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Electricity prices forecasting by averaging dynamic factor models

Carolina García-Martos, Guadalupe Bastos and Andrés Modesto Alonso Fernández

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

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.

Keywords: Dimensionality; reduction; Electricity; prices; Bayesian; model; averaging; Forecast; combination (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ene and nep-for
Date: 2017-01
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