Economics at your fingertips  

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

Mawuli Segnon, Chi Keung Lau, Bernd Wilfling () and Rangan Gupta ()

No 6117, CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster

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 (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dcm
Date: 2017-05
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) ... r/cqe_wp_61_2017.pdf Version of May 2017 (application/pdf)

Related works:
Working Paper: Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster Am Stadtgraben 9, 48143 Münster, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Susanne Deckwitz ().

Page updated 2019-10-19
Handle: RePEc:cqe:wpaper:6117