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Measurement Error and Nonlinearity in the Earnings-Returns Relation

Measurement Error and Nonlinearity in the Earnings-Returns Relation There is a long history of research which examines the relation between unexpected earnings and unexpected returns on common stock. Early literature used simple linear regression models to describe this relation. Recently, a number of authors have proposed nonlinear models. These authors find that the earnings-returns relation is approximately linear for small changes but is 'S'-shaped globally. However, unexpected earnings are generated by the sum of a measurement error and a true earnings innovation, so the apparent nonlinearity could be an artifact of nonlinearity in the measurement errors. Using a research design that minimizes the presence of measurement errors, we provide evidence consistent with the hypothesis that measurement errors contribute to the nonlinearities in the earnings-returns relation. While we are not suggesting that the earnings-returns relation is linear, our evidence suggests that there is no advantage to using a nonlinear model for large firms that are widely followed by analysts. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

Measurement Error and Nonlinearity in the Earnings-Returns Relation

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References (40)

Publisher
Springer Journals
Copyright
Copyright © 1998 by 1998 Kluwer Academic Publishers
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
DOI
10.1023/A:1008362715659
Publisher site
See Article on Publisher Site

Abstract

There is a long history of research which examines the relation between unexpected earnings and unexpected returns on common stock. Early literature used simple linear regression models to describe this relation. Recently, a number of authors have proposed nonlinear models. These authors find that the earnings-returns relation is approximately linear for small changes but is 'S'-shaped globally. However, unexpected earnings are generated by the sum of a measurement error and a true earnings innovation, so the apparent nonlinearity could be an artifact of nonlinearity in the measurement errors. Using a research design that minimizes the presence of measurement errors, we provide evidence consistent with the hypothesis that measurement errors contribute to the nonlinearities in the earnings-returns relation. While we are not suggesting that the earnings-returns relation is linear, our evidence suggests that there is no advantage to using a nonlinear model for large firms that are widely followed by analysts.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Oct 6, 2004

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