Krieger  observed similar results during the three days surrounding quarterly earnings announcements. Rather than determining the existence or nonexistence of information content in accounting announcements, this paper uses daily data to examine when the market reacts relative to an earnings announcement-??particularly quarterly ones-??in the WAS. Whether the market reacts before or after the announcement provides additional insights into how information is disseminated and processed.
Securities on both stock exchanges and over-the- counter (ETC) markets are investigated and compared. Price changes and trading volume in securities markets may occur in situations unrelated to information specific to a particular security. Wealth and risk preference changes as well as changes in consumption opportunities may lead to a reallocation of resources. If these events are independent of the release of firm-specific information, however, large samples should diversify the effects of such information factors.
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Market factors, both informational and informational, affecting prices and trading volume in general may he removed through regression. So, although trading and price changes due to firm-specific information may not be completely isolated, there are empirical methods to mitigate against the effects of other factors. Assuming price changes and trading volume related to firm-specific information can be isolated to some degree, we can then consider interpretations of the results. The rice change and trading volume activity surrounding public announcements is analyzed in detail in Morse .
To summarize the arguments, trading prior to a public announcement may occur because of differences in beliefs about the probability of different signals being emitted by the public announcement. These differences in beefs may be caused by the asymmetric distribution of the information before its public announcement. Trading volume following the public announcement may be due to different interpretations of the signal released and/or investors returning to diversified positions after taking speculative positions prior to he public announcement.
Significant price changes surrounding public announcements may occur when some nonzero subset of investors receives a signal that changes their beliefs. Therefore, price changes prior to the public announcement may indicate that the signal or some clue about it had been received by a subset of the population. ‘ A price change immediately following the public announcement indicates some consensus change in beliefs caused by the signal.
Price changes in the days following the public announcement may indicate that the WAS does not release all the pertinent ‘ There is a question of whether the announcement that information will be released will affect prices. If investors use Bayesian revision and have log utility functions and wealth independent of their beliefs, then the expected price change prior to the release of a signal to any investor would be zero. 376 information related to the public announcement SMS further information is released through other sources on subsequent days.
Additionally, there may be an information-processing period, so that while the stock price may react in an unbiased manner on the day of the announcement, further processing of the information exults in price increases for some securities and price decreases for others. A As can be seen FL-mom the above, unique interpretations of the resists are not possible, but this is true in any empirical study. A detailed study of price changes and trading volume surrounding quarterly and annual earnings will, however, eliminate some theories about information dissemination and interpretation.
Also, the results may provide directions for further research. 2. Sample The sample used in this study includes daily price and volume data for four years (1973-76) for 25 sectaries traded on stock exchanges (20 on the NYSE and 5 on the EASE) and 25 sectaries traded over the counter (ETC). This is an attempt to obtain a more representative sample of securities available to investors and avoid the emphasis on NYSE firms that often occurs through the use of the CRISP tapes. For ETC firms the bid price was used as the measure of price.
Selection criteria for both groups included an industrial Compost’s number, quarterly earnings data available from different sources for nine years (1968-76), 75 percent of these earnings figures reported in the Wall Street Journal in the last four years, and trading of at least I(K) hares on 90 percent of the trading days. ‘ The most severe criterion was the longevity one for ETC firms. Such a criterion could lead to a sample biased toward firms that were successful, but not too successful (otherwise they would likely be listed on the exchanges). Hence, the samples may not be completely representative of their respective optimizations. From this subgroup firms were chosen randomly through their Compost’s number. The price and volume ‘ The question of time of information processing should be of particular concern to accountants. Accountants provide society with processed information. The further processing that occurs in the market may indicate that the accountant is providing a nonpolitical level of information processing.
Cost of information processing to the various groups would, of course, have to be considered, ‘ In using daily data there is a concern in accurately measuring return when there is not much trading to continually reaffirm the price, Schools and Williams  suggest an instrumental variable to overcome this problem, but it is viable only when there is not serial correlation in the lag between the last trade and the end of the ay. Morse  found that serial correlation of this type is very likely.
Therefore, the standard method of calculating betas is used and the sample is limited to securities that trade relatively frequently. ‘ The asset size in 1976 for the ETC sample used in this study was compared with the asset size of a randomly selected sample of 100 other ETC firms in 1976. The mean for the sample in this study was $112 million, while the mean for the randomly selected sample was $108 million. They were not significantly different at the 5- 377 data were taken from the Daily Stock Price Record. The firms in the sample are listed in table 1.