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

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

Zusammenfassung

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.

Schlüsselwörter

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

Zitieren als

Segnon, M., Keung, L. C., Wilfling, B., & Gupta, R. (2017). Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data. In CQE-Working-Papers: Vol. 61/2017. University of Muenster: Center for Quantitative Economics (CQE), University of Muenster.

Details

Publikationstyp
Arbeitspapier / Working Paper

Begutachtet
Nein

Publikationsstatus
Veröffentlicht

Jahr
2017

Band
61/2017

Reihe
CQE-Working-Papers

Verlag
Center for Quantitative Economics (CQE), University of Muenster

Ort
University of Muenster

Sprache
Englisch