Measurement Error and Nonlinearity in the Earnings-Returns Relation
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.Get Access
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.
- Abarbanell, J.S., W.N. Lanen and R.E. Verrechia, “Analysts' forecasts as proxies for investor beliefs in empirical research.” Journal of Accounting and Economics 20, 31–60, (1996).
- Abdel-khalik, A.R. “Specification problems with information content of earnings: revisions and rationality of expectations and self-selection bias.” Contemporary Accounting Research 7, 142–172 (1990).
- Ball, R., S.P. Kothari and R.L. Watts, “Economic determinants of the relation between earnings changes and stock returns.” The Accounting Review 68, 622–638, (1993).
- Beneish, M.D., “Stock prices and the dissemination of analysts' recommendations.” Journal of Business 64, 393–416, (1991).
- Beneish, M.D. and C.R. Harvey, “A new approach to estimating the earnings response function.” Working paper, Duke University, (1990).
- Bernard, V.L. and J.K. Thomas, “Post-announcement drift: Delayed price response or risk premium?” Journal of Accounting Research 27, 1–36, (1989).
- Brown, L.D., “Earnings Forecasting Research: Its Implications for Capital Markets Research.” Journal of International Forecasting 9, 295–320, (1993).
- Brown, L., P. Griffin, R. Hagerman, and M. Zmijewski, “Security analyst superiority relative to univariate time series models in forecasting quarterly earnings.” Journal of Accounting and Economics 9, 61–87, (1987).
- Cacoullos, T., “Estimation of a multivariate density.” Annals of the Institute of Mathematical Statistics 18, 176–189, (1996).
- Chambers, A.E. and Penman, S.H., “Timeliness of reporting and the stock price reaction to earnings announcements.” Journal of Accounting Research 22, 21–47, (1984).
- Cheng, C.S.A., W.S. Hopwood and J.C. McKeown, “Nonlinearity and specification problems in unexpected earnings response regression model.” The Accounting Review 67, 379–398, (1992).
- Cleveland, W.S. and S.J. Devlin, “Locally weighted regression: An approach to regression analysis by local fitting.” Journal of the American Statistical Assocation 83, 596–609, (1988).
- Collins, D.W. and S.P. Kothari, “An analysis of intertemporal and cross-sectional determinants of earnings response coefficients.” Journal of Accounting and Economics 11, 143–181, (1989).
- Cornell, B., and Landsman, W.R., “Security price response to quarterly earnings announcements and analysts' forecast revisions.” The Accounting Review 64, 680–692, (1989).
- Christie, A.A., “On cross-sectional analysis in accounting research” Journal of Accounting and Economics 9, 231–258, (1987).
- Das, S. and B. Lev, “Nonlinearity in the returns-earnings relation: Tests of alternative specification and explanations.” Contemporary Accounting Review 11, 353–379, (1994).
- Easton, P. and M. Zmijewski, “Cross-sectional variation in the stock market response to accounting earnings announcements.” Journal of Accounting and Economics 11, 117–141, (1989).
- Fama, E.F. and K.R. French, “Business conditions and expected returns on stocks and bonds.” Journal of Financial Economics 25, 23–50, (1989).
- Fama, E.F. and K.R. French, “The cross section of expected returns.” Journal of Finance 42, 427–466, (1992).
- Freeman, R.N. and S. Tse, “A nonlinear model of security price responses to unexpected earnings.” Journal of Accounting Research 30, 185–209, (1992).
- Fukunaga, K., Introduction to statistical pattern recognition, New York: Academic Press, 1972.
- Gallant, A.R., “On the bias in flexible functional forms and an essentially unbiased form: The Fourier flexible form.” Journal of Econometrics 15, 211–224, (1981).
- Granger, C.W.J. and P. Newbold, Forecasting economic time series, New York: Academic Press, 1986.
- Hansen, L.P., “Large sample properties of generalized method of moment estimators.” Econometrica 50, 1029–1054, (1982).
- Härdle, W., Applied Nonparametric Regression. Cambridge University Press, 1990.
- Hughes, J.S. and Ricks, W.E., “Association between forecast errors and excess returns near to earnings announcements.” The Accounting Review 62, 158–175, (1987).
- Keim, D.B. and R.F. Stambaugh, “Predicting returns in the bond and stock market.” Journal of Financial Economics 17, 357–390, (1986).
- Lang, M., “Time-varying stock price responses to earnings induced by uncertainty about the time-series properties of earnings.” Journal of Accounting Research 27, 229–257, (1991).
- Lev, B., “On the usefulness of earnings and earnings research: Lessons and directions from two decades of empirical research.” Journal of Accounting Research Supplement 27, 153–192, (1989).
- Mizrach, B., “Multivariate nearest-neighbour forecasts of EMS exchange rates.” Journal of Applied Econometrics 7, S151–S163, (1992a).
- Mizrach, B., Forecast comparison in L2, Working paper, Federal Reserve Bank of New York, (1992b).
- Pagan, A. and G.W. Schwert, “Alternative models for conditional stock volatility.” Journal of Econometrics 45, 267–290, (1990).
- Parzen, E., “On the estimation of probability density and mode.” Annals of Mathematical Statistics 33, 1065–1076, (1962).
- Philbrick, D.R. and W.E. Ricks, “Using Value Line and IBES analysts forecasts in accounting research.” Journal of Accounting Research 29, 397–415, (1991).
- Schipper, K., “Analysts' forecasts.” Accounting Horizons 5, 105–121, (1991).
- Silverman, B.W., Density estimation for statistics and data analysis, London: Chapman and Hall, 1986.
- White, H., “A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity.” Econometrica 48, 817–838, (1980).
- Measurement Error and Nonlinearity in the Earnings-Returns Relation
Review of Quantitative Finance and Accounting
Volume 11, Issue 3 , pp 219-247
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- measurement error
- unexpected earnings
- nonparametric estimation
- Industry Sectors