Accounting Research Center, Booth School of Business, University of Chicago Stock Market Reaction to Estimates of Earnings per Share by Company Officials Author(s): George Foster Reviewed work(s): Source: Journal of Accounting Research, Vol. 11, No. 1 (Spring, 1973), pp. 25-37 Published by: Wiley-Blackwell on behalf of Accounting Research Center, Booth School of Business, University of Chicago Stable URL: http://www.jstor.org/stable/2490279 . Accessed: 23/08/2012 08:42 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp . JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. . Wiley-Blackwell and Accounting Research Center, Booth School of Business, University of Chicago are collaborating with JSTOR to digitize, preserve and extend access to Journal of Accounting Research. http://www.jstor.org
Transcript
Accounting Research Center, Booth School of Business, University of Chicago
Stock Market Reaction to Estimates of Earnings per Share by Company OfficialsAuthor(s): George FosterReviewed work(s):Source: Journal of Accounting Research, Vol. 11, No. 1 (Spring, 1973), pp. 25-37Published by: Wiley-Blackwell on behalf of Accounting Research Center, Booth School of Business,University of ChicagoStable URL: http://www.jstor.org/stable/2490279 .Accessed: 23/08/2012 08:42
Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp
.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact [email protected].
.
Wiley-Blackwell and Accounting Research Center, Booth School of Business, University of Chicago arecollaborating with JSTOR to digitize, preserve and extend access to Journal of Accounting Research.
Stock Market Reaction to Estimates of Earnings per Share by Company
Officials
GEORGE FOSTER*
Recent papers have examined the stock market reaction to a variety of information generating events, e.g., stock splits [10], annual and quarterly earnings announcements [1, 3, 7, 8], and announcements of discount rate changes by the Federal Reserve Bank [20]. This paper examines the stock market reaction to another potential information generating event, i.e., estimates of annual earnings per share by company officials. These esti- mates are made after the end of the financial year, but before the release of audited earnings figures.
Three kinds of annual report data may be produced following the end of a firm's fiscal year: (a) Estimates of annual EPS by company officials, (b) Preliminary earnings reports, and (c) Complete annual report data. Relatively few of the companies for which preliminary and complete annual report data are published, release estimates of annual EPS made by com- pany officials. For this reason, the number of firms in our sample is much smaller than in past studies on the stock market reaction to preliminary earnings reports [1, 3].
Individual and Aggregate Market Behavior
In the first part of this paper, the trading volume reaction to estimates of EPS by company officials is examined. Volume statistics evidence the reac- tion of individual actors in the capital market. The latter part of this paper examines the stock price adjustment to the EPS estimate. Price statistics evidence the aggregate market reaction to information. There is no neces- sary reason why the individual and the aggregate market reaction to in- formation should be the same. For instance, the aggregate market reaction
* Ph.D. Student, Stanford University.
25
26 JOURNAL OF ACCOUNTING RESEARCH, SPRING, 1973
TABLE 1
Time-Lapse from Company Officials' EPS Estimate to the Announcement of
Preliminary Earnings Report No. of
companies
0-10 trading days 12 11-20 trading days 31 21-30 trading days 16 31+ trading days 9
to a piece of information may be canceled out, but it may still cause in- creased volume reaction because of investors' heterogeneous expectations and/or changes in risk preferences.'
Sample Design The Wall Street Journal Annual Index for 1968 to 1970 was used to
identify instances in which, after the end of each financial year, a company official publicly announced an estimate of EPS before the release of the preliminary earnings report. The following selection criteria were used:
(a) A firm with a December 31 financial year-this criterion facilitated the search process.
(b) A firm whose stock prices are on the CRSP tape. (c) No dividends announced in either the week of the company official's
EPS estimate or the week of the preliminary earnings announce- ment; no stock split announcement in the 16-week period surround- ing either announcement. The reason for this criterion was the same as in Beaver [3], i.e., to isolate the effect of the earnings announce- ments from other announcements.
(d) The estimate of the annual EPS was a precise one made by a com- pany official. Many of the annoucements of EPS estimates in The Wall Street Journal Index do not include the identity of the estimator. In these cases, the issue of The Wall Street Journal was checked to verify that the estimate was in fact made by a company official rather than, say, being a report from the "Heard on the Street" section of the Journal.
The result was 68 instances of estimates of EPS by company officials in the period 1968 to 1970. The company official who most frequently made the announcement was the chairman or the president.
The distribution of the time-lapse between the EPS estimate and the preliminary earnings announcement is presented in Table 1. The median and the mean time-lapse were, respectively, 17 and 18 trading days.
