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Noise in Expectations: Evidence from Analyst Forecasts

Resource type
Authors/contributors
Title
Noise in Expectations: Evidence from Analyst Forecasts
Abstract
Analyst forecasts outperform econometric forecasts in the short run but underperform in the long run. We decompose these differences in forecasting accuracy into analysts’ information advantage, forecast bias, and forecast noise. We find that noise and bias strongly increase with forecast horizon, while analysts’ information advantage decays rapidly. A noise increase with horizon generates a mechanical reversal in the sign of the error-revision (Coibion-Gorodnichenko) regression coefficient at longer horizons, independently of over-/underreaction. A parsimonious model with bounded rationality and a noisy cognitive default matches the term structures of noise and bias jointly.
Publication
The Review of Financial Studies
Volume
37
Issue
5
Pages
1494-1537
Date
2024-05-01
Journal Abbr
The Review of Financial Studies
ISSN
0893-9454
Short Title
Noise in Expectations
Accessed
5/1/24, 10:12 AM
Library Catalog
Silverchair
Citation
de Silva, T., & Thesmar, D. (2024). Noise in Expectations: Evidence from Analyst Forecasts. The Review of Financial Studies, 37, 1494–1537.
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