In many electricity markets, retailers purchase electricity at an unregulated spot price and sell to consumers at a heavily regulated price. Consequently, the occurrence of spikes in the spot electricity price represents a major source of risk for retailers, and the forecasting of these price spikes is important for effective risk management. Traditional approaches to modelling electricity prices have aimed to predict the trajectory of spot prices. In contrast, this paper focuses on the prediction of price spikes. The time series of price spikes is treated as a discrete-time point process, and a nonlinear variant of the autoregressive conditional hazard model is used to model this process. The model is estimated using half-hourly data from the Australian electricity market for the period 1 March 2001 to 30 June 2007. One-step-ahead forecasts of the probability of a price spike are then generated for each half hour in the forecast period, 1 July 2007 to 30 September 2007. The forecasting performance of the model is then evaluated against a benchmark that is consistent with the assumptions of commonly-used electricity pricing models.
- Autoregressive conditional duration
- Autoregressive conditional hazard
- Electricity futures
- Electricity prices
- Price spikes
ASJC Scopus subject areas
- Business and International Management