I The distinction between the role of information at the individual and at the ag- gregate market level is stressed in Beaver [3]. More extended discussion on the role of information, at both the individual and the market level, is in Fama and Laffer [11] and Hirshleifer [14].
STOCK MARKET REACTION TO EPS 27
The accuracy of the EPS estimate was measured by computing the following:
The average error for the 68 EPS estimates was 1.8 percent. In contrast, if the EPS was predicted to be the same as last year's EPS, the average absolute percentage error would have been 26.7 percent.2
A group of 68 firms with no EPS estimate by a company official was chosen to serve as a control group. The choice criterion was that each time a firm with an EPS estimate was discovered, the next firm in The Wall Street Journal Annual Index to satisfy criteria (a) to (c) was selected to be in the control group. Since the Index references most firms on the NYSE, no systematic bias in the composition of the control group is expected. The stock market reaction to the preliminary earnings report of the control group will serve as a benchmark with which to compare the reaction to the earnings announcements of the 68 firms with EPS estimates.
Individual Investor Reaction to EPS Estimates
The reaction of individual investors to the EPS estimates was measured by the following variable:
number of shares in firm i traded in week t i number of shares outstanding for firm i in week t
number of trading days in week to
Vie is the weekly average of the daily percentage of shares traded.3 For group I (the control group), Vit was computed for each of the eight weeks before the company's preliminary earnings announcement and each of the eight weeks after that announcement, as well as for the week of the an- nouncement itself. For group II (the 68 firms with EPS estimates), Vit was computed for two different 17-week periods-one surrounding the EPS estimate, the other surrounding the preliminary earnings announcement. The respective average values of Vie for each of the three 17-week periods are presented in Table 2.
For group I (column 1 of Table 2), there was a 47 percent increase in
'The EPS estimates by company officials examined in this paper are a different class than EPS forecasts made by company officials prior to the end of the financial year.
An examination of the forecasting ability of some company officials was presented in Green and Segall [12, 13]. They concluded that "on almost any reading we do not find the executives' forecasts impressive.... If the executives' forecasts have validity and are not biased, we may say that some forecasts (e.g., this year's EPS same as last year's) are not inferior to actual, presumably less naive, forecasts" [12, p. 54].
'The weekly volume data were taken from Standard and Poor's I.S.L. Daily Stock Index, New York Stock Exchange.
28 GEORGE FOSTER
TABLE 2
Average Viz for Period Surrounding Earnings Announcements (Reported Numbers are Vit X 10')
Group I Group II
Company officials' ~~Prelim. earnings Week Prelim. earnings EPS estoiate Prelim. earnings ann. = iweek 0
ann. = week 0 =week 0 ann. = week 0 (EPS estimate (1) (2) (3) week deleted)
Viz at the preliminary earnings announcement week, relative to the average of the 16 weeks surrounding that announcement. This increase is consistent with individual investors perceiving the preliminary earnings announce- ment to have informational content. For group II there was a 51 percent increase in Vit at the week the estimate was made, relative to the average Vie for the 16 weeks surrounding the EPS estimate (column 2); for this same group of firms, there was only a 1 percent increase in Vit at the week the preliminary earnings report was released (column 3). This result is consistent with individual investors perceiving the annual EPS to have informational content, but reacting to the earliest source of that figure.
The Vit for the eight weeks before the preliminary earnings reports for group II includes the week the EPS estimate was made. But since this EPS estimate week is not the same for all 68 firms (see Table 1), the average Vit for group II in the eight weeks before the preliminary earnings an- nouncement overstates the average Vit for the period. To overcome this problem, the Vit for each firm at the week the EPS estimate was made was deleted from the computation of the average Vit for the 16-week period surrounding the preliminary earnings announcement. The adjusted figures appear in Table 2, column (4). After deleting Vie for the EPS estimate week, there was still only a 6.5 percent increase in Vie at the preliminary earnings announcement week, relative to the 16 weeks surrounding that announce- ment. Thus, most individual investors do appear to react to the earliest
STOCK MARKET REACTION TO EPS 29
TABLE 3
Rank of Vt: at Week = 0 for Relevant 17-Week Period Group I Group II
Rank of Vi t . Company officials' Pei.erig at-week e Prelim. earnings EPS estimate ann. = week 0 =week 0 ann. = week 0
source of annual earnings rather than waiting for the release of audited earnings.
