Combining the wavelet transform and forecasting models to predict gas forward prices


Autoria(s): Nguyen, Hang T.; Nabney, Ian T.
Data(s)

11/12/2008

Resumo

This paper presents a forecasting technique for forward energy prices, one day ahead. This technique combines a wavelet transform and forecasting models such as multi- layer perceptron, linear regression or GARCH. These techniques are applied to real data from the UK gas markets to evaluate their performance. The results show that the forecasting accuracy is improved significantly by using the wavelet transform. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

Formato

application/pdf

Identificador

http://eprints.aston.ac.uk/7964/1/ICMLA08final.pdf

Nguyen, Hang T. and Nabney, Ian T. (2008). Combining the wavelet transform and forecasting models to predict gas forward prices. IN: Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08. IEEE.

Publicador

IEEE

Relação

http://eprints.aston.ac.uk/7964/

Tipo

Book Section

NonPeerReviewed