Modelling Spikes in Electricity Prices

During periods of market stress, electricity prices can rise dramat-ically. Electricity retailers cannot pass these extreme prices on to cus-tomers because of retail price regulation. Improved prediction of these price spikes, therefore, is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queens-land electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilites. Unlike traditional Markov-switching models, that assume normality of the prices in each state, the model presented here uses a generalized beta distribution to allow for the skewness in the distribution of electricity prices during high-price episodes