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, L.; Grossi, L.; Nan, F.. - (2018), pp. 279-283. (Intervento presentato al convegno 2018 Mathematical and Statistical Methods for Actuarial Sciences and Finance, MAF 2018 tenutosi a Universidad Carlos III de Madrid, esp nel 2018) [10.1007/978-3-319-89824-7_50].
Forecasting the volatility of electricity prices by Robust Estimation: An application to the Italian Market
Grossi L.;
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 IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.