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Energies 2016, 9(8), 600;

Electricity Price Forecasting by Averaging Dynamic Factor Models

Department of Statistics, Universidad Carlos III de Madrid, Getafe 28903, Madrid, Spain
Instituto Flores de Lemus, Universidad Carlos III de Madrid, Getafe 28903, Madrid, Spain
Escuela Técnica Superior de Ingenieros Industriales, Universidad Politécnica de Madrid, Madrid 28040, Spain
A preliminary version of this paper was presented in the Joint International Conference on Computational and Financial Econometrics - European Research Consortium for Informatics and Mathematics Meeting, Ciudad de Oviedo, Spain, 1–3 December 2012.
Author to whom correspondence should be addressed.
Academic Editor: Alicia Troncoso
Received: 2 March 2016 / Revised: 23 June 2016 / Accepted: 13 July 2016 / Published: 28 July 2016
(This article belongs to the Special Issue Energy Time Series Forecasting)
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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. View Full-Text
Keywords: dimensionality reduction; electricity prices; Bayesian model averaging; forecast combination dimensionality reduction; electricity prices; Bayesian model averaging; forecast combination

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Alonso, A.M.; Bastos, G.; García-Martos, C. Electricity Price Forecasting by Averaging Dynamic Factor Models. Energies 2016, 9, 600.

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