The distribution of earnings news over time and seasonalities in aggregate stock returns

Journal of Financial Economics 18 (1987) 199-228. North-Holland

THE DISTRIBUTION OF EARNINGS NEWS OVER TIME AND SEASONALITIES IN AGGREGATE STOCK RETURNS Stephen H. PENMAN* University of California at Berkeley. Berkeley,

CA 94720, USA

Received August 1985, final version received September 1986 Over the past 55 years returns on stock market indexes have on average been higher during the first half-month of calendar quarters 2 through 4 than at other .times. Coincidentally, aggregate corporate earnings news arriving at the market during these half-month periods tends to be good, whereas earnings reports arriving later are more likely to convey bad news. In addition firms tend to publish bad-news earnings reports on Mondays, coincident with negative Monday effects in stock returns. The coincidence of earnings news arrival and market seasonalities leads to conjectures about informational reasons for observed seasonalities.

1. Introduction

This paper documents coincidental seasonalities in aggregate corporate earnings news and stock returns. During certain calendar periods, corporate earnings reports convey ‘good news’ on average, whereas in other periods they convey ‘bad news’. Mean stock returns differ over these good-news and bad-news periods, and the direction of the difference is consistent with the differences in the aggregate earnings news arriving at the market during these times. Two patterns of corporate earnings reporting are evident from observation of earnings reports over ll$ years from October 1971 through December 1982. The first is seen in the distribution of good and bad earnings news within quarters. Earnings reports published in the first two weeks of calendar quarters 2, 3 and 4 on average convey good news, in the sense that they affect stock prices of reporting firms positively, whereas reports appearing later in the quarter are more likely to carry bad news, in the sense that they affect stock prices negatively. Second, there is an intra-week distribution of earnings news. More bad news arrives at the market on Mondays and, to a lesser extent, on Fridays than on other days of the week. The intraquarter distribution of ~n-;~nr “PITIC :m S.-r+ rB..Ar+;“n in L411UU~jJ ‘lC,vvJ ,.O” bCzI1I.US ~“..ln;..,J Ly_l’aLu~U Lu pu L h.r “J AbY” n11~ l-.‘ah”.A,TF “~114”‘“. A,v-.l.mzantPA U_ULIIbIILcIU 11. *The comments of Jim Ohlson, seminar participants at the University of California at Berkeley, Stanford University, and UCLA, Ross Watts (the referee), and G. William Schwert (the editor) are gratefully acknowledged. 0304-405X/87/$3.500

1987, Elsevier Science Publishers B.V. (North-Holland)

200

S. H. Penman. Earnings new and reasonahries in stock reurns

Chambers and Penman (1984) Kross and Schroeder (1984) and Penman (1984): firms tend to publish their earnings more promptly when they have good news to report and tend to delay reporting when they have bad news. This paper also documents an as-yet unnoticed seasonality in mean stock returns. Over the past 55 years, returns for the market as a whole have, on average, been significantly higher in the first two weeks of calendar quarters 2, 3 and 4 than in other periods during these quarters. This beginning-of-quarter effect is not as strong as the ‘January effect’ typically observed at the beginning of the first quarter. Unlike the January effect, however, it does not appear to be primarily a small-firm phenomenon. Further, the higher observed mean returns during the early part of calendar quarters 2 through 4 are not associated with higher observed variance of returns, which suggests market inefficiency. The two-week period during which higher mean market returns are observed is the same period during which aggregate earnings news is, on average, positive. This coincidence is striking, suggesting informational reasons for the observed shifts in market returns. Speculation about informational reasons for market seasonalities is reinforced bv the resu!ts indicatin-eCIthat ------Mondavs tend to be marked by the arrival of bad earnings news. This is coincident with the so-called Monday effect reported in a number of papers: mean observed market returns are lower on Mondays than on other days of the week and, in fact, are negative. The paper is organized as follows. Section 2 describes the earnings report data and summarizes tirms’ reporting patterns. Because the interpretation of the results on the distribution of earnings news over time assumes that the sample of earnings reports is representative, these data are discussed at some length. In section 3 the intraquarter distribution of good and bad earnings news is documented. The intraquarter distribution of mean (market) stock :-._~...~~1. ~:~.~L..r:~-c _-*_.---,r:-- *. A X“r-r:-- JE rl_ Icl.uIIIs :” 13 -,-.-._&A1 IG:p”lLCU:111bCLLI”ll 111>CLlIUII Lilt: lIIlI&tWCt5K UISLIIUULIUU WI earnings news is examined. Finally, a summary of the results and a discussion of their implications for market efficiency issues are contained in section 6. 2. Summary of earnings report data and fhms’ reporting patterns Announcement dates of interim (quarterly) and annual earnings reports appearing between October 1, 1971 and December 31, 1982 were obtained from a customized file supplied by Standard & Poor’s Compustat Services, Inc. The file contains earnings report dates for the 2,396 firms appearing on the 1982 COMPUSTAT PDE tape. Of these, 2,205 tirms appear on the 1982 I_.. mm\ version of the Center for Research. in Security Prices (C;Ksr) Daiiy Returns Fife. For these 2,205 CRSP 6rms there are 78,553 earnings report dates on the Standard & Poor’s file over the lla years in the sample period. The fiscal period to which the report applied was discovered in 78,178 of these cases and daily returns were available on the CRSP file at the report date in 75,736 of

