Learning to be overprecise

Christoph Merkle () and Philipp Schreiber ()
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Christoph Merkle: Aarhus University BSS
Philipp Schreiber: Esslingen University

Journal of Business Economics, 2025, vol. 95, issue 2, No 10, 467-497

Abstract: Abstract We replicate and extend two studies on the dynamics of overconfidence among financial professionals. Using 20 years of data from the ZEW Financial Market Survey with over 40,000 individual forecasts of confidence intervals, we document that participants are overprecise during the entire time period with no evidence of learning on the aggregate. We confirm that professionals update in a Bayesian manner after hits and misses by contracting or expanding their confidence intervals, respectively. However, this updating is insufficient to reach proper calibration. We cannot confirm other predictions of a Bayesian model. An explanation based on self-attribution bias fits the data better.

Keywords: Overconfidence; Overprecision; Miscalibration; Replication; Bayesian learning; Financial forecasting (search for similar items in EconPapers)
JEL-codes: D03 D83 D84 G17 G41 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11573-024-01203-w

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