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

Alonso, Andrés M.; García-Martos, Carolina; Rodríguez, Julio y 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.

Descripción

Título: Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting
Autor/es:
  • Alonso, Andrés M.
  • García-Martos, Carolina
  • Rodríguez, Julio
  • Sánchez Naranjo, María Jesús
Tipo de Documento: Artículo
Título de Revista/Publicación: Technometrics: A journal of statistics for the physical, chemical and engineering sciences
Fecha: 2011
Volumen: 53
Materias:
Palabras Clave Informales: Dimensionality reduction, Energy prices, Nonstationary, Seasonality, Unobserved components, VARIMA models
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 12363
Identificador DC: http://oa.upm.es/12363/
Identificador OAI: oai:oa.upm.es:12363
Identificador DOI: 10.1198/TECH.2011.09050
URL Oficial: http://www.tandfonline.com/doi/abs/10.1198/TECH.2011.09050
Depositado por: Memoria Investigacion
Depositado el: 17 Ago 2012 12:45
Ultima Modificación: 19 May 2017 15:31
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