Modeling and Forecasting Electricity Spot Prices: A Functional Data Perspective
Classical time series models have serious difficulties in modeling and forecasting the enormous fluctuations of electricity spot prices. Markov regime switch models belong to the most often used models in the electric- ity literature. These models try to capture the fluctuations of electricity spot prices by using different regimes, each with its own mean and covariance structure. Usually one regime is dedicated to moderate prices and another is dedicated to high prices. However, these models show poor performance and there is no theoretical justification for this kind of classification. The merit or- der model, the most important micro-economic pricing model for electricity spot prices, however, suggests a continuum of mean levels with a functional dependence on electricity demand. We propose a new statistical perspective on modeling and forecasting electricity spot prices that accounts for the merit order model. In a first step, the functional relation between electricity spot prices and electricity demand is modeled by daily price-demand functions. In a second step, we parameter- ize the series of daily price-demand functions using a functional factor model. The power of this new perspective is demonstrated by a forecast study that compares our functional factor model with two established classical time se- ries models as well as two alternative functional data models.
|Date of creation:||Sep 2013|
|Date of revision:|
|Publication status:||Published in The Annals of Applied Statistics 3.7(2013): pp. 1562-1592|
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- Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
- Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
- Kosater, Peter & Mosler, Karl, 2006.
"Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices,"
Elsevier, vol. 83(9), pages 943-958, September.
- Kosater, Peter & Mosler, Karl, 2005. "Can Markov-regime switching models improve power price forecasts? Evidence for German daily power prices," Discussion Papers in Econometrics and Statistics 1/05, University of Cologne, Institute of Econometrics and Statistics.
- Park, Byeong U. & Mammen, Enno & HÃ¤rdle, Wolfgang & Borak, Szymon, 2009.
"Time Series Modelling With Semiparametric Factor Dynamics,"
Journal of the American Statistical Association,
American Statistical Association, vol. 104(485), pages 284-298.
- Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Weron, R & Bierbrauer, M & Trück, S, 2004.
"Modeling electricity prices: jump diffusion and regime switching,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 336(1), pages 39-48.
- Rafal Weron & Michael Bierbrauer & Stefan Trück, 2003. "Modeling electricity prices: jump diffusion and regime switching," HSC Research Reports HSC/03/01, Hugo Steinhaus Center, Wroclaw University of Technology.
- Daniel Gervini, 2008. "Robust functional estimation using the median and spherical principal components," Biometrika, Biometrika Trust, vol. 95(3), pages 587-600.
- Siem Jan Koopman & Marius Ooms & M. Angeles Carnero, 2005.
"Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices,"
Tinbergen Institute Discussion Papers
05-091/4, Tinbergen Institute.
- Koopman, Siem Jan & Ooms, Marius & Carnero, M. Angeles, 2007. "Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 16-27, March.
- Borak, Szymon & Weron, Rafal, 2008.
"A semiparametric factor model for electricity forward curve dynamics,"
10421, University Library of Munich, Germany.
- Szymon Borak & RafaÅ‚ Weron, 2008. "A semiparametric factor model for electricity forward curve dynamics," SFB 649 Discussion Papers SFB649DP2008-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
- Huisman, R. & Huurman, C. & Mahieu, R.J., 2007.
"Hourly Electricity Prices in Day-Ahead Markets,"
ERIM Report Series Research in Management
ERS-2007-002-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
- Yao, Fang & Muller, Hans-Georg & Wang, Jane-Ling, 2005. "Functional Data Analysis for Sparse Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 577-590, June.
- Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
- Jaromir Antoch & Lubos Prchal & Maria Rosaria De Rosa & Pascal Sarda, 2010. "Electricity consumption prediction with functional linear regression using spline estimators," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2027-2041.
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