Publication: Electricity price forecasting by averaging dynamic factor models
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2016-08-01
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MDPI
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Abstract
In the context of the liberalization of electricity markets, forecasting prices is essential. With this aim, research has evolved to model the particularities of electricity prices. In particular, dynamic factor models have been quite successful in the task, both in the short and long run. However, specifying a single model for the unobserved factors is difficult, and it cannot be guaranteed that such a model exists. In this paper, model averaging is employed to overcome this difficulty, with the expectation that electricity prices would be better forecast by a combination of models for the factors than by a single model. Although our procedure is applicable in other markets, it is illustrated with an application to forecasting spot prices of the Iberian Market, MIBEL (The Iberian Electricity Market). Three combinations of forecasts are successful in providing improved results for alternative forecasting horizons.
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Market, Combination, Dimension, Selection, Dimensionality reduction, Electricity prices, Bayesian model averaging, Forecast combination
Bibliographic citation
Alonso, A., Bastos, G., & García‐Martos, C. (2016). Electricity price forecasting by averaging dynamic factor models. Energies, 9(8), 600.