Differential earnings response coefficients to accounting information: The case of revisions of financial analysts' forecasts.

Persistent Link:
http://hdl.handle.net/10150/184712
Title:
Differential earnings response coefficients to accounting information: The case of revisions of financial analysts' forecasts.
Author:
Guo, Miin Hong.
Issue Date:
1989
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation extends previous studies on firms' differential earnings response coefficients. It provides further theoretical explanation and empirical evidence for the differential earnings response coefficients across firms and time. The empirical evidence found by Ball & Brown (1968) that the sign of unexpected earnings is positively correlated with the sign of market reactions is used to improve the control of measurement errors on investors' prior belief. Revisions of financial analysts' forecasts (FAFs) for firms' future earnings per share (EPS) are used as the event information. Both the impact of FAFs quality on investors' earnings belief revision and the mapping from EPS to security price are considered. Investors are assumed to be Bayesians who are homogeneous in belief. They use FAFs as information for making portfolio investment decisions. FAFs with smaller contemporary dispersion relative to the variance of investors' prior belief are considered to have higher quality. It is proposed that investors have stronger faith on the forecasts with higher information quality. A non-normative approach is used to map EPS into security prices. The market price over (expected) earnings ratio (P/E) is used as a linear approximation for the security valuation function. The major advantage of this approach is that non-earnings factors that have price effect on securities are implicitly controlled. The model predicts that ceteris paribus, the earnings response coefficient adjusted for the differential P/E is positively correlated with the quality of FAFs. Cross-sectional and time series samples of 1097 FAFs revisions from Standard & Poor's Earnings Forecaster in the years 1981 to 1985 are used in the empirical test. The empirical results are consistent with the theoretical implication. The quality of FAFs is found to be positively correlated with the P/E adjusted earnings response coefficient at one percent significance level. The results are robust across event day windows, the estimation periods for market model parameters and the price reaction measurements.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Investments -- Mathematical models.; Business forecasting.; Disclosure in accounting.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Business Administration; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Dhaliwal, Dan S.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleDifferential earnings response coefficients to accounting information: The case of revisions of financial analysts' forecasts.en_US
dc.creatorGuo, Miin Hong.en_US
dc.contributor.authorGuo, Miin Hong.en_US
dc.date.issued1989en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation extends previous studies on firms' differential earnings response coefficients. It provides further theoretical explanation and empirical evidence for the differential earnings response coefficients across firms and time. The empirical evidence found by Ball & Brown (1968) that the sign of unexpected earnings is positively correlated with the sign of market reactions is used to improve the control of measurement errors on investors' prior belief. Revisions of financial analysts' forecasts (FAFs) for firms' future earnings per share (EPS) are used as the event information. Both the impact of FAFs quality on investors' earnings belief revision and the mapping from EPS to security price are considered. Investors are assumed to be Bayesians who are homogeneous in belief. They use FAFs as information for making portfolio investment decisions. FAFs with smaller contemporary dispersion relative to the variance of investors' prior belief are considered to have higher quality. It is proposed that investors have stronger faith on the forecasts with higher information quality. A non-normative approach is used to map EPS into security prices. The market price over (expected) earnings ratio (P/E) is used as a linear approximation for the security valuation function. The major advantage of this approach is that non-earnings factors that have price effect on securities are implicitly controlled. The model predicts that ceteris paribus, the earnings response coefficient adjusted for the differential P/E is positively correlated with the quality of FAFs. Cross-sectional and time series samples of 1097 FAFs revisions from Standard & Poor's Earnings Forecaster in the years 1981 to 1985 are used in the empirical test. The empirical results are consistent with the theoretical implication. The quality of FAFs is found to be positively correlated with the P/E adjusted earnings response coefficient at one percent significance level. The results are robust across event day windows, the estimation periods for market model parameters and the price reaction measurements.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectInvestments -- Mathematical models.en_US
dc.subjectBusiness forecasting.en_US
dc.subjectDisclosure in accounting.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineBusiness Administrationen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorDhaliwal, Dan S.en_US
dc.contributor.committeememberSalatka, William K.en_US
dc.contributor.committeememberPfeiffer, Glennen_US
dc.identifier.proquest8919036en_US
dc.identifier.oclc702127252en_US
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