Weron, Rafal and Misiorek, Adam (2008): Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models. Forthcoming in: International Journal of Forecasting

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Abstract
This empirical paper compares the accuracy of 12 time series methods for shortterm (dayahead) spot price forecasting in auctiontype electricity markets. The methods considered include standard autoregression (AR) models, their extensions – spike preprocessed, threshold and semiparametric autoregressions (i.e. AR models with nonparametric innovations), as well as, meanreverting jump diffusions. The methods are compared using a time series of hourly spot prices and systemwide loads for California and a series of hourly spot prices and air temperatures for the Nordic market. We find evidence that (i) models with system load as the exogenous variable generally perform better than pure price models, while this is not necessarily the case when air temperature is considered as the exogenous variable, and that (ii) semiparametric models generally lead to better point and interval forecasts than their competitors, more importantly, they have the potential to perform well under diverse market conditions.
Item Type:  MPRA Paper 

Original Title:  Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models 
Language:  English 
Keywords:  Electricity market, Price forecast, Autoregressive model, Nonparametric maximum likelihood, Interval forecast, Conditional coverage 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes Q  Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4  Energy > Q40  General 
Item ID:  10428 
Depositing User:  Rafal Weron 
Date Deposited:  18. Sep 2008 06:46 
Last Modified:  12. Feb 2013 05:12 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/10428 