What is it about?
We compare the various components (trend, seasonal cycles) and the forecasts generated by unobserved component models and spline-based nonlinear REGARIMA models when applied to quantities and prices of electricity exchanged in four European markets. There is no uniformly best model, but for some countries one approach tends to be better the the other.
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Why is it important?
Both approaches are rather effective in predicting electricity quantities and prices, but for some time series one approach can be significantly bettere than the other.
Perspectives
Comparing our approaches to machine learning models is the next step.
Professor Matteo M Pelagatti
Universita degli Studi di Milano-Bicocca
Read the Original
This page is a summary of: Component estimation for electricity market data: Deterministic or stochastic?, Energy Economics, August 2018, Elsevier,
DOI: 10.1016/j.eneco.2018.05.027.
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