Since the 1960s we have seen the rise in empirical evidence asking the question: Is accounting information useful to investors? Since then we have seen huge progress. If you read my article Accounting Information II you can read all about the most important discoveries in this field. However in this article I will explain the root accounting information theory, the Ball and Brown study. The Ball and Brown study was conducted in 1968, and involved two Australian academics, Professor Ray Ball and Philip Brown. The study asked the question: Is there a relationship relationship between earnings and share price.
The Ball & Brown study was founded on three essential assumptions:
1. Investors find earnings per share relevant in making decisions
2. That investors have the ability to forecast earnings per share through accounting information
3. Investors react to errors in their forecast, when revealed, by adjusting the current share price of the particular stock
The investigation measured the forecast error in earnings per share. Ball and Brown used the “random walk model” (the assumption that the price of a stock follows a random path) to calculate earnings per share. This meant that:
Expected EPS (year 1) = Actual ESPS (year 0)
In other words, Ball & Brown assumed that the earnings per share given in the current financial statement should equal the earnings per share in the next financial statement. This gave rise to the following formula:
Forecast error (year 1) = actual EPS(yr0) – expected EPS(yr 1)
Next Ball & Brown measured investor’s reaction to any abnormal (or unexpected) return in share price. If We assume a diversified market model we assume that only systematic risk is relevant in calculating expected returns:
Expected return = risk free rate + Beta x market risk premium E(R) = rf + βRm
Next Ball & Brown measured the abnormal return:
U = actual return – E(R)
The test itself consisted of 261 New York Stock Exchange firms. Between 1957-1965 Ball & Brown found the average monthly actual returns 12 months prior to EPS announcement and the cumulative abnormal returns. They then formed two group’s positive changes (good news) and negative changes (bad news).
After cumulating the results the firm tested the following hypothesis:
“Good/bad news should be related with positive and negative changes in cumulative abnormal returns”
The research found that the market had forecasted 80% of the news BEFORE the earnings announcement and the 3 and 6-month returns AFTER the announcement was approximately zero.
In other words’ the greatest abnormal returns were generated around EPS announcements. The hypothesis was supported and Ball & Brown were able to conclude that accounting numbers do have information content. Furthermore it suggested that the market is semi-strong efficient and reacts quickly and unbiasedly to new information.
Below is a five minute video that talks about this study in detail: