Title: Volatility jumps and the classification of monetary policy announcements
Authors: Giampiero Gallo - NYU in Florence (Italy)
Demetrio Lacava - Luiss University (Italy) [presenting]
Edoardo Otranto - University of Messina (Italy)
Abstract: In the last two decades, due to many endogenous and/or exogenous events (e.g. subprime mortgage crisis, high inflation, and the Covid-19 pandemic), even more frequent actions have been taken by many central banks, with direct implications on market volatility. Taking the example of the Federal Reserve (FED), we propose a new model-based classification of monetary policy announcements according to whether they cause a jump rather than a reduction of volatility. The proposed model (the GAS-AMEM with jumps) - which combines the distinctive features of the Generalized Autoregressive Score (GAS) model along with those of the Multiplicative Error Model (MEM) - provides an accurate classification method, while preserving the flexibility and the ability of the classical MEM of reproducing the well-known stylized facts characterizing volatility. Focusing on a short window around each FED's communication, we isolate the impact of monetary announcements by excluding any contamination carried by relevant events that may occur within a business day. By relying on both the S\&P500 stock index and specific firms, we classify FED's announcements according to their effect on the stock market as a whole, on the one hand, and on specific sectors of the market, on the other hand.