S. H. Penman, Earnings news and rearonalities

in stock returm

201

the 78,178 cases. These 75,736 earnings reports provide the sample for the analysis. For the inferences in this paper it is important that the earnings reports appearing in the sample on any day be representative of all earnings reports published that day. With this large sample there is a significant number of reports for most days. The sample period covers 2,842 trading days. Of these, only 19 have no earnings reports, and the coincidence of these with certain days of the year suggests they were days on which firms generally did not report.’ The median number of reports on a trading day is 18, the mean 26.8, and values at the 0.05, 0.10, 0.25, 0.75, 0.90 and 0.95 fractiles of the distribution of the number of reports on a trading day are 5, 7, 11, 36, 60 and 79, respectively. A small number of reports on a day does not necessarily reflect a deficiency in the data, since there are periods (for example, toward the end of calendar quarters 2 through 4) when few earnings reports appear. There are 10,970 reports in the period October 1, 1971 to the end of 1973 (an average of 19.6 per trading day), 19,771 in the 1974-1976 period (an average of 26.2 per trading day), 21,339 from 1977 to 1979 (an average of 28.4 pre trading day), and 23,656 from 1980 to I982 (an average of 31,4 per trading day). The differences in the average number of reports per trading day over these subperiods no doubt reflect a secular trend due to a growing number of firms, but possibly also less diligence by Standard & Poor’s in collecting report dates for the earlier part of the sample period. Subperiod tests in the paper are sensitive to this issue. The survivorship bias usually ascribed to the COMPUSTAT data bases appears to be the only selection bias in the sample. As indicated later, the survivorship bias probably works against the results here. Thirteen hundred and thirty firms appear on the CRSP Daily Returns File for at least one day during the sample period but are not in the sample. Only 68 of these, however, ^__^,... lr”llLlllL.l”UJl~ ,-.,...r:_..^.. cl.. “I1 ^_ *La rDCD 1IIc: Cl.-.lnu”ugl;ll”uL l. _^..ml-..r rL_ _.X^_ ^,.--A ilPPG&lI LIIC;LJLJC LI,C111 IL~-ycal PC‘l”U. I-Ll,lC number of firms on the CRSP file on a given trading day and not in the sample declines (fairly uniformly) from about 1,000 in 1972 to 800 in 1976, to 500 in 1979, to about 160 in 1982. It is also important that earnings report dates be assessed with some precision. Standard & Poor’s indicates that the report date ‘is that date that IMS first receives any valid information for the quarter’ (emphasis in original). The usual source is the broadtape or PR Newswire. Two problems are apparent in S&P’s recording of report dates. First, ‘any usable broadtape or PR Newswire with a time later than 3:30 p.m. (is) recorded using the date for the following day’. This presents a problem for reports arriving between 3:30 _ . _p.m. and 4:UU p.m. in the period when exchanges ciosed at 4:00 p.m. Second, when adding a company, S&P records report dates in the past from ‘all the ‘Six of the days cell on a September One was a December 24 and another

7, five on either a May 4 or 5, and three on a December a January 2.

31.

202

S. H.

Penman.

Earnings

new

and seasonalrues

m stock returns

WaN Street Journal reports available’. The Wall Street Journal report usually nnnenrs the after -Tr--_-__ dnv --, ---_-

the report.

