On classifying the effects of policy announcements on volatility

Abstract

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.

Network log-ARCH models for forecasting stock market volatility

“…see Otranto, 2008;D'Urso et al, 2016), Multiplicative Error Model (e.g. see Gallo et al, 2021), or score-driven models (e.g. see Cerqueti et al, 2021Cerqueti et al, , 2022.…”