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Forecasting Daily Volatility Using Range-Based Data

Author

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  • Wang, Yuanfang
  • Roberts, Matthew C.

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.

Suggested Citation

  • Wang, Yuanfang & Roberts, Matthew C., 2004. "Forecasting Daily Volatility Using Range-Based Data," 2004 Annual meeting, August 1-4, Denver, CO 20377, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea04:20377
    DOI: 10.22004/ag.econ.20377
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    Cited by:

    1. Tomasz Skoczylas, 2013. "Modelowanie i prognozowanie zmienności przy użyciu modeli opartych o zakres wahań," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 35.

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    Marketing;

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