reaches

the m&p!,

nnl~~c nnnnnnrPmPnt --l_l_ thr --__ _-.__.,I&___.____._

is made after the close of trading the day before.2 A comparison of 1,866 report dates on the Standard & Poor’s Ne with dates in the Wall Street Joumal Index found 38.4% on the same day, 49.2% one day prior to the WSJ date, 1.4% more than one day before the WSJ date, 8.7% one day after the WSJ date, and 2.2% more than one day after. These comparisons covered the full sample period and firms in a variety of industries, To deal with the report-date problem, the analysis was conducted defining the report date alternatively as (1) the date on the Standard & Poor’s file, (2) the two-day period covering the Standard & Poor’s date and the day before, and (3) the day on which the absolute value of (market-adjusted) daily returns was highest over the three-day period covering the day of, the day before, and the day after the Standard & Poor’s date. (The third definition assumes that the earnings report is associated with higher return volatility than that on surrounding days because of the news it conveys.) The results presented below are based on the tirst of these definitions and are conservative in relation to those based on the other two definitions. Figs. 1 and 2 present frequency distributions of reporting lag times for interim earnings reports (covering fiscal quarters one through three) and annual (fourth-quarter) earnings reports, respectively.3 Reporting lag is defined as the number of trading days from the end of the fiscal period to the date of the report. Reports are grouped into intervals of five trading days. Each interval covers one calendar week, unless exchanges are closed for holidays. It is clear that firms are generally slower in publishing annual reports than quarterly reports. The median reporing lag for reports for ouarters 1.-------- one through three is 19 days, whereas the median lag for annual reports is 34 days. The interim reports cluster in weeks 3 through 5 after the end of the fiscal period, whereas annual reports are more evenly spread over weeks. Ninetyseven percent of interim reports appear within 35 trading days (approximately seven weeks), whereas 8% of annual reports are still outstanding after 60 trading days (twelve weeks).4 Note that figs. 1 and 2 are developed from pooled cross-sectional and time-series data and that median lag times vary *See Pate11 and Wolfson (1982) and Abdel-KM& (1984). ‘Standard & Poor’s reports an announcement date for four fiscal quarters. The announcement date for the fourth quarter is deemed to be the earnine full annml renntt ___ .~_ annual ___ --_----_-__r_‘~ o- renort --r -- - date. ----. The usually comes later, but once fourth-quarter earnings are known, annual earnings are effectively known. In the paper, references to quarterly reports apply to reports for fiscal quarters one through three. %3 reports appeared on the file with an announcement date prior to the end of the fiscal period indicated. These are not represented in the figures. Occasionally, firms set their fiscal end-of-period one or two days before the last day of the month to coincide with a weekend. There were also 251 interim reports and 92 annual reports later than the period covered by the figures, so these are not reflected in the figures.

S. H. Penman Earnings news and seawmalirzes m stock returns

203

66sl -

3996 -

6727 -

5555

1

ppl

296 -

5

10

15

20

25

30

35

Reporting

40

234

r

-83

45

50

67 55

60

Lag in Trading Days from Fiscal-Period

65 End

Fig. 1. Relative frequency distribution of reporting lag times: interim reports. Absolute numbers of reports are given at the top of each bar.

across industries and firm sire, with larger firms tending to report earlier than small firms.

3. The distribution of good and bad earnings news within calendar quarters This section demonstrates that earnings reports published during the early part of calendar quarters 2 through 4 can be characterized as conveying good news whereas those published later in these quarters are more likely to convey bad news. In addition the analysis suggests that this phenomenon is due, at

S. H. Penman.

Earntngs

new

and seasonahies

rn stock returns

Fig. 2. Relative frequency distribution of reporting lag times: annual reports. Absolute numbers of reports are given at the top of each bar.

least in part, to firms’ reporting early when they have good news and delaying reports when they have bad news. ‘Good’ and ‘bad’ earnings news are defined on the basis of the stock price reaction to earnings reports. For each firm i reporting on day t an announcement day abnormal return was calculated as

0) where R,, is the stock return on the report day for the firm and R,, is the return on the market for the same day (measured by the CRSP equally weighted index of stock returns). Market returns were subtracted in view of the seasonalities documented in section 4. The second term in the expression is the mean market-adjusted return for the firm estimated over 100 trading days before the report is announced and is assumed to be expected market-adjusted return for the report day. If RTt > 0, the firm’s earnings news is deemed to be good, and if RTt < 0, the news is deemed to be bad. For each trading day t in the sample period for which at least one report was available, a mean

S. H. Penman, Earnmgs new and rem_makties

abnormal earnings announcement

m stock returns

205

return was calculated as

where n, is the number of firms reporting on that day. If R: > 0, the day is deemed to be a good-news day, and if R; -Z0,a bad-news day. An alternative measure summarizing the relative number of good- and bad-news earnings reports was also calculated. For each day t the measure Pr{ RF, > 0} was calculated as the number of reports on day r with Rrt > 0 relative to the total number of reports, n,, on day f. If this is greater than 0.5, day t is deemed a good-news day, and if less than 0.5, a bad-news day. Given market efficiency, one would expect stocks to be priced so that earnings news is, on average, neutral. Specifically, one would expect the mean nf \A, /l\ “._I n\‘~r~r U.I 011 .i u4.v nnrl ,t tn ‘IP~A UAIk.) anrl &A.“’ oiven “I L” hn “1 ‘..#I”

.CJ,,nifnrm U.lll”.lli

rlirtrihrrtinn Y.ICII”Y.I”I.

