The Information Content of Quarterly Earnings Data and The Market's Revision of Risk Predictions Implied in Option Prices (Call, American)

153 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1986.This dissertation examines the relationship between changes in the market's prodictions of the total risk of common stocks surrounding quarterly earnings announcement dates and signals contained in the announcements. The research provides an alternative approach to test the information content of quarterly earnings numbers within the risk context. The limitations of beta prediction as a means of evaluating the usefulness of accounting data in assessing security risk and the inconclusiveness of research results bearing on the issue provide the motivation for this study.A dividend-adjusted American call option pricing model is used to derive the market's risk predictions. The information conveyed by a new earnings announcement is assumed to be its predictive content of the expected earnings and earnings variability in the future. A model that relates the rate of change in the market's risk predictions to the rates of changes in expected earnings and earnings variability is derived and tested for each of the four quarters of 1981. The results of testing this functional relationship are quarter-specific.Both the theoretical and empirical limitations of the functional relationship are discussed. A partial relationship between the rate of change in the market's risk predictions and the relative change in expected earnings is further tested. Though the results of testing the partial relationship are more homogeneous across quarters than those of testing the functional relationship, the evidence shows clear support for the hypothesized relationship for only the first and fourth quarters.Overall, the results presented here, at best, provide some evidence that the market uses quarterly earnings data to revise its risk predictions. The exact functional relationship, however, is still unclear.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD