Electricity Price Forecasting by Averaging Dynamic Factor Models

Alonso, Andrés M. and Bastos, Guadalupe and García-Martos, Carolina (2016). Electricity Price Forecasting by Averaging Dynamic Factor Models. "Energies", v. 9 (n. 8); pp. 600-621. ISSN 1996-1073. https://doi.org/10.3390/en9080600.

Description

Title: Electricity Price Forecasting by Averaging Dynamic Factor Models
Author/s:
  • Alonso, Andrés M.
  • Bastos, Guadalupe
  • García-Martos, Carolina
Item Type: Article
Título de Revista/Publicación: Energies
Date: August 2016
ISSN: 1996-1073
Volume: 9
Subjects:
Freetext Keywords: dimensionality reduction; electricity prices; Bayesian model averaging; forecast combination
Faculty: E.T.S.I. Industriales (UPM)
Department: Ingeniería de Organización, Administración de Empresas y Estadística
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainECO2012-38442UnspecifiedUnspecifiedMétodos estadísticos avanzados para datos complejos
Government of SpainECO2015-66593UnspecifiedUnspecifiedUnspecified
Government of SpainDPI2011-23500UnspecifiedUnspecifiedModelado y predicción de los mercados de energía eléctrica y de CO2 mediante modelos de componentes inobservables

More information

Item ID: 45969
DC Identifier: http://oa.upm.es/45969/
OAI Identifier: oai:oa.upm.es:45969
DOI: 10.3390/en9080600
Official URL: http://www.mdpi.com/1996-1073/9/8/600
Deposited by: Memoria Investigacion
Deposited on: 19 May 2017 15:25
Last Modified: 20 Mar 2019 15:46
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