DP15932 The Voice of Monetary Policy
We develop a deep learning model to detect emotions embedded in press conferences after the meetings of the Federal Open Market Committee 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, positive tone in the voices of Fed Chairs leads to statistically significant and economically large increases in share prices. In other words, how policy messages are communicated can move the stock market. In contrast, the bond market appears to take few vocal cues from the Chairs. Our results provide implications for improving the effectiveness of central bank communications.