an empirical investigation of the effect of quarterly earnings announcement timing on stock returns

Accounting Research Center, Booth School of Business, University of Chicago

An Empirical Investigation of the Effect of Quarterly Earnings Announcement Timing onStock ReturnsAuthor(s): William Kross and Douglas A. SchroederReviewed work(s):Source: Journal of Accounting Research, Vol. 22, No. 1 (Spring, 1984), pp. 153-176Published by: Blackwell Publishing on behalf of Accounting Research Center, Booth School of Business,University of ChicagoStable URL: http://www.jstor.org/stable/2490706 .Accessed: 27/02/2012 13:15

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].

Blackwell Publishing 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.

http://www.jstor.org

http://www.jstor.org/action/showPublisher?publisherCode=black

http://www.jstor.org/action/showPublisher?publisherCode=grad-uchicago

http://www.jstor.org/action/showPublisher?publisherCode=grad-uchicago

http://www.jstor.org/stable/2490706?origin=JSTOR-pdf

http://www.jstor.org/page/info/about/policies/terms.jsp

Journal of Accounting Research Vol. 22 No. 1 Spring 1984

Printed in U.S.A.

An Empirical Investigation of the Effect of Quarterly Earnings

Announcement Timing on Stock Returns

WILLIAM KROSS AND DOUGLAS A. SCHROEDER*

1. Introduction

This research examines both the association between quarterly announcement timing (early or late) and the type of news (good or bad) reported, and the relationship between stock returns and timing around the earnings announcement date. Recent research on announcement timing (Givoly and Palmon [1982], Patell and Wolfson [1982], Kross [1981], and Whittred [1980]) has provided evidence that delayed announcements of annual earnings more often convey bad news (i.e., lower than expected earnings) than do early announcements. However, we know of no study which has reported evidence of the same phenomenon for quarterly earnings. Furthermore, there is a limited amount of evidence regarding the reaction of market participants to announcement timing. While three studies (Givoly and Palmon [1982], Kross [1982], and Chambers and Penman [1984]) find that early (late) announcements are associated with higher (lower) abnormal returns or high (low) stock return variability, relative to late (early) announcments, only Kross [1982] controlled for the sign of the earnings forecast error and none controlled for the magnitude of the earnings forecast error.

It is well accepted that stock returns are associated with the sign of the earnings forecast error (EFE). Since announcement timing is also

* Associate Professor and Assistant Professor, Purdue University. We wish to thank the members of the Purdue University and the University of Chicago accounting seminars for their comments. [Accepted for publication June 1983.]

153

Copyright ?, Institute of Professional Accounting 1984

154 JOURNAL OF ACCOUNTING RESEARCH, SPRING 1984

associated with the EFE this variable must be controlled if one is to examine market reaction to announcement timing. Similarly, Beaver, Clarke, and Wright [1979] reported that stock returns are also associated with the magnitude of the earnings forecast error, so it is necessary to control for forecast error magnitudes as well. This is because early (late) announcers could be releasing extremely good (bad) news. Finally, in the light of recent research which shows that stock returns around the announcement date are inversely related to the size (market value) of the firm (Atiase [1980] and Ro [1983]), like Chambers and Penman [1984], we decided to control for the potentially confounding size effect.1

Our objective, then, was to determine whether the association between announcement timing and stock returns persists after controlling for the sign and the magnitude of the earnings forecast error and firm size. Briefly, our results show that early quarterly earnings announcements (1) contain better news and (2) were associated with larger abnormal returns relative to late announcements. These findings hold both for large and small firms, for positive and negative EFEs, and for small absolute values of the EFE.

In section 2 we describe the procedures and the data used in the tests. The lag and earnings expectations models used to classify firms into reporting and earnings categories are discussed in section 3. The results appear in section 4, followed by a summary and conclusions (section 5).

