EconPapers    
Economics at your fingertips  
 

Forecasting crude oil market volatility: A Markov switching multifractal volatility approach

Yudong Wang, Chongfeng Wu and Li Yang

International Journal of Forecasting, 2016, vol. 32, issue 1, pages 1-9

Abstract: We use a Markov switching multifractal (MSM) volatility model to forecast crude oil return volatility. Not only can the model capture stylized facts of multiscaling, long memory, and structural breaks in volatility, it is also more parsimonious in parameterization, after allowing for hundreds of regimes in the volatility. Our in-sample results suggest that MSM models fit oil return data better than the traditional GARCH-class models. The out-of-sample results show that MSM models generate more accurate volatility forecasts than either popular GARCH-class models or the historical volatility model.

Keywords: Markov switching multifractal (MSM) models; Volatility; Crude oil markets; GARCH-class models; Model confidence set (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (3) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207015000631
Full text for ScienceDirect subscribers only

Related works:
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: http://EconPapers.repec.org/RePEc:eee:intfor:v:32:y:2016:i:1:p:1-9

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Series data maintained by Dana Niculescu ().

 
Page updated 2017-02-22
Handle: RePEc:eee:intfor:v:32:y:2016:i:1:p:1-9