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Forecasting electricity spot prices using time-series models with a double temporal segmentation

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bfm_2014.pdf (1.105Mb)
Date
2014
Dewey
Economie de la terre et des ressources naturelles
Sujet
Electricity spot prices; forecasting; regime-switching
JEL code
C.C2.C22; C.C2.C24; Q.Q4.Q43
Conference name
2nd International Symposium on Energy and Finance Issues (ISEFI-2014)
Conference date
03-2014
Conference city
Paris
Conference country
France
URI
https://basepub.dauphine.fr/handle/123456789/13532
Collections
  • LEDa : Publications
Metadata
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Author
Fouquau, Julien
status unknown
Bessec, Marie
status unknown
Méritet, Sophie
status unknown
Type
Communication / Conférence
Item number of pages
34
Abstract (EN)
The French wholesale market is set to expand in the next few years under European pressure and national decisions. In this paper, we assess the forecasting ability of several classes of time series models for electricity wholesale spot prices at a day-ahead horizon in France. Electricity spot prices display a strong seasonal pattern, particularly in France given the high share of electric heating in housing during winter time. To deal with this pattern, we implement a double temporal segmentation of the data. For each trading period and season, we use a large number of specifications based on market fundamentals: linear regressions, markov-switching models, threshold models with a smooth transition. Non-linear models designed to capture the sudden and fast-reverting spikes in the price dynamics yield more accurate forecasts. Modeling each season independently also leads to better results. Finally, pooling forecasts gives more reliable results. Individual models are generally superior but their performance is more unstable across hours and seasons.

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