2. Procedure and Data

2.1 PROCEDURE

First, we computed a time lag forecast error for each of 12 quarters on the basis of a comparison of the actual quarterly announcement date with a forecasted date. Second, we computed an earnings forecast error for each firm and each quarter on the basis of a comparison of actual to forecasted quarterly earnings. We then examined the earnings forecast errors for the earliest and latest quarterly announcements for each firm with the expectation that the earliest announcements (relative to expectations) would have a higher (larger positive or smaller negative) median EFE than observed for the latest announcements. Next, we categorized each firm on the basis of both its lag forecast error (early, on time, late) and its earnings forecast error (good news, bad news). This process resulted in six distinct groups of firms: early-good, early-bad, on time- good, on time-bad, late-good, late-bad. Finally we examined the abnormal stock return behavior on the days surrounding the quarterly announcements for all six groups of firms in order to determine whether the announcement timing conveyed or was associated with information other than that contained in the earnings number.

'We want to thank the reviewer for making this suggestion.

EFFECT OF EARNINGS ANNOUNCEMENT TIMING 155

TABLE 1 Median Autocorrelations at Lags One-Four

Autocorrelation Raw Residuals Residuals at Lag Time Lag Random Walk Model Autoregressive Model

1 -.1712 +.1909 -.1015 2 -.0939 +.0517 -.0069 3 -.1887 -.0086 -.0302 4 +.5809 -.2832 -.1310

2.2 THE SAMPLE

Our total sample consisted of 297 NYSE and American Stock Exchange firms that met the following conditions: (1) daily stock price data were available for the years 1977-80 on the daily ISL (Investment Statistics Laboratory) tapes produced by Standard and Poor's and Chase Econo- metrics; (2) quarterly earnings from the third quarter of 1968 through the third quarter of 1980 (the latest available at the time this study was conducted) were available on the quarterly COMPUSTAT tapes; (3) quarterly earnings announcements dates were available from the second quarter of 1971 through the third quarter of 1980 on the quarterly COMPUSTAT tapes; and (4) the fiscal year ended in December.

These filters resulted in 3,564 observations-12 quarters for each of 297 firms. All observations were used when we examined the relationship between announcement timing and the earnings forecast error. However, missing stock return data caused us to eliminate one firm, yielding 3,552 observations for the examination of stock price behavior.

3. Models

3.1 ANNOUNCEMENT LAG FORECAST MODELS

A firm was classified as reporting early or late based on a comparison of the actual time of announcement with the expected time of announcement. The expected time of announcement was formulated via a time- series analysis of each firm's reporting history. We examined the autocorrelation functions for the 26 quarterly report time lags from the second quarter of 1971 through the third quarter of 1977 for the 297 firms in our sample.2 The median autocorrelations for lags one through four are presented in table 1.

As one would expect, there is clearly a spike in the autocorrelation function at lag four. The autocorrelation function of the fourth differ- ences (a random walk model) still produced small spikes at lags one and four. Since we expected fourth-quarter (annual) earnings to be reported at longer lags, on average, than interim reports, we estimated an auto-

2 A lag was measured by the number of days elapsing from the end of the reporting period to the earnings announcement.

156 W. KROSS AND D. A. SCHROEDER

regressive model with an indicator variable associated with fourth- quarter announcements for predicting report time lags for each firm. Model (1) predicts the report lag as follows:

Lagiq = ai + fj(Lagiq-4) + Yi(Q4) + Fi(Lagiq-) (1)

where: Lagiq = forecast of the number of days spanning the end of the quarter

and the earnings announcement for firm i in quarter q; Lag i-4 = actual number of days spanning the end of the quarter and

the earnings announcement for the same quarter of the preceding year; Lagi,_q = actual number of days spanning the end of the quarter and

the earnings announcement for the quarter immediately preceding quarter q;

Q4= 1 if quarter q is the fourth fiscal quarter, 0 otherwise; a, y, y, r = firm-specific parameters. The medians of the autocorrelation function of the residuals for model

(1) (column 4 in table 1) indicate that they are nearly white noise. This model was used to forecast the report time lag for each of the next 12 quarters with a reestimation of the parameters after each quarter's forecast.

A second lag forecast model, model (2), was chosen as a benchmark for comparison to model (1). This model is a random walk in which report lags are predicted as:

La~gq = Lagiq-4 (2)

where the terms are defined as before. As reported in column 3, table 1, small spikes appear in the autocorrelation function at lags one and four for this model. Nevertheless model (2) seemed a reasonable and appropriate benchmark for purposes of comparison with model (1). Each of these models was used to forecast the announcement lag for each of 12 consecutive quarters beginning with the fourth quarter of 1977.

