Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting

Alonso, Andrés M. and García-Martos, Carolina and Rodríguez, Julio and Sánchez Naranjo, María Jesús (2011). Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting. "Technometrics: A journal of statistics for the physical, chemical and engineering sciences", v. 53 (n. 2); pp. 137-151. ISSN 0040-1706. https://doi.org/10.1198/TECH.2011.09050.

Description

Title: Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting
Author/s:
  • Alonso, Andrés M.
  • García-Martos, Carolina
  • Rodríguez, Julio
  • Sánchez Naranjo, María Jesús
Item Type: Article
Título de Revista/Publicación: Technometrics: A journal of statistics for the physical, chemical and engineering sciences
Date: 2011
ISSN: 0040-1706
Volume: 53
Subjects:
Freetext Keywords: Dimensionality reduction, Energy prices, Nonstationary, Seasonality, Unobserved components, VARIMA models
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 this work, we propose the Seasonal Dynamic Factor Analysis (SeaDFA), an extension of Nonstationary Dynamic Factor Analysis, through which one can deal with dimensionality reduction in vectors of time series in such a way that both common and specific components are extracted. Furthermore, common factors are able to capture not only regular dynamics (stationary or not) but also seasonal ones, by means of the common factors following a multiplicative seasonal VARIMA(p, d, q) × (P, D, Q)s model. Additionally, a bootstrap procedure that does not need a backward representation of the model is proposed to be able to make inference for all the parameters in the model. A bootstrap scheme developed for forecasting includes uncertainty due to parameter estimation, allowing enhanced coverage of forecasting intervals. A challenging application is provided. The new proposed model and a bootstrap scheme are applied to an innovative subject in electricity markets: the computation of long-term point forecasts and prediction intervals of electricity prices. Several appendices with technical details, an illustrative example, and an additional table are available online as Supplementary Materials.

More information

Item ID: 12363
DC Identifier: http://oa.upm.es/12363/
OAI Identifier: oai:oa.upm.es:12363
DOI: 10.1198/TECH.2011.09050
Official URL: http://www.tandfonline.com/doi/abs/10.1198/TECH.2011.09050
Deposited by: Memoria Investigacion
Deposited on: 17 Aug 2012 12:45
Last Modified: 19 May 2017 15:31
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