nf onnrl O&l.. an,4 “I b”“Y

bad news over time, the mean of (2) over t to be zero also. The grand mean abnormal announcement return (1) over the 75,736 reports in the sample is 0.0011 (with a t-statistic of 7.73) and the mean of daily mean abnormal announcement returns (2) over the 2,823 report days in the sample period is 0.0016 (with a t-statistic of 6.59). These values are significantly greater than zero. These positive values are consistent with the sample period being one when, ex post, firms tended to have good earnings news, with a survivorship bias in the data, with higher volatility (surprise) associated with good news, or with higher (non-diversifiable) risk during announcement periods [as indicated in Kalay and Loewenstein (1985) during dividend announcement periods]. The reasons are not expiored here; the observation is made because it bears on the analysis that follows. Table 1 summarizes the measures of aggregate earnings news for the first 35 trading days (approximately 7 weeks) of the 2nd, 3rd and 4th calendar quarters, pooled for all such quarters during the period October 1971 through December 1982. The values %f in the third column of table 1 are means of Ry for the relevant trading day for all three quarters in all years (34 quarters in all) in the sample period. There are relatively more positive values of i?F in the early part of the quarters than later and more values of the pooled Pr{ Rf, > 0} greater than 0.50 earlier than later. In the first 12 trading days there are five values of t(RT) greater than 1.66, compared with two in the next 12 days (one of which is on day 13), and one in the last 11 days.’ There are six values of Pr{ RTt > 0} greater than 0.50 in the first 12 days, three in the next 12 days, ‘The t-statistics are based on observations that may be drawn from distributions with different variances. Similar results are obtained when firms’ abnormal announcement returns are standardized by estimates of the standard deviation of abnormal returns. A mean of individual firms’ abnormal announcement returns (Rf,) was calculated for each day also to see whether the means of mean daily abnormal announcement returns reported here are strongly affected by the observation weightings in the calculation. Results are similar.

Table 1

: 4 5 6 7 8 9 10 11 12 13 14 15 16

1 I

Trading day I, in quarter

406 308 293 249 285 392 582 825 1058 1364 1685 2193 2628 2415 2613 2512

No. of reports

-0.0016 _ ^... _ -0.0013 0.0042 - 0.0038 - 0.0002 0.0015 0.0051 0.0028 0.0015 0.0014 0.0029 0.0022 0.0029 0.0005 0.0007 -0.04lO5

News measure,’ RaI - 0.76 0.36 1.31 -1.09 - 0.06 0.71 3.26 1.77 1.04 1.73 2.99 3.53 4.77 0.70 0.94 -0.85

f(iq) 0.49 0.45 0.55 0.47 0.45 0.48 0.56 0.51 0.50 0.51 0.53 0.52 0.53 0.50 0.50 0.47

Fraction positive,b Pr( Ry, > 0) 44 39 36 47 x0 1YI 400 601 829 1122 1460 2027 2465 2316 2460 2405

No. of reports 0.001 x - 0.0000 - 0.0033 o.OQ60 0.0032 0.0000 0.0060 0.0013 0.0026 0.0020 0.0034 0.0019 0.0024 0.0005 0.0005 - 0.0005

News measure,a R’ I 0.34 - 0.00 -0.58 1.49 O.Yl 0.02 3.92 0.97 1.75 2.04 3.60 3.13 3.58 0.64 0.67 - 0.74

f(RY)

0.54 0.50 0.43 0.50 0.50 0.44 0.76 0.56 0.62 0.73 0.71 0.74 0.74 0.50 0.62 0.41

Fraction positive,b Pr( Rf, > 0)

Median percent change in Mean earnings days dy’ reported -.___-. 16.7 1.3x 12.4 0.68 0.63 18.1 0.07 ! 5.5 2.37 9.7 2.7Y 14.7 1.09 23.7 15.5 1.87 1.75 17.1 1x.7 I .65 1.39 14.3 1.36 15.4 1.27 14.3 1.10 14.Y O.Yl 13.0 0.82 11.9

news measures for the first 35 trading days of calendar quarters 2 through 4 for the total sample of firms and the subsample of quarters in the period October 1971 through December 1982. Aggregate earuings news effects are measured by the average abnormal (market-adjusted) stock return, Rf, for all firms with earnings reports on a given day in the sample, and by the fraction of such returns that are positive on a given announcement day. _____ All reports Quarterly reports of calendar-fiscal-quarter firms

Aggregate daily earnings firms with calendar-fiscal

8 E 2 D 5 2 x ??

& 2

;

4

!? 2.

3

:

2

934 814

1182 1077

30 31

32 33

- 0.0030 - 0.0007

- 0.0005 -0.0011

-

-

-

0.0009 0.0011 ,. ,.,.,.. U.wtJI 0.0013 0.0007 0.0007 0.0012 0.0010 0.0005 0.0005 o.cOO1 0.0003 0.0003

0.46 0.4x

- 2.38 - 0.42

794 69Y

736 758

0.49 0.47

-0.19 - 0.86

Lb43

2117 1793 1503 1148 992 1015 858 764 690 668

0.49 0.49 0.51 0.49 0.47 0.48 0.49 0.48 0.49 0.48

u.49

2597 2743 ^, .^

0.52 0.50 _ .,.

