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

Abstract

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.
Pages283-301
Number of pages19
ISBN (Electronic)9789811229251
DOIs
StatePublished - 1 Jan 2020

Keywords

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

Fingerprint

Dive into the research topics of 'Separating accuracy from forecast certainty: A modified miscalibration measure'. Together they form a unique fingerprint.

Cite this