A1347
Title: More than words: Twitter chatter and financial market sentiment
Authors: Andrea Ajello - Board of Governors of the Federal Reserve System (United States) [presenting]
Abstract: A new credit and financial market sentiment measure is built using natural language processing on Twitter data. The Twitter financial sentiment index (TFSI) correlates highly with corporate bond spreads and other price- and survey-based measures of financial conditions. It is documented that overnight Twitter financial sentiment helps predict next-day stock market returns. Most notably, it is shown 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, it is documented that sentiment worsens in response to an unexpected tightening of monetary policy.
