International Conference on Probabilistic Methods Applied to Power Systems - PMAPS 2016, Beijing (China). 16-20 October 2016
Summary:
Commodity and electricity price models are motivated by the several unexpected evolutions that commodity prices have shown over the previous decades. Several models are based on the classic Black-Scholes model, which was one of the first to simulate the stochastic behaviour of commodity prices. However, as of today, these forecasting models show poor performance when tested in long-term horizons, especially when applied to electricity market prices. This work attempts to determine a way to provide a decent accuracy in long-term (one year or more) forecasts of the Spanish electricity market price using cointegration and vector error correction (VEC) models, alongside other variables, such as fuel spot prices and futures prices. These variables have been assessed in order to determine which factors contribute to this work’s purpose.
Keywords: Cointegration, Commodity Price Models, Electricity Markets, Error Correction Models, Long-Term Forecasting
DOI: 
https://doi.org/10.1109/PMAPS.2016.7764158
Published in PMAPS 2016, pp: 1-7, ISBN: 978-1-5090-1971-7
Publication date: 2016-12-05.
Citation:
R. Marcos, J. Reneses, A. Bello, Long-term Spanish electricity market price forecasting with cointegration and VEC models, International Conference on Probabilistic Methods Applied to Power Systems - PMAPS 2016, Beijing (China). 16-20 October 2016. In: PMAPS 2016: Conference proceedings, ISBN: 978-1-5090-1971-7
