Outlier Treatment and Robust Approaches for Modeling Electricity Spot Prices

Trueck, Stefan and Weron, Rafal and Wolff, Rodney (2007): Outlier Treatment and Robust Approaches for Modeling Electricity Spot Prices.

Abstract

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.

• Item Type: MPRA Paper
• Institution: Hugo Steinhaus Center, Wroclaw University of Technology
• Language: English
• Keywords: Electricity; price modeling; seasonal decomposition; price spike
• Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q40 - General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation

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