EconPapers    
Economics at your fingertips  
 

FORECASTING DAILY VOLATILITY USING RANGE-BASED DATA

Yuanfang Wang and Matthew C. Roberts

No 20377, 2004 Annual meeting, August 1-4, Denver, CO from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association)

Abstract: Users of agricultural markets frequently need to establish accurate representations of expected future volatility. The fact that range-based volatility estimators are highly efficient has been acknowledged in the literature. However, it is not clear whether using range-based data leads to better risk management decisions. This paper compares the performance of GARCH models, range-based GARCH models, and log-range based ARMA models in terms of their forecasting abilities. The realized volatility will be used as the forecasting evaluation criteria. The conclusion helps establish an efficient forecasting framework for volatility models.

Keywords: Marketing (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://ageconsearch.umn.edu/record/20377/files/sp04wa04.pdf (application/pdf)

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: https://EconPapers.repec.org/RePEc:ags:aaea04:20377

DOI: 10.22004/ag.econ.20377

Access Statistics for this paper

More papers in 2004 Annual meeting, August 1-4, Denver, CO from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().

 
Page updated 2019-10-12
Handle: RePEc:ags:aaea04:20377