On Classifying the Effects of Policy Announcements on Volatility
| Autor: | Demetrio Lacava, Giampiero M. Gallo, Edoardo Otranto |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Estimation
General Economics (econ.GN) Markov chain Applied Mathematics European central bank 02 engineering and technology Markov switching model Unconventional monetary policies Stock market volatility Multiplicative error model Smoothed probabilities Model–based clustering Theoretical Computer Science Great recession FOS: Economics and business Artificial Intelligence Order (exchange) Central bank 020204 information systems 0202 electrical engineering electronic engineering information engineering Econometrics Economics 020201 artificial intelligence & image processing Volatility (finance) General Finance (q-fin.GN) Cluster analysis Quantitative Finance - General Finance Software Economics - General Economics |
| Popis: | 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. 23 pages, 2 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|