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ANSWERING THE SKEPTICS: YES, STANDARD VOLATILITY MODELS DO PROVIDE ACCURATE FORECASTS*

International Economic Review(1998)SCI 3区

Northwestern Univ

Cited 4463|Views37
Abstract
A voluminous literature has emerged for modeling the temporal dependencies in financial market Volatility using ARCH and stochastic volatility models. While most of these studies have documented highly significant in-sample parameter estimates and pronounced intertemporal volatility persistence, traditional ex-post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts. Contrary to this contention, we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications. New methods for improved ex-post interdaily volatility measurements based on high-frequency intradaily data are also discussed.
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要点】:本文通过对现有金融市场波动性模型的研究,证明了标准波动性模型在实际应用中能够提供准确的日内波动性预测,反驳了传统评价标准认为这些模型预测效果不佳的观点。

方法】:作者采用ARCH和随机波动性模型来分析金融市场的波动性时间依赖性,并提出了一种新的基于高频日内数据来改进后验日内波动性测量的方法。

实验】:文中未具体说明实验细节和数据集名称,但提到通过新方法对模型进行评估,得到了对潜在波动性因子的准确日内预测结果。