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Research Question

Real-Time Measure of Analyst Beliefs Jason V. Chen University of Michigan Venky Nagar University of Michigan Jordan Schoenfeld University of Michigan. Research Question. Analysts provide EPS forecasts, price targets, and stock recommendations to capital market participants

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Research Question

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  1. Real-Time Measure of Analyst BeliefsJason V. ChenUniversity of MichiganVenky NagarUniversity of MichiganJordan SchoenfeldUniversity of Michigan

  2. Research Question • Analysts provide EPS forecasts, price targets, and stock recommendations to capital market participants • However, these outputs are not always timely because analysts may share them with clients prior to their public release • Does a timely measure of analyst beliefs demonstrate the information intermediary role of analysts?

  3. Research Design • Setting: earnings conference calls • Real-time environment where we can learn analyst beliefs for the first time after the earnings disclosure • Predictions: our measure of analyst beliefs predicts • Analyst revisions of EPS forecasts, price targets, and stock recommendations • Abnormal returns • Institutional investor abnormal buying

  4. Belief Construct • Ratio of positive words to negative words, which we refer to as tone Manager tone measures include words spoken by the CEO, CFO, and COO

  5. Construct Example

  6. Table 1 – Panel C * Indicates significance at the 5% level ^ Financially oriented sentences calculated using Matsumoto et al. (2011)’s dictionary

  7. Table 1 – Panel D – Sample Selection • 18,814 calls from Thomson Reuters for years 2002-2008

  8. Table 2 – Covariates of Analyst Tone

  9. Preview of Findings • A one standard deviation increase in analyst tone is followed by: • a 4.56% increase in the analyst consensus EPS forecast from day 0 to day 60 • a 1.44% increase in the analyst consensus price target from day 0 to day 60 • a 0.013 more favorable analyst stock recommendation level from day 0 to day 60 • a 0.8% increase in abnormal returns over days (0, +1) • abnormal institutional investor buying

  10. Table 3 – Future Changes in Analyst Outputs

  11. Table 4 – Abnormal Returns

  12. Table 4 – Abnormal Returns

  13. Cross-Sectional Tests • Analysts are more influential: • For firms with more institutional investors • When there is more new information to interpret • I.e., management’s earnings disclosure has a larger unexpected component

  14. Table 5 – Abnormal Return Interaction Effects

  15. Institutional Investor Trading • Analyst tone predicts institutional investor abnormal buying

  16. Abnormal Institutional Investor Buying (AIB) Measure • Abel Noser institutional investor trading database • AIB is calculated using a control window approach as follows: • AIB on the conference call date would therefore be:

  17. Table 6 – Abnormal Institutional Investor Buying

  18. Conclusions • Timely measures of analyst beliefs demonstrate their role as important information intermediaries • Analysts are more influential: • for firms with more institutional investors; • when there is more new information to interpret

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