (7)
   See also Working Paper Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO, WORking papers in Management Science (WORMS) (2021) View citations (7) (2021)

2020

6. Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts
   Energies, 2020, 13, (7), 1-16 View citations (14)
   See also Working Paper Beating the naive: Combining LASSO with naive intraday electricity price forecasts, WORking papers in Management Science (WORMS) (2020) View citations (5) (2020)
7. Forecasting Electricity Prices Using Deep Neural Networks: A Robust Hyper-Parameter Selection Scheme
   Energies, 2020, 13, (18), 1-18 View citations (12)
8. Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?
   International Journal of Forecasting, 2020, 36, (2), 466-479 View citations (28)
   See also Working Paper Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?, HSC Research Reports (2018) View citations (4) (2018)

2019

9. On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks
   International Journal of Forecasting, 2019, 35, (4), 1520-1532 View citations (43)
10. On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting
    Energy Economics, 2019, 79, (C), 171-182 View citations (38)
    See also Working Paper On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting, HSC Research Reports (2017) View citations (16) (2017)
11. Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO
    International Journal of Forecasting, 2019, 35, (4), 1533-1547 View citations (55)
    See also Working Paper Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO, HSC Research Reports (2018) View citations (5) (2018)

2018

12. Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting
    Energies, 2018, 11, (9), 1-20 View citations (39)
    See also Working Paper Selection of calibration windows for day-ahead electricity price forecasting, HSC Research Reports (2018) View citations (39) (2018)
13. Think then act or act then think?
    PLOS ONE, 2018, 13, (11), 1-19 View citations (2)

2016

14. The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles
    PLOS ONE, 2016, 11, (11), 1-19 View citations (2)

Software Items

2021

1. ENERGIES_14_3249_MATLAB: MATLAB codes for computing combinations of electricity spot price forecasts as utilized in Jedrzejewski et al. (2021) Energies 14, 3249
   WORMS Software (WORking papers in Management Science Software), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology
2. ENERGIES_14_3249_PYTHON: Market data and PYTHON codes for computing electricity spot price forecasts using LASSO-estimated AR (LEAR) models as utilized in Jedrzejewski et al. (2021) Energies 14, 3249
   WORMS Software (WORking papers in Management Science Software), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology
3. EPFTOOLBOX: The first open-access PYTHON library for driving research in electricity price forecasting (EPF)
   WORMS Software (WORking papers in Management Science Software), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology