  We build a new measure of credit and financial market sentiment using Natural
Language Processing on Twitter data. We find that the Twitter Financial
Sentiment Index (TFSI) correlates highly with corporate bond spreads and other
price- and survey-based measures of financial conditions. We document that
overnight Twitter financial sentiment helps predict next day stock market
returns. Most notably, we show that the index contains information that helps
forecast changes in the U.S. monetary policy stance: a deterioration in Twitter
financial sentiment the day ahead of an FOMC statement release predicts the
size of restrictive monetary policy shocks. Finally, we document that sentiment
worsens in response to an unexpected tightening of monetary policy.
