Journal of Finance Vol. 74 No. 2 2019

Robust Measures of Earnings Surprises

Chin-Han Chiang; WEI DAI; Jianqing Fan; Harrison Hong; Jun Tu^1,2,3

¹ Institute of Semitic Studies · ² Financial Management Association International · ³ Singapore Management University

Abstract

Event studies of market efficiency measure earnings surprises using the consensus error ( CE ), given as actual earnings minus the average professional forecast. If a subset of forecasts can be biased, the ideal but difficult to estimate parameter‐dependent alternative to CE is a nonlinear filter of individual errors that adjusts for bias. We show that CE is a poor parameter‐free approximation of this ideal measure. The fraction of misses on the same side ( FOM ), which discards the magnitude of misses, offers a far better approximation. FOM performs particularly well against CE in predicting the returns of U.S. stocks, where bias is potentially large.

DOI

10.1111/jofi.12746

Volume

74

Issue

2

Pages

943-983

Language

en

Sources

bibtex:phds-export.bib openalex crossref

Cite

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