政策公告对波动性影响的分类研究
On Classifying the Effects of Policy Announcements on Volatility
摘要：
围绕大衰退的金融动荡要求中央银行进行前所未有的干预：非常规政策影响到经济的各个领域，包括股票市场波动。为了评估这种影响，包括马尔可夫转换动态在最近的乘法误差模型，我们提出了一个基于模型的分类的日期中央银行的公告，以区分的情况下，公告意味着增加或减少波动性，或没有效果。详细地说，我们提出了两个平滑的概率为基础的分类方法，作为一个产品的模型估计，这提供了非常相似的结果，从一个经典的k-均值聚类过程。对四个欧元区市场波动序列的应用表明，144个欧洲中央银行公告的成功分类。
英文摘要：
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.
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