Volatility of electricity prices has been often estimated through GARCHtype 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.
Forecasting the Volatility of Electricity Prices by Robust Estimation: An Application to the Italian Market
Crosato Lisa
;
2018-01-01
Abstract
Volatility of electricity prices has been often estimated through GARCHtype 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.I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.