More than Words: Twitter Chatter and Financial Market Sentiment

Andrea Ajello, Diego Silva, Travis Adams and Francisco Vazquez-Grande
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Francisco Vazquez-Grande: https://www.federalreserve.gov/econres/francisco-vazquez-grande.htm

No 2023-034, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: 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.

Keywords: Financial Market Sentiment; Monetary policy; Natural Language Processing; Stock Returns; Twitter (search for similar items in EconPapers)
JEL-codes: C55 C58 D53 E52 (search for similar items in EconPapers)
Pages: 36 p.
Date: 2023-05-23
New Economics Papers: this item is included in nep-big, nep-cba, nep-fmk and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2023-34

DOI: 10.17016/FEDS.2023.034

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