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As was the case with the income regression model, stock returns model contained a number of apparent violations of OLS assumptions. The return of market index was relevant to the residual because the market index contained the return for firm j, and because the industry impacts. Neither violation was serious, because the “Combination Investment Performance Index” of Fisher (Fisher, 1966) was calculated over all stocks listed on the New York Stock Exchange (hence stock returns was only a small portion of the index), and also because the industry impacts accounted for up to 10 percent (Brealey, 1968) of the changes in the rate of return on the average stock. Again, any bias had little effect on the results, because there is in no case was the stock return regression that was fitted over 100 observations (Fama, et al., 1967).

Therefore, Ball and Brown (1968) assumed that it was impossible that no useful information about a particular firm reflected the rate of return during a period, but only the market-wide information that fitted for all firms. By abstracting market impacts, they identified the impact of information fitted to individual firms. Then, in order to determine whether part of the effect could be associated with information contained in the numbers of accounting income of a firm, they separated the expected and unexpected changes in income.

If the income forecast error was negative, that was, if the actual change in income was less than its conditional expectation, they defined it as a bad news and predicted that if there was some relationship between accounting income numbers and stock prices, and then releases of the income figures would lead to the return on that firm’s stock, which was less than what would have been originally expected.

The results from the empirical test of Ball and Brown showed that the information contained in the annual income figures were useful, as it related to stock prices. Beaver, Clark, and Wright (1979) found similar results and confirmed the initial findings of Ball and Brown (1968). Subsequent studies (Barth, Beaver, &Landsman, 1992; Collins & Kothari, 1989) found similar results again. The research of Lipe (1990) found that the relationship between earnings and equity value changes with the persistence of earnings.

This study found that the equity value during a period is a function of (1) the time-series persistence of the earnings series, (2) the interest rate used in discounting expected future earnings, and (3) the relative ability of earnings versus alternative information to predict future earnings. The comparative statistics of Lipe (1990) showed that the response coefficient played an increasingly important role for past earnings to predict future earnings and an increasing function of persistence. In addition, the movements of stock price changed conditionally on earnings being announced was a decreasing effect of the predictability of the earnings series and an increasing effect of earnings persistence. If the predictability or response-coefficient effect was positive, that was because the value attached to a one-dollar current-period earnings shock was an increasing effect of predictability; if the predictability or variance-of-price-changes本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。