Using Twitter to Predict Markets and Monetary Policy
- By Sam van de Schootbrugge
- 5 min read
Summary
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- A new FEDS working paper uses Twitter chatter to build a measure of credit and financial market sentiment.
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- The authors use Keyword Clustering alongside FinBERT to assign sentiment scores to tweets. They then average over tweets to create sentiment indices at different frequencies.
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- Their monthly index correlates highly with corporate bond spreads and other price- and survey-based measures of financial conditions.
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- At higher frequencies, the index can predict next-day stock market returns and forecast changes in the US monetary policy stance.
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