As a response to the Great Recession, many central banks resorted to unconventional monetary policies, in the form of a balance sheet expansion. Our research aims at analyzing the impact of the ECB policies on stock market volatility in four Eurozone countries (France, Germany, Italy and Spain) within the Multiplicative Error Model framework. We propose a model which allows us to quantify the part of market volatility depending directly on unconventional policies by distinguishing between the announcement the implementation effects. While we observe an increase in volatility on announcement days, we find a negative implementation effect, which causes a remarkable reduction in volatility in the long term. A Model Confidence Set approach finds how the forecasting power of the proxy improves significantly after the policy announcement; a multi-step ahead forecasting exercise estimates the duration of the effect, and, by shocking the policy variable, we are able to quantify the reduction in volatility which is more marked for debt-troubled countries.

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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 in-crease or a decrease in volatility, or no effect. In detail, we propose two naïve classification methods, obtained as a byproduct 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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