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Erscheinungsjahr: 
2024
Quellenangabe: 
[Journal:] Journal of Business Economics [ISSN:] 1861-8928 [Volume:] 95 [Issue:] 2 [Publisher:] Springer Berlin Heidelberg [Place:] Berlin/Heidelberg [Year:] 2024 [Pages:] 467-497
Verlag: 
Springer Berlin Heidelberg, Berlin/Heidelberg
Zusammenfassung: 
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.
Schlagwörter: 
Overconfidence
Overprecision
Miscalibration
Replication
Bayesian learning
Financial forecasting
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Sonstige Angaben: 
D03;D83;D84;G17;G41
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Dokumentart: 
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Dokumentversion: 
Published Version
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