We investigate the effects of outlier treatment on the estimation of the seasonal component and stochastic models in electricity markets. Typically, electricity spot prices exhibit features like seasonality, mean-reverting behavior, extreme volatility and the occurrence of jumps and spikes....

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,...

Model selection in nonparametric and semiparametric regression is of both theoretical and practical interest. Gao and Tong (2004) proposed a semiparametric leave–more–out cross–validation selection procedure for the choice of both the parametric and nonparametric regressors in a nonlinear...

It is known that semiparametric time series regression is often used without checking its suitability and compactness. In theory, this may result in dealing with an unnecessarily complicated model. In practice, one may encounter the computational difficulty caused by the spareness of the data....

In this paper, new estimating methods proposed for dynamic and static probit models with panel data. Simulation studies show that the proposed estimators work relatively well.