Noise in Expectations: Evidence from Analyst Forecasts

Author:

de Silva Tim1,Thesmar David2

Affiliation:

1. MIT Sloan School of Management , USA

2. MIT Sloan School of Management , USA, NBER, and CEPR

Abstract

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.

Publisher

Oxford University Press (OUP)

Subject

Economics and Econometrics,Finance,Accounting

Reference59 articles.

1. Overreaction in Expectations: Evidence and Theory;Afrouzi;Quarterly Journal of Economics,2023

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3. Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?;Ball;Management Science,2018

4. Inference for high-dimensional sparse econometric models;Belloni;Advances in Economics and Econometrics: Tenth World Congress Volume 3, Econometrics,2011

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