1.22 1.63 -0.i4 2.13 0.60 0.94 1.11 -0.69 0.35 0.43 - 0.07 -0.21 0.17

- 0.0048 - 0.0014

- 0.0012 -0.0018

0.0012 0.0007 0.0007 0.0004 - o.OQO5 - 0.0005 0.0005 0.0010 - 0.0020 0.0010

U.UUU1

0.0010 0.0008 ^ ^^^_

- 3.23 - 0.57

- 0.54 - 1.03

1.67 0.64 0.91 0.40 - 0.29 - 0.37 0.45 0.53 - 1.12 0.48

0.1X

1.48 1.18 ,. .^ 0.11 0.12 0.01 0.36 -0.14 - 0.41 ~ 0.34 - 1.13 - 0.87 - 1.06 - 0.99 - 1.26 - 1.74 - l.YH - 1.87 - 2.01

0.41 0.53 0.29 0.44 0.38 0.38

0.46

o.i9 0.60 ._

0.59 0.44 0.53 0.53 0.55 0.48 0.50 0.53 0.29 0.50

USJ

0.53 0.62 ^ __

0.0 6.5

6.3 7.0

12.0 10.2 3.7

11.8 12.9 12.0 12.8

ii.5

13.7 12.7

34 35

841 639

0.0029 0.0010

1.59 0.62

0.47 0.4Y

504 251

- o.WO7 - 0.0027

- 0.30 - 0.90

0.0 0.0 ___ _ OThe news measure, R:, is calculated as follows. For each firm i reporting on day f in a given quarter, an abnormal return is calculated for day I as Rf, = (R,, - R,,,) - (Ri, - R,,,), where R,, is the stock return for the firm on day I, R ,,,, is the return on the CRSP equally weighted returns index on day I, and R,, -R,, is the mean market-adjusted return over 100 trading days prior to day /. For each day I, R: =xy:, R:,/tr,, where n, is the number of firms reporting on day I. E: is the mean of R: over all 34 quarters in the sample period. f(R:) is a r-statistic cafculated from the 34 observations of Ry. ‘Pr( RT, > 0) is the ratio of the number of good-news reports (with Rf, > 0) observed on each day I in the sample period to the total number of reports observed on days indexed I (given in the table). ‘Mean days early is defined as the mean over firms of the difference in trading days between the report date and that for the same tiscal period of the previous fiscal year, with a positive value indicating earlier reporting.

2757 2903 _““_ LILU 2318 1909 1693 1311 1031 1162 983 876 837 817

17 18 i9 20 21 22 23 24 25 26 27 28 29

2

:: T R

2

$ & L. 3 2

z_ 2

;

4

6 3_.

2 P

S. H. Penman, Earnings new and seasonahries m stock reruns

208

and none in the last 11 days. The division of the 35-day period into three parts for these comparisons is somewhat arbitrary, of course. The estimated Spearman rank correlation between trading day number in the quarter, f, and RT is -0.35 (with a r-statistic of -2.14) and between trading day and Pr{RTt>O} it is -0.30 (with a r-statistic of - 1.83). These estimates suggest a relationship between time of quarter and the nature of the earning news arriving at the market. On the right-hand side of table 1 values of x; are reported for interim quarterly reports of firms on a calendar-fiscal-quarter basis. These reports (which amount to 77.5% of all reports in the three quarters) cover the same fiscal period (the previous calendar quarter) and nearly all were published in

1

.6

I

.5 .4 .3 .2 .l 0

- .l

. ~

.

.

I

- .2 - .3 - .4 -5

Trading Day in Calendar Quarters, 2-4 Fig. 3. Mean of abnormal announcement returns during the first 35 trading days of calendar quarters 2 through 4 for firms on a calendar-fiscal-quarter basis. Mean abnormal announcement returns, R:, are defined in notes to table 1.