The data in Table 2 do not reveal whether the observed average pattern was general for the 68 firms in both groups I and II, or whether it resulted from extreme observations in both groups at the relevant announcement dates. A Kolmogorov-Smirnov One Sample Test was therefore used.4 First, I determined the number of companies in group I for which Vit at the week of the preliminary earnings announcement was the highest Vie for the 17- week period examined was noted. Then I determined the number of com- panies for which Vit at preliminary earnings announcement week was the second highest Vit for the same 17-week period. This procedure was con- tinued until Vit at the preliminary earnings announcement week was classi- fied for each of the 68 firms in group I. The same procedure was used in classifying Vie for group II at both (a) the week of the company official's EPS estimate, and (b) the week of the announcement of preliminary earn- ings. Table 3 summarizes the results of these classifications.
The data in Table 3 were used to calculate the cumulative probability distribution for Vit in week 0 being greater than, or equal to, the ith highest trading week in the 17-week period. These were compared to the expected cumulative probability distribution under the null hypothesis that Vie at week 0 is no different from Vte at nonweek 0 periods. The relevant cumula- tive probability distributions for groups I and II are summarized in Table 4.
'A more detailed description of the Kolmogorov-Smirnov one-sample test is pre- sented in Siegel [19].
30 GEORGE FOSTER
TABLE 4 Cumulative Probability Distribution of Rank of Vit at Week = 0 for Relevant 17-Week
Period Group I Group II
Expected distr. Rank of Vit Prelim. earnings Company officials' Prelim under null at week 0 ann. = week 0 EPS estimate an. = earningsthsi
Kolmogorov-Smirnov One-Sample Test Level of significance for D = Max [Fn(X) -Sn(X)] for N 68
.01 D = .200 .15 D= .138
.05 D = .165 .20 D= .130
.10 D = .150
For group I, the null hypothesis that Vit at earnings announcement week is the same as Vit at the other 16 weeks surrounding that announcement can be rejected at the .01 significance level. The null hypothesis for group II can also be rejected at this level but only for the Vit at the week of the EPS estimate; the rejection for the week of the preliminary earnings report can only be made at the .20 significance level.' These results indicate that the pattern observed in Table 2 was not the result of several extreme ob-
'The week to week variations in V4t are much more variable than those reported by Beaver [3] for the trading volume reaction to preliminary earnings reports. My smaller sample-68 instances as opposed to the 506 examined by Beaver-appears to explain these larger variations. A Kolmogorov-Smirnov one-sample test was run on V4t at every week in the three 17-week periods for which there was at least a 10 percent in- crease over the V4t of the previous week. The null hypothesis could not be rejected at the .20 significance level for any of the weeks examined. The relevant maximum [Fn(X) - Sn(X)] are as follows:
servations, but was, in fact, a general pattern for the 68 companies in groups I and II. Individual investors do perceive annual earnings announce- ments as having informational content. However, they react to the earliest source of annual earnings rather than waiting for the release of audited figures.
Aggregate Market Reaction to EPS Estimates In the remaining section of this paper, I examine the adjustment of
security prices (reflecting aggregate market reaction) to EPS estimates by company officials. The operational measure of this adjustment will be the ability of trading strategies based on these EPS estimates to generate abnormal returns. An abnormal return is defined as the difference between (a) the actual return on a share between two points of time, and (b) the predicted return, given the normal relationship between the rate of return on this share and the rate of return on a market index. This normal rela- tionship is calculated by a regression of monthly price relatives for the share on the corresponding values for Standard and Poor's Stock Index for the past 60 months. An Abnormal Performance Index will be used to measure abnormal returns:
T
A.P.I. = II (1 + lit) tool
where T = number of trading days from start of the trading strategy (detailed below) to the preliminary earnings announcement (both dates taken from The Wall Street Journal Index). The Uit are measured using Sharpes market model [17, 1816:
Rit = cai + liRmt + Sit
where =it = return on security i in period t
ai, li = intercept and slope of linear relationship between RiJ and Rmt R.m - market return in period t Rig stochastic portion of individualistic component of R6t, and
E(Ut7) 0. 6 The Sharpe model used in this paper is a single index model. In attempting to iso-
late the individualistic component of Rit, only general market factors are abstracted. King [15] found that whereas general market factors accounted for 52 percent of the variance in a typical security's rate of return between 1927 and 1960, industry factors also accounted for another 11 percent. Meyer [16], using a different cluster technique, extended King's study to 1967. He concluded there are "strong industry-related fac- tors underlying the behavior of stock prices. However, the pattern is much less clear than suggested by King" (p. 13).
The industry classifications of the 68 firms with EPS estimates by company officials were examined to see whether omission of the industry factor might systematically bias the results. As there was no clustering of the firms in any one industry, no systematic bias is likely.