3.2 EARNINGS FORECAST MODEL

The type of earnings news reported was classified vis-A-vis an extrap- olation of each firm's quarterly earnings. We utilized the premier quarterly forecasting model proposed by Griffin [1977] and Watts [1975], the parameters of which were estimated for each firm:

Zq = Zq-4 + Zq-i - Zq-5 - Oaq1 - yaq4 + Oyaq-5 (3)

where:

Zq = one-quarter-ahead forecast of EPS in quarter q, Zq = actual EPS in quarter q,

0 = a regular first-order moving average parameter, y = a seasonal moving average parameter, a = a serially uncorrelated error term.


The choice of a "common model" structure follows from Jenkins [1979] as well as empirical studies of earnings. Jenkins suggests that for rela- tively short time series a common model may be appropriate where the environments generating the data have common features. In addition, empirical studies such as Foster [1977], Lorek [1979], and Schroeder [1980] provide evidence that time-series models generate quarterly forecasts that are superior to naive martingalelike models.

For each firm, the 37 quarterly EPS figures (adjusted for stock divi- dends and stock splits) from the third quarter of 1968 through the third quarter of 1977 were used to estimate the parameters of this model. All forecasts of interim and annual (fourth-quarter) EPS were one-quarter- ahead forecasts generated by updating the model for each of the next 12 quarters.

3.3 STOCK RETURN MODEL

In the evaluation of stock return response to earnings announcements, we used the traditional market model posited by Sharpe [1963]:

Rik = ai + O2iRmk + Like (4)

The parameters of this model were estimated using one year of daily returns (approximately 252 observations) prior to the quarter of the earnings announcement. The parameter estimates were used to compute the abnormal return for days -2 through +2.

4. Results

4.1 RESULTS-TIMING VERSUS TYPE OF NEWS

In this section we report on the nature of the report timing for both interim and annual earnings and the association of report timing with the EFE.

Figures 1 and 2 depict the distributions of the actual reporting lags (the number of days between the end of the fiscal period and the earnings announcement), while figures 3-6 depict the unexpected (actual-expected) lag over four-(calendar) -day reporting intervals. The distribution of the raw reporting lag is quite similar to that reported by Chambers and Penman [1984]. Interim reports, reported in figure 1, cluster between 22 to 30 days after the quarter and are characterized by a distribution that is skewed to the right. However, the distribution of annual announcements, reported in figure 2, seems more symmetric, with some clustering of announcements between 28 and 40 days after the end of the year. The distributions of the lag forecast errors, reported in figures 3-6, are almost symmetrical for both annual and interim announcements. As expected, all four distributions are characterized by a sharp spike at zero with a similar number of observations above (late) and below (early) the mean.


bays -6 10 14 18 22 26 30 34 38 42 46 50 54 58 -62

FIG. 1.-Frequency distribution of reporting time lags: interim announcements.

Days .56 104 14_ - 18 224 264 30 1-38 42 -46 50 54 58 62

FIG. 2.-Frequency distribution of reporting time lags: annual announcements.

Tests of the relationship between the unexpected lag and EFEs are reported in table 2 for both interim and annual announcements. The raw forecast error was first deflated by its standard error (se). Thus:

EFE = (Zq Zq)/se.

When EFE is positive (negative), earnings are greater (less) than expected.

Panel A of table 2 shows the average earnings forecast error across all firms from the earliest to the latest announcement (relative to expectations). The Wilcoxon statistic on the difference between the averages for


A * (4) ,~, I

I * (3)

co I -I

0~~~~(0

D I * (1)

* *H(4) v I I

L I * (04) .

