Publication: Electricity prices forecasting by averaging dynamic factor models
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2017-01
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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 can not 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 acombination of models for the factors
than by a single model. Although our procedure is applicable in other markets, it is
illustrated with applications to forecasting spot prices of the Iberian Market, MIBEL
(The Iberian Electricity Market) and the Italian Market. Three combinations of
forecasts are successful in providing improved results for alternative forecasting
horizons.
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Dimensionality reduction, Electricity prices, Bayesian model averaging, Forecast combination