It is well known that GM estimators for linear models are consistent andlead to a small loss of efficiency with respect to LS estimator. When they are extended to threshold models, which are piecewise linear models, the consistency of GM estimators is guaranteed only under certain choices of the objective function. In this paper we suggest the use of robust SETAR (Self Exciting Threshold AutoRegressive) processes to model and forecast electricity prices observed on deregulated markets. The main advantages of estimating robust SETAR models is the possibility to capture two very well-known stylized facts of electricity prices: nonlinearity produced by changes of regimes and the presence of sudden spikes due to inelasticityof demand.

Robust forecasting of electricity prices with nonlinear models and exogenous regressors

GROSSI, Luigi;Nan, Fany
2014-01-01

Abstract

It is well known that GM estimators for linear models are consistent andlead to a small loss of efficiency with respect to LS estimator. When they are extended to threshold models, which are piecewise linear models, the consistency of GM estimators is guaranteed only under certain choices of the objective function. In this paper we suggest the use of robust SETAR (Self Exciting Threshold AutoRegressive) processes to model and forecast electricity prices observed on deregulated markets. The main advantages of estimating robust SETAR models is the possibility to capture two very well-known stylized facts of electricity prices: nonlinearity produced by changes of regimes and the presence of sudden spikes due to inelasticityof demand.
9788884678744
Electricity prices; Extreme values; GM estimator; nonlinear dynamics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/787438
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