Data and Code for: The Voice of Monetary Policy

We develop a deep learning model to detect emotions embedded in press conferences after the Federal Open Market Committee meetings and examine the influence of the detected emotions on financial markets. We find that, after controlling for the Fed’s actions and the sentiment in policy texts, a positive tone in the voices of Fed chairs leads to significant increases in share prices. Other financial variables also respond to vocal cues from the chairs. Hence, how policy messages are communicated can move the financial market. Our results provide implications for improving the effectiveness of central bank communications.本研究构建深度学习模型，以识别联邦公开市场委员会（Federal Open Market Committee，FOMC）会议后新闻发布会中蕴含的情绪，并探究此类检测到的情绪对金融市场的影响。研究发现，在控制美联储政策行动与政策文本情绪倾向后，美联储主席发言中的积极语调会显著推高股价。其余金融变量亦会对主席的语音信号作出响应。由此可见，政策信息的传递方式能够影响金融市场走势。本研究结果为提升中央银行沟通的有效性提供了启示。