This paper proposes an agent-based modeling (ABM) approach to study the diffusion and adoption of dynamic electricity tariffs. We discuss the difference between opinions and decisions of electricity consumers regarding dynamic pricing. By means of a simple ABM, we provide a plausible explanation...

Recently, Nowotarski et al. (2013) have found that wavelet-based models for the long-term seasonal component (LTSC) are not only better in extracting the LTSC from a series of spot electricity prices but also significantly more accurate in terms of forecasting these prices up to a year ahead...

In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. In particular we calibrate AR/ARX (''X'' stands for exogenous/fundamental variable -- system load in our study), AR/ARX-GARCH, TAR/TARX and Markov regime-switching models to...

The price of electricity is far more volatile than that of other commodities normally noted for extreme volatility. The possibility of extreme price movements increases the risk of trading in electricity markets. However, underlying the process of price returns is a strong mean-reverting...

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they...

This empirical paper compares the accuracy of 12 time series methods for short-term (day-ahead) spot price forecasting in auction-type electricity markets. The methods considered include standard autoregression (AR) models, their extensions – spike preprocessed, threshold and semiparametric...

Typical data sets employed by economists and financial analysts do not exceed a few hundred or thousand observations per series. However, in the last decade data sets containing tick-by-tick observations have become available. The studies of these data have turned up new and interesting facts...

In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate ARMA and ARMAX (where the exogenous variable is the system load) processes. Models are tested on a time series of California power market system prices and loads from the period...