Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models
Misiorek, Adam, Trueck, Stefan, & Weron, Rafal (2006) Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models. Studies in Nonlinear Dynamics & Econometrics, 10(3).
In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. In particular we calibrate AR/ARX ("X" stands for exogenous/fundamental variable—system load in our study), AR/ARX-GARCH, TAR/TARX and Markov regime-switching models to California Power Exchange (CalPX) system spot prices. We then use them for out-ofsample point and interval forecasting in normal and extremely volatile periods preceding the market crash in winter 2000/2001. We find evidence that (i) non-linear, threshold regime-switching (TAR/TARX) models outperform their linear counterparts, both in point and interval forecasting, and that (ii) an additional GARCH component generally decreases point forecasting efficiency. Interestingly, the former result challenges a number of previously published studies on the failure of non-linear regime-switching models in forecasting.
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|Item Type:||Journal Article|
|Keywords:||NONLINEAR ANALYSIS, ELECTRICITY PRICES, Interval Forecasting|
|Subjects:||Australian and New Zealand Standard Research Classification > ECONOMICS (140000)|
|Divisions:||Current > QUT Faculties and Divisions > QUT Business School|
|Copyright Owner:||Copyright 2006 The Berkeley Electronic Press|
|Copyright Statement:||Reproduced in accordance with the copyright policy of the publisher.|
|Deposited On:||20 Jun 2007 00:00|
|Last Modified:||28 Apr 2015 00:12|
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