Volatility jumps and the classification of monetary policy announcements

TL;DR

This paper introduces the AJM model to analyze how Federal Reserve monetary announcements influence intradaily volatility jumps, providing a new classification method for these impacts.

Contribution

The paper develops the Asymmetric Jump Multiplicative Error Model (AJM) to specifically capture volatility jumps and classifies monetary policy announcements based on their effects on these jumps.

Findings

AJM effectively isolates volatility jumps caused by monetary announcements.

The classification distinguishes different impacts of Fed communications on volatility.

Model-based approach improves understanding of market reactions to policy signals.

Abstract

Central Banks interventions are frequent in response to exogenous events with direct implications on financial market volatility. In this paper, we introduce the Asymmetric Jump Multiplicative Error Model (AJM), which accounts for a specific jump component of volatility within an intradaily framework. Taking the Federal Reserve (Fed) as a reference, we propose a new model-based classification of monetary announcements based on their impact on the jump component of volatility. Focusing on a short window following each Fed's communication, we isolate the impact of monetary announcements from any contamination carried by relevant events that may occur within the same announcement day.