32 GEORGE FOSTER
THE TRADING STRATEGY ADOPTED
The trading strategy examined was to (a) buy a share when the com- pany official's EPS estimate exceeded the EPS prediction from an earnings expectations model; or (b) adopt a short selling policy when the EPS esti- mate was less than the EPS prediction from an earnings expectations model. Group (a) will be referred to as the positive prediction error group, group (b) as the negative prediction error group.
This trading strategy was adopted for two separate time periods. The first time period was from five days (an arbitrary choice) prior to the re- lease of the official's EPS estimate to the date the preliminary earnings report was announced in The Wall Street Journal. It was assumed that pur- chases and sales are made at the closing prices on the relevant days.7 The results of the trading strategy for this time period will answer the question of whether there was an opportunity to earn abnormal returns by knowing, in advance, the sign of the earnings prediction error.
The second time period was from the date the EPS estimate was an- nounced in The Wall Street Journal to the date the preliminary earnings report was likewise announced. It was also assumed that purchases and sales are made at the closing prices on the relevant days. The results of the trading strategy for this time period will indicate the extent to which security prices adjust to the EPS estimate (assuming abnormal returns exist for the trading strategy for the first time period).
The following five earnings expectations models, using annual EPS data, were used to classify firms into those with a positive prediction error and those with a negative prediction error.
I: EPS for last year II: EPS for last year plus the change in EPS over the most recent year
III: Average of last two years' EPS IV: EPS for last year plus the average change in the past two years V: EPS for last year less the average change in the past two years'
EPS (a mean reverting model). By the time the company official makes an estimate of annual EPS, the
results of the first three quarters are already publicly available. To in- corporate this information into predictions of this year's annual EPS the following five earnings expectations models, using quarterly data, were also tested.
VI: Four-thirds of this year's first 3 quarters' EPS VII: EPS for first 3 quarters of this year, plus EPS for 4th quarter of
last year VIII: EPS for last year plus four-thirds of the difference between this
year's first 3 quarters' EPS and last year's first 3 quarters' EPS IX: EPS for last year times the percentage change in this year's first
3 quarters relative to last year's first 3 quarters.
'The daily price data was taken from Standard and Poor's I.S.L. Daily Stock Price Index, New York Stock Exchange.
STOCK MARKET REACTION TO EPS 33
X: EPS for first 3 quarters times the ratio of the average annual EPS for the last two years to the average first 3 quarters' EPS for the last two years.
Notation for each of the above 10 expectations models is presented in the Appendix.
The choice of this set of annual and quarterly models was influenced by the results of studies into the time series behavior of earnings variables [2, 4, 6] and the results of studies using earnings expectations models and/or abnormal performance indexes [1, 5, 7, 8, 9, 12, 13]. Moreover, several of the latter studies showed that first differences formulations of annual earn- ings expectations models consistently outperformed models predicting the level of next year's EPS.8 To make my results as comprehensive as possible, I also used first difference formulations of each of the above five annual and five quarterly expectations models were also tested. Thus, a total of 20 expectations models were tested.
RESULTS OF TRADING STRATEGY
The average returns for the trading strategies for each of the earnings expectations models are presented in Table 5. The Roman numerals I, II, etc. refer to the expectation models detailed in the Appendix. The A and B refer to the level and differences formulations, respectively, of each expec- tation model.9
Up to the time the company official announces the EPS estimate, there is still opportunity for an abnormal return. The average abnormal return for the trading strategy, based on knowledge of EPS estimate five days before it is publicly released, is 1.61 percent for the 10 annual expectations models10 and 1.48 percent for the 10 quarterly expectations models.
'A first difference formulation of an expectation model can be illustrated as follows. Assume the expectation model for levels of EPS is
E(EPS) = EPSt-l
where E is an expectations operator. A first difference formulation would be:
E(EPSt - EPSt-1) = EPSt-1 - EPSt -2.
'The trading strategy examined required firms be classified into those with a posi- tive prediction error and those with a negative prediction error. Using this classifica- tion, it is possible to gain some insight into whether company officials are more prone to make an estimate of EPS when EPS is likely to exceed predictions, "likely" being tested in terms of the expectations models examined. For the 10 annual expectations models, the average percentage of firms with a positive prediction error was 51 percent; the relevant figure for the 10 quarterly expectations models was 63 percent.
' The average time-lapse of the trading strategy, based on knowledge of the EPS estimate five days prior to its release, is 23 trading days, i.e., approximately 1 month.
