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Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO

Author

Listed:
  • Bartosz Uniejewski
  • Grzegorz Marcjasz
  • Rafal Weron

Abstract

Using a unique set of prices from the German EPEX market we take a closer look at the fine structure of intraday markets for electricity with its continuous trading for individual load periods up to 30 minutes before delivery. We apply the least absolute shrinkage and selection operator (LASSO) to gain statistically sound insights on variable selection and provide recommendations for very short-term electricity price forecasting.

Suggested Citation

  • 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.
  • Handle: RePEc:wuu:wpaper:hsc1807
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    File URL: http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_18_07.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. repec:gam:jeners:v:12:y:2019:i:6:p:1097-:d:215955 is not listed on IDEAS
    2. repec:gam:jeners:v:12:y:2019:i:4:p:631-:d:206429 is not listed on IDEAS
    3. Micha{l} Narajewski & Florian Ziel, 2018. "Econometric modelling and forecasting of intraday electricity prices," Papers 1812.09081, arXiv.org, revised Sep 2019.
    4. Micha{l} Narajewski & Florian Ziel, 2019. "Estimation and simulation of the transaction arrival process in intraday electricity markets," Papers 1901.09729, arXiv.org, revised Dec 2019.

    More about this item

    Keywords

    Intraday electricity market; Variable selection; Price forecasting; LASSO;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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