F I I ** (10)

I

** (3) I I

*********** (125) I o ********************* (405)) I I

) *********************** (1214) I

CI 0. o *********** (533))

iI I

L, o' ***** (235) ..I

o I .. ** (616)

-I

I D *

I

I

v * (4)

esI

T' IIILI

40)0 800 1 200) 1600 200 Fr eque-ncy


a (0 * (4)

(8I I A* (8)

(4I

*

(8) I

4 * (3) I'

CD (1221

n , * (4) U , I

S * (18)

~~~(17

I e. ' ** (44)

I C ' ***** (166)

Fr I

l 1 I ************** (5 23)

I :L I

5 ******************************** (1 221)

~ I o ********** (376) S I

a I t ' ******* (237) S I - I

e o** ( 34 ) S. I eD I

, * (1 7) ~' 1

: @ * ~(7) I

m * (4 ) ?u' I

I * (3) I I

IV* (4)

400 800 12900 1600 2000 F'requenlcy


0,

A ** (5) I I

I W * (2) H

l cn

I, ** (5)

:: I ** (8)

I

(87) _-~'-7 1 -. I

.. I **** (27) I

00

I ******** (71) I I

o j ***~************* 17

cLI I

o ************************************ ( 353) I

?I ' ' ***************** (155)

~Fq I <

o? ******* (59 ) I 0

cLI e **** (25)

I

,_ * (13) I

o I : - ** (6)

I

I

8 v * (1) * I

I IllII

100 200) 300 400 500 Frequency


(0

A I ** (5)

tQ I I

X ** (6) HI

I I @ * (3)

I I t | ** (8)

I

w I ** (9) CL s I t **** (25)

_. 1 2

. I 02 | ******* (57) 0 Io

I I ***************** (163)

~0 121

20~ ~~~2

00

o **t************************************** (388) I I

r , ************ (110)

I I

0'o ******** (73) I

o I 'L ,o, *** ( 20 )

FeuI 02 I

H ** (12) 02

I

02 I 0 0 H_ * (2)

v) I I

02 * (2) * I

I v ** (2 )

I

100 200 300 4 00 500( Frequenc y


t *q

,-~~~ L bC LO --b

cl '1 ' 1 '

'-~~~~~~~~~~~~~~~~~~~~~~~~-

CTc"

CCC * c 0 C) Z**

cq~ ~ ~~~~.

o ~~~~~~~~~~~~~~~-o

o C~~~~~~~~~~~~~0C CC CeZCCC-

LO CCCI0

2 ~ C I e

CCCCC

CI)Q C4I C) 1 LO M C

-q cq l2 - l

cl l

m~~~~~~~


the earliest and the latest announcing quarters is significant at a = .01 for both the autoregressive and the random walk models. The results of the Page L test (which tests the null against the ordered alternative a,1 >

2> * *. *> 12 and thereby uses more of the sample information) is also significant at a = .01.

Panel B of table 2 shows the results when the three annual announcements are omitted for each firm. Again, the results are significant and consistent with the results based on all quarters. We conclude, therefore, that earlier (later) quarterly announcements are characterized by higher (lower) unexpected earnings. We next investigate whether this relationship had any effect on stock returns.

4.2 RESULTS-ANNOUNCEMENT TIMING AND STOCK

RETURNS

Using daily data, the possibility of cross-sectional correlation in the residuals existed due to earnings announcement clustering. For example, as many as 39 firms announced their earnings on the same calendar date. In order to mitigate the problem of cross-sectional correlation we generated controlled residuals by subtracting the residuals of a randomly selected nonannouncing sample firm from that of each announcing firm during the earnings announcement time period (day -2 through day +2). The controlled residual was computed as follows:

Vik = fik - fjk

where: Vik = controlled residual for treatment firm i, day k; cik = market model residual for treatment firm i, day k; cjk = market model residual for control firm j, day k.

The only restriction applied in the selection of the control firm was that the quarterly earnings announcement of the treatment firm did not occur within seven calendar days of the announcement of its control firm. This process was repeated for each firm for each quarter tested. The results of all succeeding tests are reported using these controlled residuals (hereafter residuals).3

In order to assess the relationship between announcement timing and stock returns, we had to control for the announcements' news effects on those returns. We did so using a two-factor analysis of variance. One factor classified firms by the type of news (good or bad) reported, while the other represented the timing (early, on time, or late) of the announcement. This approach allowed us to examine the timing effect indepen- dently of the type of news reported. For test purposes we classified firms as reporting on time if the actual announcement date was within ? one

3We also conducted tests on the raw residuals of the treatment firms. Our conclusions were not altered.


day of the expected announcement date. Announcements arriving earlier (later) were categorized as early (late).

The results for all observations are presented in figure 7 and table 3 for the autoregressive lag expectation model. The residuals are reported as percentages. A glance at figure 7 reveals immediately that announcement timing as well as the type of news had a distinct association with the stock return residuals.