Ball and Brown [1] found that, for 261 NYSE firms over the 1957-65 period, the average abnormal return in the month prior to the release of preliminary earnings was 0.95 percent. This finding was conditional upon an earnings expectations model pre-
34 GEORGE FOSTER
TABLE 5 Abnormal Returns from Trading Strategies Based on EPS Estimates
Av. abnormal ret. Av. abnormal ret. for for strategy 5 days
Earnings strategy after EPS before EPS expectations announced announced Chi-square for Chi-square for
model (1) (2) (1) (2)
IA -.12 1.37 .36 2.94*** B .40 1.40 1.31 3.80***
11A .40 1.40 1.31 .380*** B .78 2.46 1.69 6.45**
IIIA -.55 .47 .01 .78 B .35 1.73 .36 3.02***
IVA .35 1.60 .34 2.82*** B .87 2.70 2.11 9.44*
VA .25 1.23 .16 .45 B .35 1.73 .34 3.02***
VIA -.01 1.33 1.02 4.94** B .03 1.71 1.01 3.00***
VIIA -.25 1.86 .40 3.18*** B .11 1.16 .28 1.36
VIllA .03 1.61 1.01 3.00*** B -.26 .83 .24 .67
IXA -. 10 1.50 .65 2.31 B .41 1.55 .36 .53
XA .15 1.70 1.22 3.38*** B .20 1.54 .24 .60
Chi-square for critical values * Prob(xI 6.64) = .01 for 1 degree of freedom
** Prob(x2 3.84) = .05 for 1 degree of freedom * Prob(X2 2.71) = .10 for 1 degree of freedom
Prob(X2 1.64) = .20 for 1 degree of freedom
Once the official's EPS estimate is publicly released, there is a stock price adjustment such that the trading strategy based on that information yields lower abnormal returns than the trading strategy detailed above. This result is consistent for all 10 annual expectations models using annual data, and for all 10 expectations models using quarterly data. For the 10 annual expectations models, the average abnormal return is 0.31 percent; this contrasts with the 1.61 percent average abnormal return if the EPS esti- mate was known 5 days before it was publicly released. For the 10 quarterly expectations models the average abnormal return is also 0.31 percent; the average abnormal return if the EPS estimate was known 5 days before its release was 1.48 percent.
Comparisons of abnormal returns do not indicate the extent to which the observed results was a general pattern for all firms or was due to ex- treme observations. To examine this issue, chi-square statistics for the trading strategy for the two time periods were computed. The following
dieting next year's EPS to be the same as last year's EPS. The average abnormal re- turn. for the same expectations model in my smaller sample, a more restrictive one than in Ball and Brown [1], was 1.37 percent.
STOCK MARKET REACTION TO EPS 35
two by two contingency table was used. The numbers in the table are those for the naive expectation model (IA) for the trading strategy after the EPS is publicly released:
EPS greater than EPS less than predicted predicted
Abnormal return greater 24 12 than 0
Abnormal return less than 0 20 12
Summary chi-statistics for all 20 expectations models are presented in Table 5.
For every one of the 20 expectations models, the chi-square statistic is higher for the trading strategy based on knowledge of the EPS five days before its public release than for the trading strategy using the EPS estimate when it is announced. Indeed, for 13 of the 20 earnings expectations models, the chi-square statistic is significant at the .10 significance level for the former strategy; none of the 20 models is significant at the .10 significance level for the strategy based on the EPS estimate when it is publicly re- leased. Thus, there is a statistically significant relationship between the sign of the EPS prediction error and the sign of the abnormal return before the release of the EPS company official. Once that information is made publicly available, however, there is no statistically significant relationship between the sign of the EPS prediction error and the sign of the abnormal return.
Conclusion
On the basis of volume and price studies, both individual investors and the aggregate market consider pre-audited estimates of EPS to have in- formational content. Once the estimate is made public, stock prices rapidly adjust such that a trading strategy based on these estimates does not earn abnormal returns.
APPENDIX A
Earnings Expectations Models
I. E(EPSt) = EPSt-,
II. E(EPSt) = EPSt_1 + (EPSt-, - EPS2)
III. E(EPSt) = EPSt-1 + EPSt2 2
12 IV. E(EPSt) = EPSt-, + EI (EPSti - EPSt-i-1) 2 p=1
36 GEORGE FOSTER
2 V. E (EPSj) =-EPSj~-2 E (EPSON-EP
VI. E(EPS ) =- Qt
VII. E (EPSt) = Qt + (EPS1 j-Q -)
VIII. E(EPSt) = EPSj-1 + 4
(Qt -QI-) 3
IX. E(EPSj) = EPSt-, (Q
X. E(EPSj) = 1 (EPSI-1 + EPSJ-2' \Qt-l + Qt-2 /
where Qt = first 3 quarters' EPS for period t.
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STOCK MARKET REACTION TO EPS 37
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