Let's face it: Quantifying the impact of nonverbal communication in FOMC press conferences

• 成果类型: Article
• 署名作者: Curti, Filippo; Kazinnik, Sophia
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - Richmond
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2023.06.007
• 发表日期: 2023
• 页码: 110-126
• 关键词: central bank communication; Market expectations; behavioral finance; Facial recognition; Video data; Machine Learning

摘要

When the Fed Chair speaks, investors not only listen, but also watch. To demonstrate this phenomenon, we apply facial recognition analysis to FOMC press conference videos and quantify one of the most important aspects of nonverbal communication-facial expressions. Using minute-level data, we align our nonverbal communication measure with a set of financial assets to estimate the impact of the Fed Chairs' facial expressions on investor expectations. We find that investors adversely react to negative expressions revealed during the press conference, even when controlling for the verbal component of the press conference and other explanatory variables. (c) 2023 Elsevier B.V. All rights reserved.