Noise in Expectations: Evidence from Analyst Forecasts

Tim de Silva and David Thesmar

The Review of Financial Studies, 2024, vol. 37, issue 5, 1494-1537

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.

Keywords: G17; G24; G40 (search for similar items in EconPapers)
Date: 2024
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