Weron, Rafal and Misiorek, Adam (2006): Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market. Published in: Proceedings of the Modern Electric Power Systems MEPS'06 International Symposium, September 6-8, 2006, Wrocław, Poland (2006): pp. 34-38.
Download (273kB) | Preview
In this paper we assess the short-term forecasting power of different time series models in the Nord Pool electricity spot market. We evaluate the accuracy of both point and interval predictions; the latter are specifically important for risk management purposes where one is more interested in predicting intervals for future price movements than simply point estimates. We find evidence that non-linear regime-switching models outperform their linear counterparts and that the interval forecasts of all models are overestimated in the relatively non-volatile periods.
|Item Type:||MPRA Paper|
|Institution:||Hugo Steinhaus Center, Wroclaw University of Technology|
|Original Title:||Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market|
|Keywords:||Wholesale electricity price; Point forecast; Interval forecast; AR model; Threshold AR model|
|Subjects:||L - Industrial Organization > L9 - Industry Studies: Transportation and Utilities > L94 - Electric Utilities
Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q40 - General
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 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes
|Depositing User:||Rafal Weron|
|Date Deposited:||07. Jan 2007|
|Last Modified:||13. Mar 2015 00:02|
 D.W. Bunn, Forecasting loads and prices in competitive power markets, Proc. IEEE 88, 2000, 163-169.  P. Christoffersen and F.X. Diebold, How relevant is volatility forecasting for financial risk management, Review of Economics and Statistics 82, 2000, 12-22.  A.J. Conejo at al., Forecasting electricity prices for a day-ahead pool-based electric energy market, International Journal of Forecasting 21, 2005, 435-462.  E.A. Feinberg and D. Genethliou, Load forecasting. In: Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence, J.H. Chow et al. (eds.), Springer, 2005.  J. Hamilton, Time Series Analysis, Princeton Univer-sity Press, 1994.  B.E. Hansen, Inference in TAR models, Studies in Nonlinear Dynamics and Econometrics 2, 1997, 1-14.  A. Misiorek at al., Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models, Studies in Nonlinear Dynamics and Econometrics 10(3), 2006, Article 2.  A. Misiorek and R. Weron, Interval forecasting of spot electricity prices, Proceedings of the EEM-06 Conference, Warszawa, 2006.  M. Shahidehpour at al., Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management, Wiley, 2002.  R. Weron and A. Misiorek, Short-term electricity price forecasting with time series models: A review and evaluation. In: Complex Electricity Markets, Mielczarski, W. (ed.), Łódź, 2006.  R. Weron, Modeling and forecasting electricity loads and prices: A statistical approach, Wiley, Chichester, 2006.