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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).

Abstract

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.

Impact and interest:

36 citations in Scopus
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22 citations in Web of Science®

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ID Code: 8162
Item Type: Journal Article
Additional URLs:
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
Last Modified: 11 Aug 2011 04:15

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