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On Classifying the Effects of Policy Announcements on Volatility

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  • Giampiero M. Gallo
  • Demetrio Lacava
  • Edoardo Otranto

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 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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  • Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Papers 2011.14094, arXiv.org, revised Feb 2021.
    • Handle: RePEc:arx:papers:2011.14094
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    1. G.M. Gallo & D. Lacava & E. Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Working Paper CRENoS 202306, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.

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