Forecasting the Volatility of Electricity Prices by Robust Estimation: An Application to the Italian Market

Lisa Crosato (), Luigi Grossi and Fany Nan
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Lisa Crosato: University of Milano-Bicocca
Fany Nan: European Commission, Joint Research Center (JRC)

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2018, pp 279-283 from Springer

Abstract: Abstract Volatility of electricity prices has been often estimated through GARCH-type models which can be strongly affected by the presence of extreme observations. Although the presence of spikes is a well-known stylized effect observed on electricity markets, robust volatility estimators have not been applied so far. In this paper we try to fill this gap by suggesting a robust procedure to the study of the dynamics of electricity prices. The conditional mean of de-trended and seasonally adjusted prices is modeled through a robust estimator of SETAR processes based on a polynomial weighting function while a robust GARCH is used for the conditional variance. The robust GARCH estimator relies on the extension of the forward search by Crosato and Grossi. The robust SETAR-GARCH model is applied to the Italian day-ahead electricity market using data in the period spanning from 2013 to 2015.

Keywords: Italian electricity market; Robust forecasting; Forward search; SETAR models (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-89824-7_50

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DOI: 10.1007/978-3-319-89824-7_50

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