S. H. Penman, Earnings news and reasonalities in stock returns

209

the 35 trading days covered by the table (as indicated in fig. 1). These values of 3; are also presented as a sequence of bar plots in fig. 3 for visual effect. The distribution of earnings news is more accentuated than that for all reports. The estimated Spearman rank correlation between trading day in the quarter and 2: for these reports is -0.60 (with a t-statistic of -4.28) and the estimated rank correlation between trading day and Pr{ R:, > 0} for these reports is -0.81 (with a f-statistic of -7.80). These are considerably stronger correlations than those reported for all reports. Chambers and Penman (1984) and Kross and Schroeder (1984) document that, while firms report earnings on a fairly predictable basis, they tend to bring their reports out earlier than usual when they have good news and to delay reporting bad news. This provides a possible explanation for the time distribution of earnings news observed here at the aggregate level: a higher proportion of reports in the early part of the quarter are those of firms that published early with good news. If this is so, the stronger results on the right-hand side of table 1 may be due to filtering out of annual reports (which are published with greater median reporting lags) and quarterly reports for fiscal r-----nerinds end_i_n_rz tha_n_!_h_eone im_qe&a_& , nrecedim t = 1. -. The __.=____ -‘__c) dav --, 5) other -----column headed ‘mean days early’ in table 1 gives the mean (over firms on a calendar-fiscal-quarter basis) of the difference (in trading days) between the quarterly report date and the date of the report for the same fiscal period in the previous fiscal year. If the latter is (crudely) assumed to be the expected report date, this is a measure of the timeliness of reports. A positive value indicates an early report, a negative value a late report. The relative values over t do indicate that reports published earlier in the quarter are those appearing before their expected publication dates. The estimated Spearman rank correlation between the trading day into the quarter and mean days early for these reports is - 0.87 (with a t-statistic of - 10.21).6 l-L_ I__r CUIUII~ __1..-- III :- *_I_,_ -.‘_.__ .I__ -_1:.._^_^^_.^_^ _I__--_ . .I.,. IIIE: 1a3i iaule 1I gives ine meunin perccn~agc crkingc iii LIIC quarterly earnings (from the same quarter of the previous year) reported by calendar-fiscal-quarter firms on all days t in the sample period. These median values are higher for days in the early part of quarters 2 through 4 than for later ones. The estimated Spearman correlation between these values and trading day in the quarter is - 0.84 (with a r-statistic of - 8.81). So it appears that earnings reports arriving early in quarters 2 through 4 are not only associated with higher price reactions, on average, than those published later, but also reflect a higher quality of accounting earnings (in relation to previous years’ earnings). Thus the differential mean price reactions over time reflect differences in the fundamentals.

6The corresponding estimate for all reports (covered in the left-hand side of the table) is - 0.50 (with a r-statistic of - 3.29).

0.0025 5.07

3638

No. of reports

0.0018 4.06 6004

1

with cdedur /i.sctr I qldcrrlm I YJ a?,)

Reports o/firms

t(Y,) No. of reports

VI

Table 2

0.0013 - 2.05 25740

26836

-0.0006 -0.80

- 0.0025 - 3.80 10407

-0.0017 - 2.36 11095

Half-month

I

- 0.002tl -3.15 2891

6294

o.Ow2 - 0.42

neriod.

O.0031 1.66 210

0.0012 0.78 3964

- 0.0106 - 2.81 67

-0.0004 - 0.38 3323

6

6.19 !O.ooO!

2.24 (0.047)

F statistic’

4, for

5.1185

5,2035

Degrees of freedom

of tests of the hypothesis that mean abnormal announcement returns are the same in each half-month period within quarters 2 through the total sample of firms and the subsample of firms with calendar-fiscal quarters in the period October 1971 through December 1982

Reports o/u11 jirms

Results

- 0.0030 - 4.57 9511 /our hoi/month

- 0.0058 - 6.21 1756

+ y.,Js,, + e,

- 0.0306 - 2.72

25151

3271 9511

- 0.0537 - 4.73

1756

- 0.0995 - 6.95

Pr(R~,~0)=u,+u2d2,+u,d,,+uqd4,+~,

Put~el C: Reports published over/d

,-0.0016 - 2.71 25151

0.5393 57.25

0.0027 5.61 3271

R: = x + YzJ~, + ~43,

hdfmonfh

periods h

periods”

(O.OtW

1x.37

14.x4 (0.000)

3,lOlO

3. 1010

“Rf, the mean abnormal announcement return. is defined in the notes to table I. (1,,, j = 2,. (6 are dummy variables corresponding to successive half-month periods in calendar quarters 2 through 4. ‘Pr( RT, > 0) is the ratio of good-news reports on day I to the total number of reports on day f. A good-news report is delined as one where R:, > 0, where R:, is defined in the notes to table 1. J,,, j = 2,. ,4. are dummy variables corresponding to the second to the fourth half-month periods in quarters 2 through 4. ‘Numbers in parentheses indicate probability values for the observed F-statistic under the null hypothesis. F-statistics and r-statistics in both panels A and B are from estimation where the abnormal return for each tirm, Ry, is standardized by an estimate oL’ the standard deviation of abnormal returns (over a lOO-day trading period prior to the report date) prior to the averaging in R:.

f(B,) No. of reports

UJ

with culendur jiscul qrrs.

Interim reporrs oj Jirnls

I(?,) No. of reports

7,

Inlerini reporls of firm with culendur-jscul yrrs.

