Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/323464 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Business Economics [ISSN:] 1861-8928 [Volume:] 95 [Issue:] 2 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2024 [Pages:] 467-497
Publisher: 
Springer, Berlin, Heidelberg
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.
Subjects: 
Overconfidence
Overprecision
Miscalibration
Replication
Bayesian learning
Financial forecasting
JEL: 
D03
D83
D84
G17
G41
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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