Analysts' Weighting of Private and Public Information

49 Pages Posted: 20 Jul 2003

See all articles by Qi Chen

Qi Chen

Duke University - Fuqua School of Business

Wei Jiang

Columbia Business School - Finance and Economics; ECGI; NBER

Multiple version iconThere are 3 versions of this paper

Date Written: June 2003


This paper provides empirical evidence on factors affecting analysts' weighting of private and public information when they forecast firm earnings. We examine the relevance of competing explanations for the deviations of analysts' actual weighting from their efficient weighting (i.e., the optimal statistical weights on available information to form rational expectations about the underlying earnings). We find strong evidence supporting the strategic mis-weighting hypothesis (which attributes deviations from efficient weighting to analysts' rational and optimal response to economic incentives). We find weak evidence supporting the information externality hypothesis (which posits that analysts are rational but lack knowledge about the information underlying other analysts' forecasts). We find little evidence supporting the unintentional mistake hypothesis (which posits that mis-weighting is due to analysts' behavioral biases).

Keywords: analyst forecast, efficient weighting, over- and under-weighting, overconfidence, optimistic bias

JEL Classification: G14, G24, G29, J44

Suggested Citation

Chen, Qi and Jiang, Wei, Analysts' Weighting of Private and Public Information (June 2003). Available at SSRN: or

Qi Chen

Duke University - Fuqua School of Business ( email )

Box 90120
Durham, NC 27708-0120
United States
(919) 660-7753 (Phone)

Wei Jiang (Contact Author)

Columbia Business School - Finance and Economics ( email )

3022 Broadway
New York, NY 10027
United States
(212) 854-5553 (Phone)

ECGI ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels

NBER ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics