Volatility jumps and the classification of monetary policy announcements

Central Banks interventions are frequent in response to any endogenous and/or exogenous exceptional events (in the last two decades, subprime mortgage crisis, the Covid-19 pandemic, and the recent high inflation), with direct implications on financial market volatility. In this paper, we propose a new model in the class of Multiplicative Error Models (MEM), the Asymmetric Jump MEM (AJM), which accounts for a specific jump component of volatility within an intradaily framework (thirty minute intervals), while preserving the flexibility and the ability of the MEM to reproduce the empirical regularities characterizing volatility. Taking the actions of the US Federal Reserve (Fed) as a reference, we introduce a new model–based classification of monetary policy announcements according to their impact on the jump component of realized volatility. Focusing on a short window following each Fed's communication, we isolate the impact of monetary announcements by excluding any contamination carried by relevant events that may occur within the same announcement day. By considering specific tickers, our classification method provides useful information for both policy makers and investors about the impact of monetary announcements on specific sectors of the market.