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英文文献：Forecasting Daily Volatility Using Range-Based Data-使用区间数据预测日波动率
英文文献作者：Wang, Yuanfang,Roberts, Matthew C.
英文文献摘要：
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.
农业市场的使用者经常需要对预期的未来波动率建立准确的表述。基于范围的波动率估计器是高效的这一事实已经在文献中得到承认。然而，目前尚不清楚使用基于范围的数据是否会导致更好的风险管理决策。本文比较了基于距离的GARCH模型、基于距离的GARCH模型和基于对数距离的ARMA模型的预测能力。以已实现波动率作为预测评价标准。该结论有助于建立一个有效的波动率模型预测框架。
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