Since the interaction between the two factors was never significant we do not report it. Consistent with expectations, good news firms, with a five-day cumulative average residual (CAR) of .83%, outperformed bad news firms whose five-day CAR was -.97%. A stratification on timing alone yielded a CAR on early firms of .43%, while late or on time announcements had CARs of -.16% and -.27% respectively. Since earlier announcements typically contain good news the better performance for early firms is not surprising. However, when the sample is stratified into news/timing categories the effect of announcement timing still persists.

1.200 - .900 -~~-

//

.900 /

A/

a:.QOO' '~~~~~~~~~~~~~~~~- ' '

-.300} e

-1.200

-1.600-, -2.000 -1.000 DRYS 1.() 2.000

FIG. 7.-Cumulative average residuals (in percentages) around the announcement date (day 0): good/early (GE), good/late (GL), good/on time (GOT), bad/early (BE), bad/late (BL), bad/on time (BOT).


* LO

cq c t r cv cv r, cs cv Cq M Lo t O ce > 4

H m 00

cq f- r

= cv u o

T C 5 CD CeD Ce t5 CD CD t5 Ce C Ce 00

I I I I I I+ I 10

+ O .) 00 CD _ O Ce C- C- CD OC

2 > O ~~~~~~ ~~~ O O O n ~~~~~~~~ ~~ O O ~~~~~~ > L _

c U + I1+ I ++ I + I+ + +Lc

>) cq cq cq cll cq _q 00 t-

Clz o, t~-C~ m C LC ClcO LO c m cT c l

-< E + I .:I III +++t-O-

Z! CZ

C. * *

Ce ClC +l- I: +C + II+

C.)

-U I O Iz-Cl O- O h - > % C'S

0q 0U-~ U-~ 00 L-00 C 0 Cl~0

L O L+O + 1 c + c 1 1 c C?

x~~~~~~~~~~~~~~~~~~~ r-- r-- L ~O LO LO t- (s s.:

C.)~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~C

>)

,,* ,E5 E-

-H z E- Z m C


The CAR for good news announced early was 1.39%, but only .54% for good news announced late. Early bad news produced a five-day CAR of -.79%, compared to a -1.02% CAR when announced late. Thus, even after controlling for the sign of the earnings forecast error, the timing effect was still significant at day -2 through day 0 and for the five-day CAR.

The results of separate tests on annual and interim announcements are reported in panels A and B of table 4. Both timing and news effects were significant for the five-day CAR for both annual and interim announcements, at day -2 for annual announcements and at day -2 through day 0 for interim announcements. These results lend strong support to the notion that the timing effect is independent of the sign of the EFE.

Although the ANOVA results indicate that the timing effect was distinct from the sign of the EFE, it is still plausible that it was a function of the magnitude of the EFE. That is, "good news" firms might have reported very good news when they announced early, but only moderately good news when they announced late. Similarly, late "bad news" might have been very bad compared to early bad news announcements. This is a reasonable alternative hypothesis, particularly in the light of the study by Beaver, Clarke, and Wright [1979] which reported a positive relationship between stock returns and the magnitude of EFE.

In order to address this issue, we subclassified each main group into a moderate and an extreme subgroup-for example, moderately bad (negative EFE less than one standard error) and very bad (negative EFE greater than one standard error in magnitude), with a similar dichotomy for "good news" firms. If the report timing was a surrogate for magnitude of EFE, we would not expect a relationship between announcement timing and stock returns for moderate news classifications. As before, an ANOVA was used, but only on the firms that reported moderately good or bad news in early and late announcements.

The test results in table 5 are not consistent with the proposition that the timing effect was a proxy for the magnitude of the EFE. The timing effect persisted at day -1 and day 0 and for the five-day CAR even though, by construction, the magnitude of the EFE was small. Separate examinations on annual and interim announcements, reported in panels A and B of table 6, yielded similar results. Again the timing effect was significant for the five-day CAR and for one or more of the days around the announcement date. The news effect was very weak, as would be expected since all extreme EFEs were omitted for these tests. These results provide strong evidence that report timing was not a surrogate for the magnitude of the earnings forecast error, but rather conveyed or was correlated with information distinct from the sign and the magnitude of EFE.


_ o oo ooo C o c oo C C * I I + + I I I I + I I

CS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~C9 C; + o M - r-L( L - m m O r1 LC-o

C OH fCf C Cf o Cf c o

." .. . . . . . . . . .

.c

.

00

+ 00 0 ' U0r .) (1- ( a)

CZ co ol o co Cm m (M q M o- M cq oo

I II ++ I I'+ I 4I I o6

o

-N =

4. CE *

> e ;;>. Cf t C9D Ce C) C) m cq q L- o C9 1 LO

0 <U + I + + I + I I + + + +

1 +

?

IS *

_ A, C) - c Nil C 'I'd, 0 r M C t -C1o t I CI C o C CC C1

X CS *~~~~~~~~~~

o0 C9

CeD 0C 0O o Zo 0M C) 0 0 0

