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)
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)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea04:20377
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