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Judgmental overconfidence: Three measures, one bias?

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  • Fellner, Gerlinde
  • Krügel, Sebastian

Abstract

Overconfidence is used to explain various instances of detrimental decision making. In behavioral economic and finance models, it is usually captured by misperceiving the reliability of signals and results in overweighting private information. Empirical tests of these models often fail to find evidence for the predicted effects of overconfidence. These studies assume, however, that a specific type of overconfidence, i.e. “miscalibration,” captures the underlying trait. We challenge this assumption and borrow the psychological methodology of single-cue probability learning to obtain a direct measure for misperceiving signal reliability. Our findings indicate that the perception of signal precision and measures of miscalibration are unrelated. We thus conclude that in order to test the theoretical predictions of the overconfidence literature in economics and finance, one cannot rely on the well-established miscalibration bias.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Psychology.

Volume (Year): 33 (2012)
Issue (Month): 1 ()
Pages: 142-154

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Handle: RePEc:eee:joepsy:v:33:y:2012:i:1:p:142-154

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Web page: http://www.elsevier.com/locate/joep

Related research

Keywords: Overconfidence; Miscalibration; Signal perception; Cognitive bias;

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References

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Citations

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Cited by:
  1. Lambert, Jérôme & Bessière, Véronique & N’Goala, Gilles, 2012. "Does expertise influence the impact of overconfidence on judgment, valuation and investment decision?," Journal of Economic Psychology, Elsevier, vol. 33(6), pages 1115-1128.
  2. Nguyen, Viet Hoang & Claus, Edda, 2013. "Good news, bad news, consumer sentiment and consumption behavior," Journal of Economic Psychology, Elsevier, vol. 39(C), pages 426-438.
  3. Gelinde Fellner & Sebastian Krügel, 2012. "Judgmental Overconfidence and Trading Activity," Jena Economic Research Papers 2012-057, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  4. Kauko, Karlo & Palmroos, Peter, 2014. "The Delphi method in forecasting financial markets— An experimental study," International Journal of Forecasting, Elsevier, vol. 30(2), pages 313-327.

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