Analyst Misinterpretation of Tones of Earnings Calls

Do analysts/investors predictably and exploitably misinterpret tones of earnings calls? In their October 2025 paper entitled “Do Investors Get It Right? Reaction Bias to Earnings Calls”, Zhenzhen Fan and Fred Liu study interactions between textual information in earnings conference calls and analyst revisions to their next-quarter earnings forecasts. Specifically, they:

• For each stock and each following analyst: (1) link call transcripts to the closest pre-call and post-call analyst forecasts, and (2) measure analyst reaction as the fraction of the pre-announcement forecast error corrected in the post-announcement revision.
• Use Shapley values to assess the contribution of each model feature to predictive power.
• Across stocks and earnings calls, use a random forest model to test whether earnings call transcripts predict direction and magnitude of reaction bias. Use seven rolling years of the sample for model training/validation and test predictive accuracy each next year.
• Each month sort stocks into fifths (quintiles) based on predicted reaction bias and form a value-weighted, monthly rebalanced portfolio that is long stocks with the highest signal and short the stocks with the lowest. Keep a stock within its quintile until the end of the month of its next earnings announcement.

Using earnings conference call transcripts, analyst earnings forecasts, actual earnings and monthly stock return data during 2006 through 2023, they find that:

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