Date of Award

1984

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Accounting

Abstract

The primary objective of this study was to determine the ability of different subsets of information under the Statement of Financial Accounting Standards No. 33 (SFAS 33), historical cost/constant dollar (HC/CD), current cost (CC), and current cost constant dollar (CC/CD), to predict the changes in stock prices as compared to that of HC information. The study was carried out using the data available for the years 1979-1981. The test period was the eleven weeks surrounding the issuance dates of the firms' annual reports which was approximated by using the date of annual earnings announcement that appeared in the public media such as the Wall Street Journal. Two samples for two time periods (1979-1980 and 1980-1981) were selected from the companies listed on the nonfinancial file of the FASB Statement 33 Data Bank. The security's cumulative weekly return adjusted for dividends and stock splits was used as the dependent variable and percentage change in earnings per share and the related components were used as the independent variables. Each sample was assigned to different industry groups based upon the first two digits of the companies SIC code. Each industry group was divided between two subsamples. Subsample (1) was used to estimate the prediction models through least square regression. Subsample (2) (hold-out sample), which included ten observations in every case, was used to test and compare the predictive ability of the models. Prediction errors of the four models, HC, HC/CD, CC, and CC/CD models, were analyzed through a spit-plot design ANOVA. Duncan's multiple range test was carried out as a post ANOVA test wherever appropriate. The results indicated that, in predicting the changes in stock prices, HC information competes with three subsets of inflation adjusted data available under SFAS 33 and none of these three can significantly and/or consistently outperform the HC data. Furthermore, the industry was not a significant factor in predicting the changes in stock prices.

Pages

154

DOI

10.31390/gradschool_disstheses.3992

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