Work

Robust Measures of Earnings Surprises

Year: 2018

Type: article

Abstract: 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.

Source: The Journal of Finance

DOI: 10.1111/jofi.12746

Authors: CHIN‐HAN CHIANG, WEI DAI, JIANQING FAN, HARRISON HONG, JUN TU

Institutions: Seoul National University, Princeton University, World Bank Group, Columbia University, Singapore Management University, Capital University of Economics and Business

Language: English

Topic: Financial Markets and Investment Strategies

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W3123645019

FWCI: 3.959

Cites: 36

Cited by: 41

Related to: 10