Identifying the influence of market sentiment on market anomalies

Thomson Reuters News Analytics provides automated sentiment and linguistic analytics on financial news, and using Thomson Reuters News Analytics we construct a US market sentiment index from corporate Reuters news sentiment.

Following recent literature identifying the pervasive influence of market sentiment on market anomalies and on the pricing of risk factors, we use this US market sentiment index to demonstrate the influence of market sentiment on the post-earnings announcement drift anomaly, the accruals anomaly, and market risk premium.


We show that the classic risk-return trade-off of the Capital Asset Pricing Model (CAPM) holds following negative market sentiment periods, whereas the underperformance of high-risk securities known as the low-volatility anomaly holds following positive market sentiment periods. Thus, we propose a dynamic methodology which accepts either the CAPM or the low-volatility anomaly following periods of negative or positive market sentiment, respectively.

We further demonstrate the influence of market sentiment on the earnings revisions anomaly. As an application we present a monthly quant factor timing strategy driven by market sentiment, and improve upon this strategy by implementing the above, proposed dynamic methodology.

This whitepaper covers:

  • Market-Wide News Sentiment
  • Post-Earnings Announcement Drift Anomaly
  • Accruals Anomaly
  • Market Beta
  • Earnings Revisions Anomaly
  • Application: Quant Factor Timing
  • Future Directions

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