Separating accuracy from forecast certainty: A modified miscalibration measure

Doron Sonsino, Yaron Lahav, Amir Levkowitz

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations


Interval forecasting tasks are commonly used to test for forecastoverconfidence. Pointing at deficiencies of the methodology, we advance a modified assignment, where subjects provide point predictions and assess the likelihood of return falling within small intervals around their estimates. The difference between the subjective likelihood assessments and the realized hit rates is advanced as an improved forecast-overprecision measure. Over three incentivized studies, 163 of 195 participants overestimate their hit rates, and a closer look at the data illustrates that inaccuracy and excessive certainty act as distinct sources of overprecision. Applications where the adapted task may prove more powerful than standard interval forecasting are discussed.

Original languageEnglish
Title of host publicationBehavioral Finance
Subtitle of host publicationA Novel Approach
PublisherWorld Scientific Publishing Co.
Number of pages19
ISBN (Electronic)9789811229251
StatePublished - 1 Jan 2020


  • Forecast-accuracy
  • Interval forecasting
  • Miscalibration
  • Overconfidence
  • Trading

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (all)
  • Business, Management and Accounting (all)


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