FMPAF: How Do Fed Chairs Affect the Financial Market? A Fine-grained Monetary Policy Analysis Framework on Their Language

TL;DR

This paper introduces the Fine-Grained Monetary Policy Analysis Framework (FMPAF), a multimodal approach that combines fine-tuned large language models and acoustic analysis with regression to quantify how Fed Chairs' communications influence financial markets. By applying sentence-level linguistic and paralinguistic signals to a local-projection regression, the authors show that policy sentiment can materially affect SPY returns and the policy rate, with negligible FX impact in the U.S. and detectable cross-border spillovers to China and the EU. Domain-specific fine-tuning and granular data improve predictive power over coarse or generic sentiment methods, and text-based measures outperform audio-only signals due to data limitations. The findings highlight how central bank communication transmits through international markets and underscore the value of fine-grained, cross-border sentiment analysis for monetary policy transmission research.

Abstract

The effectiveness of central bank communication is a crucial aspect of monetary policy transmission. While recent research has examined the influence of policy communication by the chairs of the Federal Reserve on various financial variables, much of the literature relies on rule-based or dictionary-based methods in parsing the language of the chairs, leaving nuanced information about policy stance contained in nonverbal emotion out of the analysis. In the current study, we propose the Fine-Grained Monetary Policy Analysis Framework (FMPAF), a novel approach that integrates large language models (LLMs) with regression analysis to provide a comprehensive analysis of the impact of the press-conference communications of chairs of the Federal Reserve on financial markets. We conduct extensive comparisons of model performance under different levels of granularity, modalities, and communication scenarios. Based on our preferred specification, a one-unit increase in the sentiment score is associated with an increase of the price of S\&P 500 Exchange-Traded Fund by approximately 500 basis points, a 15-basis-point decrease in the policy interest rate, while not leading to a significant response in exchange rates.

Figures (7)

• Figure 1: Overview of our proposed Policy Analysis Framework
• Figure 2: Response of SPY to Sentiment: Different Scale
• Figure 3: Sentiment Analysis Based on Data of Different Granularities
• Figure 4: Sentiment Analysis Based on Positive/Negative Labels
• Figure 5: Sentiment Analysis for Press Conference and Monetary Policy Hearings.