论文标题
在分类政策公告对波动性的影响
On Classifying the Effects of Policy Announcements on Volatility
论文作者
论文摘要
围绕大萧条的金融动荡要求中央银行前所未有的干预：非常规政策影响了经济中各个地区，包括股市波动。为了评估这种效果，通过在最近的乘法错误模型中包括马尔可夫切换动态，我们提出了基于模型的基于模型的分类中央银行公告的日期，以区分公告意味着增加或减少波动性或无效的情况。详细介绍，我们提出了两种基于概率的平滑分类方法，这些方法作为模型估计的产物获得了，它们与来自经典K-均值聚类过程的结果非常相似。四个欧元区市场波动性系列的应用程序显示了144个欧洲中央银行公告的成功分类。
The financial turmoil surrounding the Great Recession called for unprecedented intervention by Central Banks: unconventional policies affected various areas in the economy, including stock market volatility. In order to evaluate such effects, by including Markov Switching dynamics within a recent Multiplicative Error Model, we propose a model--based classification of the dates of a Central Bank's announcements to distinguish the cases where the announcement implies an increase or a decrease in volatility, or no effect. In detail, we propose two smoothed probability--based classification methods, obtained as a by--product of the model estimation, which provide very similar results to those coming from a classical k--means clustering procedure. The application on four Eurozone market volatility series shows a successful classification of 144 European Central Bank announcements.
