A new hedging hypothesis regarding prediction interval formation in stock price forecasting

Dan Zhu, Qingwei Wang and John Goddard

Journal of Forecasting, 2022, vol. 41, issue 4, 697-717

Abstract: We propose and test a simple hedging hypothesis for prediction interval formation in stock price forecasting. In the presence of uncertainty, forecasters hedge their forecasts by adjusting the bounds of the prediction interval in a way that reflects their forecast of the average forecast of others. This hypothesis suggests a positive relationship between the belief wedge, defined as the difference between the subject's forecast of the average forecast of others and the subject's own point forecast, and the asymmetry of the prediction interval. Empirical support for the hedging hypothesis is drawn from two in‐class surveys, an experiment, and a large survey of professional analysts' forecasts of future stock prices.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1002/for.2830

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:41:y:2022:i:4:p:697-717

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().