Published

2011-05-01

UNA APROXIMACIÓN A LA COMBINACIÓN DE PRONÓSTICOS BASADA EN TÉCNICAS DE ANÁLISIS MULTIVARIANTE

A MULTIVARIATE ANALYSIS APPROACH TO FORECASTS COMBINATION. APPLICATION TO FOREIGN EXCHANGE (FX) MARKETS

Keywords:

análisis de componentes principales, análisis factorial, combinar pronósticos, metodología para pronósticos, series temporales (es)
Combining forecasting, Factor analysis, Forecasting methodology, Principal components analysis, Time series (en)

Downloads

Authors

  • Carlos G. Maté Universidad Pontificia Comillas
El cálculo de pronósticos se caracteriza por la disponibilidad de muchos métodos y porque los horizontes de los pronósticos o las predicciones (económicas, tecnológicas, etc.) son cada vez más diferentes. Combinar pronósticos es una metodología adecuada para manejar el escenario anterior, el cual es conceptualmente adecuado para la aplicación de varios métodos de análisis multivariante. Este artículo revisa algunos problemas principales al combinar pronósticos de manera eficiente, empleando el marco del análisis multivariante. En concreto, se propone una metodología para generar pronósticos combinados con un gran número de pronósticos y se analiza una aplicación al mercado de divisas. Se valora la utilidad de esta metodología en finanzas y varios contextos prácticos, abriéndose posibilidades futuras de investigación a otros contextos aplicados, como los mercados de energía.
Forecasting is characterized by the availability of a lot of methods and the fact that technological and economic forecast horizons are increasingly more different from each other. Combining forecasts is an adequate methodology for handling the above scenario, which is conceptually suitable for the application of several methods of multivariate analysis. This paper reviews some main problems in combining forecasts efficiently from the multivariate analysis view. In particular, a methodology to produce combined forecasts with a large number of forecasts is proposed. The usefulness of such a methodology is assessed in exchange rates forecasting. Further research is suggested for finance as well as for other practical contexts such as energy markets.

Downloads

Download data is not yet available.

License

Copyright (c) 2011 Revista Colombiana de Estadística

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).