~~~~~~. . . . . . . . . . ....... . . .....

:~~~~~ . . . :: . . . . ... . : :::::

~~~~~~. . . . . . . . . . . . . . . . . . . . -

;< X z = c H e a R z i 4 i o s ? E EN : >, O , o >, m O O zNO


t>C C9 O o 5)CC& C00O 0. m~ cq 00 mU~L - ~ .4 rt--~00

. o 4 : I' +: + I' I' I' I' r- H o+ o+ t c + 1+ +*I*

II*-~+ + c+

+ Iz- M M -4M L C 0~cm +~

C CO; -i

CO r- CCCCO

oo CIO Ct

:> I II II 1+ I I+1 I* I

+ *+ oo

0~~~~~~~~~~~~~~~q0 C > t- CeD 00 4 C1 00 Ce Cl0 0 Cl

CZ o~ r-- r-- r- o r- CeD o r-- o o) CeDc" C )

4 + I' +' I' +' +' I' +: I' + - + +s

CO

0 0o O ;>. C'1 C9 C9 C- Cq r-- CM L O C11 o~ o Cf

CZ

E + I' + + I' I' I' I I' a; + +

* * J

I O C z ~~~~~~ o o r~ C1 LO Loo C1 Cf Cz r C

CS * *~~~~~

IZ r--~ CZ C cq m CO C Cf

4: C 4: 4: oo I' C9 Cf O O o o C9

C9 I I'd c" t- .C C9 Cf o~ o z . .C9C q m oo 00 - % t -t -t -t -t -t

.E .O

* E. - Z.........*......


0 c fo C-1 m 0 Lo Ct o00

R~~~~~~~~~~~~~~~~~ *

X~~~~~~~~~~~~~~~ *

E- cc. c

I! Z + r+ +1 + I +I | +1 0

C - C'-1

I*L I*I* L I* I- 660~. o I

> c1 cl l m

C ) z cot- O co c0 C. m 0 t O

Q n + I + +I + 1 +I + ,L-

I Q t- C% C z

'- 0 m mttt C C-1 0 Lo U:CT "t-

>n + I1+ ++I +I+IC

+t oo ms L HC o CT

o~

oC~ CC

Lo

C

Co1oCC

o

* I I I I.I II I I I

*~~~~ ~ ~~~~ . . O. O.

Cl) I I~~~~~~~~~~a) L

. ..) ...

a,~E~c~ceZ m O .C m m 3


> ; o ~

q L- o. L- 00 Lo >%

> I I1+ + 1 .i +I6oc

+~~~~ z CT CI m C-T c m C1 m o

Q I I 1' 1- 1 I- 1 1 .? ?

4CD > CT m C m LoC

so

I II II I I I + I

tk

>1 00 t- )Cl t 'lC: ? s

I1 cqc ( C T co t c -0~.

X l ~~~C-1 oo m Cm: m t- Lo t: e

z o. H o o o o C~~t o (t

L. n I 1+ I II I I +oo

H c o on

- -N - n >e

.'S c . , *,-..'

' t C


1 Ev I+ +I +mI + +m1

+ m o T

o o 1 Lo 0 o. o o

0 I I I Lo+ I + ,Ioo

a) >1 m U1C1

cn +q t- 00 C q O - Lo U:O Q

o C- I I I+o C

C

<:~~~~~~~ *

I; C U:1 -1m m L

r = o % H e e o t- L o m 0

Q CD U o~ LC o. m 0 o

+ ++ +l +1 +1

o 4

I~~~~ C2~ CCL t t-C

>~~~~~~ o CCHHC -U>

Eq l o t cs t u: u: ~~~~~~ Cl 't o bku

H~~~ ~~ Cfz C : >U

'1 W n () bs E n ? c ,W W W

