Researchers have carefully studied post-meeting central bank communication and have found that it often moves markets, but they have paid less attention to the more frequent central bankers’ speeches. We create a novel dataset of US Federal Reserve speeches and develop supervised multimodal natural language processing methods to identify how monetary policy news affect financial volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that news in central bankers’ speeches can help explain volatility and tail risk in both equity and bond markets. Our results challenge the conventional view that central bank communication primarily resolves uncertainty and indicate that markets attend to speech signals more closely during abnormal GDP and inflation regimes. Our analysis also reveals that the views of Fed members (i.e., hawkish versus dovish) tend to play a marginal role in terms of the strength of the speech signals. Looking at the speeches by the Fed Chair, we find that the Chair signals produce a larger tail risk compared to non-Chair signals, and the estimated magnitude of the market responses depends on the position of the officials (i.e., the Fed Chair or other Fed member).
https://doi.org/10.20955/wp.2023.013
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