Identifying Spikes and Seasonal Components in Electricity Spot Price Data: A Guide to Robust Modeling

33 Pages Posted: 11 Jun 2012

See all articles by Joanna Janczura

Joanna Janczura

Hugo Steinhaus Center

Stefan Trück

Macquarie University Sydney - Department of Applied Finance and Actuarial Studies; Financial Research Network (FIRN); Centre for International Finance and Regulation (CIFR); Macquarie University, Macquarie Business School

Rafal Weron

Wroclaw University of Science and Technology, Department of Operations Research

Rodney Wolff

Queensland University of Technology - School of Economics and Finance

Date Written: June 6, 2012

Abstract

An important issue in fitting stochastic models to electricity spot prices is the estimation of a component to deal with trends and seasonality in the data. Unfortunately, estimation routines for the long-term and short-term seasonal pattern are usually quite sensitive to extreme observations, known as electricity price spikes. Improved robustness of the model can be achieved by (a) filtering the data with some reasonable procedure for outlier detection, and then (b) using estimation and testing procedures on the filtered data. In this paper we examine the effects of different treatment of extreme observations on model estimation and on determining the number of spikes (outliers). In particular we compare results for the estimation of the seasonal and stochastic components of electricity spot prices using either the original or filtered data. We find significant evidence for a superior estimation of both the seasonal short-term and long-term components when the data have been treated carefully for outliers. Overall, our findings point out the substantial impact the treatment of extreme observations may have on these issues and, therefore, also on the pricing of electricity derivatives like futures and option contracts. An added value of our study is the ranking of different filtering techniques used in the energy economics literature, suggesting which methods could be and which should not be used for spike identification.

Keywords: Electricity spot price, Outlier treatment, Price spike, Robust modeling, Seasonality

JEL Classification: Q4, C5, C8

Suggested Citation

Janczura, Joanna and Trueck, Stefan and Weron, Rafal and Wolff, Rodney, Identifying Spikes and Seasonal Components in Electricity Spot Price Data: A Guide to Robust Modeling (June 6, 2012). Available at SSRN: https://ssrn.com/abstract=2081738 or http://dx.doi.org/10.2139/ssrn.2081738

Joanna Janczura

Hugo Steinhaus Center ( email )

50-370
Wroclaw
Poland

Stefan Trueck (Contact Author)

Macquarie University Sydney - Department of Applied Finance and Actuarial Studies ( email )

North Ryde
Sydney, New South Wales 2109
Australia
61298508483 (Phone)
61298508483 (Fax)

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Centre for International Finance and Regulation (CIFR) ( email )

Level 7, UNSW CBD Campus
1 O'Connell Street
Sydney, NSW 2000
Australia

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

Rafal Weron

Wroclaw University of Science and Technology, Department of Operations Research ( email )

Wyspianskiego 27
Wroclaw, 50-370
Poland

Rodney Wolff

Queensland University of Technology - School of Economics and Finance ( email )

GPO Box 2434
2 George Street
Brisbane, Queensland 4001
Australia

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