Modelling and Forecasting the Volatility of the Nordic Power Market : An Application of the GARCH-Jump Process

Abstract

Although extreme jumps in electricity prices are a common phenomenon, investigating the jump behaviour in the power market does not receive significant attention in earlier studies. The present study aims to conceal this void in the existing literature. To do so, we employ the autoregressive conditional jump intensity (ARJI) model, combined with the generalised autoregressive conditional heteroskedasticity (GRACH) method, to describe the volatility process and the jump behaviour in Nordic electricity prices. The empirical findings reveal that the Nordic power market is highly volatile, and time-varying jumps exist in the electricity prices. In addition, the GARCH-jump models produce more accurate out-of-sample volatility forecasts than the GARCH and EGARCH models. In summary, the results demonstrate that energy economists, energy policymakers, and market analysts should consider the existence of time-varying jumps in the Nordic power market because the GARCH-jump model provides the best forecasts for electricity prices.