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Review of Financial Studies Vol. 37 No. 5 2024

Noise in Expectations: Evidence from Analyst Forecasts

Tim de Silva1; David Thesmar2

1 MIT Sloan School of Management, USA · 2 MIT Sloan School of Management , USA, NBER, and CEPR

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.

DOI
10.1093/rfs/hhad091
Volume
37
Issue
5
Pages
1494-1537
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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