Energy forward price prediction with a hybrid adaptive model

Nguyen, Hang T. and Nabney, Ian T. (2009). Energy forward price prediction with a hybrid adaptive model. IN: IEEE Symposium on Computational Intelligence for Financial Engineering, 2009. CIFEr '09. IEEE.

Abstract

This paper presents a forecasting technique for forward electricity/gas prices, one day ahead. This technique combines a Kalman filter (KF) and a generalised autoregressive conditional heteroschedasticity (GARCH) model (often used in financial forecasting). The GARCH model is used to compute next value of a time series. The KF updates parameters of the GARCH model when the new observation is available. This technique is applied to real data from the UK energy markets to evaluate its performance. The results show that the forecasting accuracy is improved significantly by using this hybrid model. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

Publication DOI: https://doi.org/10.1109/CIFER.2009.4937504
Divisions: Engineering & Applied Sciences > Computer science
Engineering & Applied Sciences > Computer science research group
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Additional Information: Computational Intelligence for Financial Engineering, CIFEr 2009, Nashville (TN)
Uncontrolled Keywords: Kalman filters,autoregressive processes,load forecasting,power markets,GARCH model,Kalman filter,UK energy markets,energy forward price prediction,forecasting technique,forward electricity/gas prices,generalised autoregressive conditional heteroschedasticity model,hybrid adaptive model,Computer Science Applications,Artificial Intelligence,Software,Applied Mathematics,Finance
Full Text Link: http://ieeexplo ... ld%3DSearch+All
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2009-03-30
Authors: Nguyen, Hang T.
Nabney, Ian T. ( 0000-0003-1513-993X)

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