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Coherence and Consistency of Investors' Probability Judgments

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  • David V. Budescu

    ()
    (Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, Illinois 61820)

  • Ning Du

    ()
    (School of Accountancy and Management Information Systems, DePaul University, Chicago, Illinois 60604)

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    Abstract

    This study investigates the quality of direct probability judgments and quantile estimates with a focus on calibration and consistency. The two response modes use different measures of miscalibration, so it is difficult to directly compare their relative (in)accuracy. We employed a more refined within-subject design in which decision makers (DMs) used both response modes to make judgments about a random sample of stocks accompanied by identical information to facilitate comparison between the two judgment methods. DMs judged the probabilities that the stocks will reach a certain threshold, provided lower and upper bounds of these forecasts, and estimated median, 50%, 70%, and 90% confidence intervals of their future prices. We found that the judgments were internally consistent and coherent, but in most cases they were slightly miscalibrated. We used several new methods of analysis that allow for more precise and reliable comparison between the two response modes. We inferred point probability estimates for the target events from the confidence intervals and analyzed them by the same methods applied to binary judgments. Interestingly, when we quantified miscalibration in identical fashion for both methods we did not find evidence of differential levels of miscalibration for the probability judgments and the confidence intervals. We discuss the theoretical and practical implications of these results.

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    File URL: http://dx.doi.org/10.1287/mnsc.1070.0727
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 53 (2007)
    Issue (Month): 11 (November)
    Pages: 1731-1744

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    Handle: RePEc:inm:ormnsc:v:53:y:2007:i:11:p:1731-1744

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    Related research

    Keywords: overconfidence; calibration; confidence intervals; probability judgments; response modes; investment decision; forecasts;

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    Cited by:
    1. Heller, Yuval, 2010. "Overconfidence and risk dispersion," MPRA Paper 25893, University Library of Munich, Germany.
    2. Thomson, Mary E. & Pollock, Andrew C. & Gönül, M. Sinan & Önkal, Dilek, 2013. "Effects of trend strength and direction on performance and consistency in judgmental exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 337-353.
    3. Sonsino, Doron & Regev, Eran, 2013. "Informational overconfidence in return prediction – More properties," Journal of Economic Psychology, Elsevier, vol. 39(C), pages 72-84.
    4. Du, Ning & Budescu, David V. & Shelly, Marjorie K. & Omer, Thomas C., 2011. "The appeal of vague financial forecasts," Organizational Behavior and Human Decision Processes, Elsevier, vol. 114(2), pages 179-189, March.

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