Panel B: Reporrs published mer fhejirsrfour

212

S. H. Penmun. Earnqs

news and seusonnlmes

in sock

return

To test formally the null hypothesis that mean abnormal announcement r~.+r,t-n~ grp ihe d the .IcYLI*., u1.s L&1_TQ~TIP LIUIIIWnn “11 mph bU1II trarlino .‘U..YA~ Aav u&L, in L&Inttcarterc .q._.U’L”LII I7 thrmtoh ““““~‘ 7. L&lbfnllnwinn L”L’“..“‘6 model was estimated using ordinary least squares (OLS) techniques:

Here t covers all trading days in quarters 2 through 4 in the sample period, not just the first 35 days. Each quarter is broken up into six half-month periods (with days 1 through 15 of each calendar month being one period and days 16 through the end of the month being the other period). The dummy variable d,, takes the value 1 if t is in the second half-month period (the last half of the first month of the quarter) and 0 otherwise; d,, takes the value 1 if t is in the third half-month period (the first half of the second month in the quarter) and 0 otherwise; and so on, so that d,, applies to the last half month of the quarter. The coefficient yi represents the mean abnormal announcement -a+..:.. rh, h-IF -,-.S.+h “I -F +I.m..nr+nr /: a rhGrrt h,lF eC AmAl r..,.. UIG 1113L UQll "I rip"", July LGLUIIL 111 LUGG,,+ ,113LIIaII-LII”IILII UK qua LCI\‘.‘., and October), which covers approximately 10 trading days. Coefficients y,, j=2,..., 6, represent differences between mean abnormal announcement returns in the first half-month period and those in the respective half-month periods following. Estimates of these coefficients are presented in panel A of table 2 using, first, all reports on day t in the calculation of R; and, second, reports of firms on a calendar-fiscal-quarter basis only. The value of an F-statistic with the indicated degrees of freedom is given to the right of the panel. This is relevant to the test of the null hypothesis, yz= y3 = y4= ys = y6 = 0. The mean announcement abnormal return for the first half-month period in both estimations is iarge and positive. For both estimations the k-statistics are significant at a high level of confidence. The stronger results for calendar-fiscal-quarter firms reflect the exclusion of reports whose arrival times are distributed differently throughout the quarter. The results are more impressive when only interim quarterly reports of the firms on a calendar-fiscal-quarter basis are included. In this case, there are very few reports in the last month of the quarter so estimations are performed on mean abnormal announcement returns in the first four half-month periods of the quarter.’ The results are shown in panel B of table 2. Mean announce‘Some days in the sample period had few reports. So as not to give undue weight to days when the sampie may not be representative, estimates here exciude days for which there were fewer than five reports. The mean abnormal daily returns (R;Z,) associated with announcement of the 274, 2 and 389 reports excluded in half-month periods 1, 3 and 4, respectively, are 0.0029, -0.OOG5 and 0.0030. No reports were excluded in period 2. Except for the fourth-period result, these are consistent with the estimated coefficients in panel B of table 2. The mean abnormal announcement return over all 2.145 reports (included and excluded) in period 4 is - 0.0024. Thus the results here are not induced by the requirement of at least five reports in the calculation Rf. As the exclusion level is increased, mean differences and significance levels also increase. Similar comments apply to the estimations in panel C of table 2.

S. H. Penmun, Earnmgs news and seasonahnes

WI

srockrewns

213

ment abnormal returns in the second half of the first month of quarters 2 through 4 and in the second month of these quarters are significantly below those in the first half month, as indicated by the F-statistic and the signs on the coefficient estimates.8 Similar results are obtained when the dependent variable is specified as the news variable, Pr{ Rfr > 0}, as indicated in panel C of the table. In both panels B and C the estimated coefficients decline monotonically over the four half-month subperiods. Estimated serial correlations of the residuals of these regression equations are close to zero. These results indicate a time distribution of earnings news within the last three calendar quarters. The results are consistent over a variety of subperiods in the sample period and over the three quarters. This robustness lessens the likelihood that the results are due to a few outliers in particular observations or time periods. The results are probably conservative because there is some doubt whether the precise report date has been picked up for all firms, as indicated in section 2. Thus the tests are biased toward the null hypothesis. Note further that, as a deliberate research approach, no attempt was made (when specifying dummy variables) to define periods within calendar quarters tn -QY;~;VP .IO~I,P nf thna rt~t;rt;rr 6” III-II-C .LI1Ub “I $llQ tart CG.T& LILUsl.Js‘r... To test for a relation between the nature of earnings news and timeliness of reports, the following model was estimated using all reports available on each trading day in the sample period:9 RF = a + BMDE, + w,,

