Forecasting electricity price volatility with the Markov-switching GARCH model: Evidence from the Nordic electric power market

Abstract

In this paper, electricity price behavior in the Nordic electric power market is forecasted with both the Markov-switching generalized autoregressive conditional heteroskedasticity (MS-GARCH) model and a set of different volatility models. The MS-GARCH model is estimated with two regimes, representing periods of low and high volatility. This study shows that electricity price volatility is not only highly volatile but also strongly regime-dependent. The empirical results show that the MS-GARCH model enables more accurate forecasting than the standard GARCH models, according to tail loss and reality check tests for one- and multi-step ahead forecasts. The results suggest that both the electricity generation companies and consumers of electricity could carry out better price forecasts by using the proposed MS-GARCH model.