~~~ S ~ W~ C *2 *2 i3 i= 1* m C

v m

_ _ Z O

CY. CY


4.3 RESULTS-ANNOUNCEMENT TIMING AND FIRM SIZE

Previous studies (Chambers and Penman [1984] and Ro [1983]) found an inverse relationship between firm size and the absolute value of stock returns around the earnings announcement date. A question naturally arises about whether the timing effect phenomenon would be observable for both large and small firms. In order to provide evidence on this issue we took our "moderate news" subsample and split it into small and large firms and conducted tests on each size substratum. All firms whose market value was below (above) the medium market value at the end of the second quarter of 1978 were defined as small (large) for the entire sample period. The test results on large (small) firms are reported in panel A (panel B) of table 7.

As shown there, the timing effect persisted across both size categories. For large firms (panel A), announcement timing was significantly related to stock returns at day -2, day -1, (weakly) at day 0, and for the five- day CAR. Late announcers of moderate news saw their share prices drop by .89%, on average, as opposed to an increase of .30% for their early- announcing counterparts. Announcement timing also affected moderate good news firms, which had residual returns of .72% if they announced early, but only .24% if they announced late.

The test results on the small firms, reported in panel B of table 7, tell a similar story. The announcement timing effect was significant at day -1, day 0, and (weakly) for the five-day CAR. The share prices of firms that announced moderately bad news late fell by .90%, on average, over the five-day announcement period, whereas the early-announcing counterparts fell by only .03%. Moderately good news announced early was rewarded by a .31% abnormal return, whereas later-announced good news was greeted with a .32% negative return. Thus, it appears that the "timing effect" persisted for both large and small firms.

5. Summary and Conclusions

Generally, we found that earnings announcement timing was associated with abnormal stock returns around the earnings announcement date. Abnormal returns of firms that announced early (late) were significantly higher (lower) than the returns of firms that announced late (early). This general result is consistent with previous research by Givoly and Palmon [1982], Kross [1982], and Chambers and Penman [1984]; however, these other studies did not completely control for potentially confounding factors regarding the "timing effect." After controlling for these, our results are remarkably consistent. The "timing effect" persisted whether the earnings announcement (1) contained good news or bad news, (2) was an annual or interim announcement, (3) was made by a large or small firm, or (4) contained moderately good or moderately bad news.


~~.o c~~~~~l 0C C

Cl~~~~~~~~~~~iC

+ m Lo O m LC m CC LO

._c 1 c c! cl oO c cs l

+ Lo+ 1+ I + I, CD

CS>)d ~ls C)S 0O cq cq

- n *

z 0~~~~~~~~~~~~~~~0

cQ + I++ I +1 I + I++ I O

I CO C3 >,0 o ~ 0Cc O V oo o co

L.~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~~~L

8 I

+ 1+ +1 +I++ N

Z~~~

COD -

^ Z ~~~> 1 0 C<: q O q N N1l LNO

O Q + + + +) I' + I + +

* _.>~ ~ ~ ~ ~ ~~~~~~~>

q *

a;~~~~~~~~~~~r CJ C5*

% t e CD O mP -;m n

* z * c z * z

4- : 4 b - -j -e 0 ; m z = m ) 0 ) 3 .C _ z r > 3

O C CO


o LO o - LCO C0 m>C1C00 > +Lo N, o C. 0 o m m

Cl I I + CD CIIA o + 0 C CD CD C D 0 0 0 C C1- C O

I+ II+ ++ II oo

+ C 0o00o Ct-00 O C C o -

> CO ~~~COq CO l 00 m CIA t - I-

00 *

3CL 0 o0 0 cO c10 LO -

> 4 fq +1 +?++ m 1- CD t

0 * * CO t O0 LO 0 C C0 ClLO Cl

I l+ +1 +i4:ic~i

Cl~~~~~~~~~~~~~~~C

) *)C O

L O t~-00 LO 0>1 00C>>O C9 l

+ OCI + l0 I + I I+ +CL

CO CIC C0 O O s 00C9

.

s CS CO CO CS ~ ~ ~ ~* * II Ii I

*. . ....-* * *

. .-e....... .

