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Outlier Treatment and Robust Approaches for Modeling Electricity Spot Prices

  • Trueck, Stefan
  • Weron, Rafal
  • Wolff, Rodney

We investigate the effects of outlier treatment on the estimation of the seasonal component and stochastic models in electricity markets. Typically, electricity spot prices exhibit features like seasonality, mean-reverting behavior, extreme volatility and the occurrence of jumps and spikes. Hence, an important issue in the estimation of stochastic models for electricity spot prices is the estimation of a component to deal with trends and seasonality in the data. Unfortunately, in regression analysis, classical estimation routines like OLS are very sensitive to extreme observations and outliers. Improved robustness of the model can be achieved by (a) cleaning the data with some reasonable procedure for outlier rejection, and then (b) using classical estimation and testing procedures on the remainder of the data. We examine the effects on model estimation for different treatment of extreme observations in particular on determining the number of outliers and descriptive statistics of the remaining series after replacement of the outliers. Our findings point out the substantial impact the treatment of extreme observations may have on these issues.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 4711.

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Date of creation: Aug 2007
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Handle: RePEc:pra:mprapa:4711
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  1. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
  2. Bierbrauer, Michael & Menn, Christian & Rachev, Svetlozar T. & Truck, Stefan, 2007. "Spot and derivative pricing in the EEX power market," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3462-3485, November.
  3. Huisman, R. & Mahieu, R.J., 2001. "Regime Jumps in Electricity Prices," ERIM Report Series Research in Management ERS-2001-48-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.
  4. repec:ner:tilbur:urn:nbn:nl:ui:12-3131736 is not listed on IDEAS
  5. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
  6. Weron, Rafal, 2008. "Market price of risk implied by Asian-style electricity options and futures," Energy Economics, Elsevier, vol. 30(3), pages 1098-1115, May.
  7. 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.
  8. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
  9. Michael Bierbrauer & Stefan Trueck & Rafal Weron, 2005. "Modeling electricity prices with regime switching models," Econometrics 0502005, EconWPA.
  10. H�lyette Geman & Andrea Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1225-1262, May.
  11. Geman, Hélyette & Roncoroni, Andréa, 2006. "Understanding the Fine Structure of Electricity Prices," Economics Papers from University Paris Dauphine 123456789/1433, Paris Dauphine University.
  12. Max Stevenson, 2001. "Filtering and Forecasting Spot Electricity Prices in the Increasingly Deregulated Australian Electricity Market," Research Paper Series 63, Quantitative Finance Research Centre, University of Technology, Sydney.
  13. De Jong Cyriel, 2006. "The Nature of Power Spikes: A Regime-Switch Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-28, September.
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