Analyzing and Forecasting Electricity Price Using Regime-Switching Models: the Case of New Zealand Market

This paper aims to study the forecasting capabilities of several models under the Markov regime-switching (MRS) and the extreme value theory (EVT) frameworks applied to daily electricity prices in the New Zealand electricity market. The MRS models in this study include up to five regimes, with time-varying transition probabilities and incorporation of external market variables. We apply Hamilton's filter with maximum likelihood estimation for parameter estimation. The EVT peaks-over-threshold (EVT-PoT) framework is also considered, and its relationship to the MRS class of models is discussed. We generate out-of-sample forecasts under various market scenarios. The MRS models are able to replicate real price densities under stable market conditions. The EVT-PoT model performs well despite its lack of complexity compared to the MRS framework. We attribute this to the usage of the generalized Pareto distribution to model price extremities.