.. ..- -

. . . . . . . . 0).. * *

. ~ . .~ . . . . *

z z z z z C C CO <

m ' t ro | | bD r t ? ? '' * CO

_Z E~ _ 0 OC 0

3 Q > 3Q Q Q v vD0


We know of no reason that the timing of the announcement per se should affect stock returns. Indeed, we believe that the announcement timing itself should have no effect, but rather is probably associated with some other event that either is typically associated with a reporting delay or is usually viewed as "bad" news. Loss contingency disclosures or CPA switches could be two such types of events. Of course, additional research is needed to explore this possibility.

Because "timing" (or other events associated with it) can greatly influence stock returns, we suggest that future studies on announcements incorporate adjustments which control for announcement timing when examining stock return responses to the announcements. Failure to do this could bias, or induce noise into, the test results.

REFERENCES

ATIASE, R. K. "Predisclosure Informational Asymmetries, Firm Capitalization, Financial Reports, and Security Price Behavior." Ph.D. dissertation, University of California, Berkeley, 1980.

BEAVER, W., R. CLARKE, AND W. WRIGHT. "The Association Between Unsystematic Security Returns and the Magnitude of Earnings Forecast Errors." Journal of Accounting Research (Autumn 1979): 316-40.

CHAMBERS, A. E., AND S. H. PENMAN. "Timeliness of Reporting and the Stock Price Reaction to Earnings Announcements." Journal of Accounting Research (Spring 1984): 21-47.

FOSTER, G. "Quarterly Accounting Data: Time-Series Properties and Predictive Ability Returns." The Accounting Review (January 1977): 1-21.

GIVOLY, D., AND D. PALMON. "Timeliness of Annual Earnings Announcements: Some Empirical Evidence." The Accounting Review (July 1982): 486-508.

GRIFFIN, P. A. "The Time-Series Behavior of Quarterly Earnings: Preliminary Evidence." Journal of Accounting Research (Spring 1977): 71-83.

JENKINS, G. M. Practical Experiences with Modeling and Forecasting Time Series. San Francisco: Holden-Day, 1979.

KROSS, W. "Earnings and Announcement Time Lags." Journal of Business Research (September 1981): 267-81.

. "Profitability, Earnings Announcement Time Lags, and Stock Prices." Journal of Business Finance and Accounting (Autumn 1982): 313-28.

LOREK, K. S. "Predicting Annual Net Earnings with Quarterly Earnings Time-Series Models." Journal of Accounting Research (Spring 1979): 190-204.

PATELL, J., AND M. WOLFSON. "Good News, Bad News, and the Timing of Corporate Disclosures." The Accounting Review (July 1982): 509-27.

Ro, B. "Firm Size and the Informational Asymmetry of Annual Earnings Announcements." Working paper, Purdue University, February 1983.

SCHROEDER, D. A. "Expectations Data and the Stochastic Properties of Accounting Numbers: A Multiple Time Series Methodology." Ph.D. dissertation, University of Kansas, 1980.

SHARPE, W. F. "A Simplified Model for Portfolio Analysis." Management Science (January 1963): 277-93.

WATTS, R. L. "The Time Series Behavior of Quarterly Earnings." Working paper, Depart- ment of Commerce, University of Newcastle, 1975.

WHITTRED, G. P. "Audit Qualification and the Timeliness of Corporate Annual Reports." The Accounting Review (October 1980): 563-69.

an empirical investigation of the effect of quarterly earnings announcement timing on stock returns

Business

earnings categories

earnings forecasterrors

earnings forecast errorfor

earnings expectations

nouncements of annual

forecast error magnitudes

nouncement timing early

early announcements