Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?

Weron, Rafal and Misiorek, Adam (2007): Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts? Published in: Prace Naukowe Akademii Ekonomicznej we Wroclawiu , Vol. 1076, (2007): pp. 472-480.

Abstract

This paper is a continuation of our earlier studies on short-term price forecasting of California electricity prices with time series models. Here we focus on whether models with heavy-tailed innovations perform better in terms of forecasting accuracy than their Gaussian counterparts. Consequently, we limit the range of analyzed models to autoregressive time series approaches that have been found to perform well for pre-crash California power market data. We expand them by allowing for heavy-tailed innovations in the form of α-stable or generalized hyperbolic noise.

• Item Type: MPRA Paper
• Institution: Hugo Steinhaus Center, Wroclaw University of Technology
• Language: English
• Keywords: Electricity; price forecasting; heavy tails; time series; α-stable distribution; generalized hyperbolic distribution
• Subjects: C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C46 - Specific Distributions ; Specific Statistics; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q40 - General

References

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