Answering the skeptics: Yes, standard volatility models do provide accurate forecasts
Answering the skeptics: Yes, standard volatility models do provide accurate forecasts
复制标题
DOI：
10.2307/2527343
复制
发表时间：
1998-11-01
影响因子：
1.5
通讯作者：
Bollerslev, T
中科院分区：
文献类型：
--
作者：
Andersen, TG;Bollerslev, T
大量的文献已经出现了建模的时间依赖性，金融市场波动性的随机波动模型。虽然大多数这些研究都记录了高度显着的样本内参数估计和显着的跨期波动持续性，传统的事后预测评价标准表明，该模型提供了看似穷人的波动预测。相反，这种说法，我们表明，波动率模型产生惊人的准确的每日预测的潜在波动率的因素，将在大多数金融应用的兴趣。本文还讨论了基于高频日内数据的改进的事后日内波动率测量方法。
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.