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Investor Behavior and Changes in Accounting Methods

Published online by Cambridge University Press:  19 October 2009

J. Winsen  and
D. Ng
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Extract

Several studies have investigated the reaction of the stock market to a firm's changing its method of accounting for external reporting purposes. By contrast, this study investigates the reaction of proper subsets of the stock market to changes in accounting methods–specifically, the reaction of the set of investors in the common stock of the firm which has changed its accounting measurement rules.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 11 , Issue 5 , December 1976 , pp. 873 - 881
Copyright
Copyright © School of Business Administration, University of Washington 1976

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References

1 See, for example: Archibald, T., “Stock Market Reaction to the Depreciation Switch-Back,” The Accounting Review (January 1972)Google Scholar; Ball, R., “Changes in Accounting Techniques and Stock Prices,” Empirical Research in Accounting (1972)CrossRefGoogle Scholar; Kaplan, R. and Roll, R., “Investor Evaluation of Accounting Information, Some Empirical Evidence,” Journal of Business (April 1972).CrossRefGoogle Scholar

2 Objectives of Financial Statements (A.I.C.P.A., 1973), p. 62.

3 Murray, R., “Let's Not Blame the Institutions,” Financial Analysts Journal (March/April 1974), p. 20.Google Scholar

4 McDonald, J., “Discussion (of The Individual Investor: Attributes and Attitudes')” The Journal of Finance (May 1974).Google Scholar

5 For a summary of evidence consistent with market efficiency see: Fama, E., “Efficient Capital Markets: A Review of Theory and Empirical Work,” The Journal of Finance (May 1970).CrossRefGoogle Scholar

6 Epps, T., “Security Price changes and Transaction Volumes: Theory and Evidence,” American Economic Review (September 1975)Google Scholar; Ng, D., “Accounting Information and Individual Consumption-Investment Decisions: A Volume of Trading Approach” (manuscript, University of California, Berkeley, 1974Google Scholar); Winsen, J., “Investor Behavior and Information,” Journal of Financial and Quantitative Analysis (March 1976).CrossRefGoogle Scholar

See also: Epps, T. and Epps, M., “The Stochastic Depencence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis,” Econometrica (March 1976).CrossRefGoogle Scholar

7 The conditions require continuity of the joint and marginal density functions; see W. Hoeffding, “A Non-Parametric Test of Independence,” The Annals of Mathematical Statistics, Vol. 19. Hoeffding's statistic estimates E(h2) where E is the expectation operator and h is as defined above. The larger the statistic, the less likelihood that the two variables are independent. See also Hollander, M. and Wolfe, D., Nonparametric Statistical Methods (Wiley, 1973), pp. 228ffGoogle Scholar. Note that the Hoeffding statistic can be used as an index of the degree of association as well as a test statistic.

8 For an outline of this test see Hollander and Wolfe, Nonparametric Statistical Methods, pp. 68ff.

9 Ibid ch.9.

10 Fama, E., “The Behavior of Stock Market Prices,” The Journal of Business (January 1965)CrossRefGoogle Scholar. It has been reported that O.L.S. estimates in the above context can be argued to be unbiased and consistent although not efficient. (See the reference to Wise in Beaver, W. “The Behavior of Security Prices and Its Implications for Accounting Research (Methods),” Accounting Review (1972 Supplement), p. 435Google Scholar.) With 20 observations consistency loses much of its appeal. On the relative efficiency of nonparametric regression versus O.L.S. see Hollander and Wolfe, Nonparametric Statistical Methods.

11 For example, see R. Ball, “Changes in Accounting Techniques and Stock Prices,” for a discussion of the possibility that changes in accounting methods may be associated with the firm's changing industries and/or its risk and so the relationship between its stock's return and that of the market. Parameter estimates using data prior to the change thus may no longer be representative. Using data following the change for parameter estimation and hypotheses testing in the present work biases independence tests, of course, since the resulting estimated residuals of model (1) are necessarily correlated. These biases affect the “treatment” and “matched” control samples equally and thus do not invalidate their comparison.

12 The generous cooperation of E. Scott in providing this sample along with the mailing dates of the annual reports and Standard and Poor's daily rate of return index, is gratefully acknowledged. Mailing dates of annual reports for the matched group were obtained from the. N.Y.S.E. Division of Stock List; daily returns from the “Scholes Wells Fargo” tape; daily volume from the Wall Street Journal. The number of outstanding shares did not change over the sample period (the relevant 20 trading days) for any of the firms studied.

13 See Hollander and Wolfe, Nonparametric Statistical Methods, pp. 219ff.

14 For an outline of this model see, Fama, E. and Miller, M., The Theory of Finance (New York: Holt, Rinehart and Winston, 1972).Google Scholar

15 A model similar to (1) has been used in, J. Winsen, “Investor Behavior and Information,” and in W. Beaver, “The Information Content of Annual Earnings Announcements,” Empirical Research in Accounting (1968). In both cases use of the filter had little effect on the results. The results of this study were also unaffected by use of such a model.