Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data

Segnon Mawuli, Keung Lau Chi, Wilfling Bernd, Gupta Rangan

Abstract
We analyze Australian electricity price returns and find that they exhibit multifractal structures. Consequently, we let the return mean equation follow a long memory smooth transition autoregressive (STAR) process and specify volatility dynamics as a Markov-switching multifractal (MSM) process. We compare the out-of-sample volatility forecasting performance of the STAR-MSM model with that of other STAR mean processes, combined with various conventional GARCH-type volatility equations (for example, STAR-GARCH(1,1)). We find that the STAR-MSM model competes with conventional STAR-GARCH specifications with respect to volatility forecasting, but does not (systematically) outperform them.

Keywords
Electricity price volatility; multifractal modeling; GARCH processes; volatility forecasting