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Efficient forecasting of electricity spot prices with expert and LASSO models

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  • Bartosz Uniejewski
  • Rafal Weron

Abstract

Recent electricity price forecasting (EPF) studies suggest that the least absolute shrinkage and selection operator (LASSO) leads to well performing models, generally better than obtained from other variable selection schemes. Conducting an empirical study involving three expert models, two multi-parameter regression (called baseline) models and four variance stabilizing transformations, we discuss the optimal way of implementing the LASSO. We show that using a complex baseline model and a well chosen variance stabilizing transformation indeed leads to significant accuracy gains compared to the typically used EPF models.

Suggested Citation

  • 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 Science and Technology.
    • Handle: RePEc:wuu:wpaper:hsc1802
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    References listed on IDEAS

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    More about this item

    Keywords

    Electricity spot price; Day-ahead market; Long-term seasonal component; LASSO; Automated variable selection; Variance stabilizing transformation;
    All these keywords.

    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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