(4)

where MDE, is the mean days early of reports appearing on day t, as defined earlier. The OLS estimate of b was 0.0003 with a t-value of 2.70, indicating that early news announcements tend to be related to positive abnormal stock returns and later announcements to lower abnormal stock returns. A relationship between the explanatory variable here and calendar time was evident in table 1. To formalize this relation further, a dummy variable regression equation similar in form to that in panel B of table 2 is estimated with the dependent variable defined as mean days early. Coefficient estimates of 1.83 days, - 1.08 days, -2.47 days and -4.30 days corresponding to the first four half-month periods in quarters 2 through 4 are observed. The observed value of F3.1010is a highly significant 230.12. The calendar time distribution of the timeliness variable, mean days early, together with the observed relation ‘Because in different

the number half-month

of firms in the calculation of the dependent variable may vary over days periods, the variance of the residuals may differ over the half-month

periods. The estimations were repeated after muitipiying I?; by d7, firms in the calculation of Rf. Similar results were found.

where n, is the number

of

9This result is also based on estimations excluding trading days with fewer than five reports to deal with outhers in both dependent and independent variables on days with relatively few reports.

214

S. H. Penman, Earnings news and searonalitles IIIstock refurru

between this variable and the nature of earnings news, suggests that the distribution of earnings news over time may be due to the reporting behavior of firms documented in the Chambers and Penman paper. In documenting the distribution of earnings news over calendar time, the discovery of explanatory variables is not an issue. One issue demands attention, however, in interpreting these results. Earlier it was observed that mean abnormal announcement returns over all the reports in the sample are positive and significantly different from zero. If this is evidence of a higher return premium demanded by the market during periods of earnings announcements (because of higher risk in these periods), and if firms with higher earnings announcement risk report earlier than others, the results could be documenting higher announcement return premiums for early reporting firms rather than a distribution of good and bad news over time. To check this, the tests in table 2 were repeated after subtracting from the abnormal announcement return for each firm at each report date [in (l)] the mean abnormal announcement return for that firm over all other report dates in the sample period. The results were similar to those above. More generally, the results were consistent nv~r alternative I v ‘~__“‘~_““.” an&firntinn< of ‘nnrmal’ r,=tllmc* the v. v. U.1...W.I ..VI ..I_. _V.Ul..Y. ..A_ tP
S.H. Penman, Eammgs

news and seawnalirles

m stock returns

215

to be surviving firms, which (as a conjecture) are firms with good earnings performance over the sample period. But since results do not differ when abnormal announcement returns for each firm at each report date are compared with mean abnormal announcement returns over all other report dates, this conjecture can be dismissed.

4. The distribution of aggregate returns within calendar quarters Table 3 summarizes observations on CRSP equally weighted (EW) and value-weighted (VW) market return indexes within calendar quarters over the period July 1962 to December 1982. For reasons of space, return measures are not presented for each trading day in the quarter as in table 1, but are summarized for five-day trading periods (approximately seven calendar days) within quarters. There are approximately 60 trading days in a quarter, giving 12 periods. l1 Each sequential pair of five-day periods covers approximately half a calendar month. Observations for quarters 2 through 4 are pooled (for conciseness): __--__-------,, it is important r-m--~-m--observed are r -------- to emphasize ----r ------ that the patterns evident in each of the three quarters. The relatively high values of the return measures in the first four five-day periods of quarter 1 (covering, approximately, the month of January) summarize the well-documented January effect. This is particularly strong in the first 10 trading days of January. The striking aspect of the table, however, is the relatively high values of the reported measures for the first 10 trading days of quarters 2 through 4 (periods 1 and 2). For example, for over 70% of the time the return on the EW market index is positive during the first two five-day periods in quarters 2 through 4, compared with 57% over periods 3 through 12. Similar observations can be made about Pr{ R,,, > 0} which -^^ . . .._^^ rL, ,,I,.+:..^ ,..-ISa, ^F .._ -,,I,,* A....* :, .-..-.,I.,,..zAA -b-l.* -_"_ ‘l,czl3UIC3 LllC Iwallvc 1IluII"~I "I LqJ-luallnGr uay> 111 Gdlrll pu1vu. 111c 111G411 return on the EW index over the first two five-day periods is 0.82% compared with 0.13% over periods 3 through 12. The higher mean returns in the first two five-day periods of quarters 2 through 4 are not associated with higher standard deviations of returns, however, unlike those for quarter 1. The apparent seasonality in the return on the equally weighted index during quarters 2 through 4 is not as strong as that in the first quarter. But although there are large differences between the statistics for the EW and VW indexes in January (indicating a particularly strong effect for small firms), this is not so for the statistics reported for the first ten days of quarters 2 through 4. The seasonality observed in quarters 2 through 4 does not appear to be primarily a smaii-firm phenomenon. lLAll quarters except one have at least 60 trading days. Most have 1 to 5 more. Thus the last twelve-day period consists of more than five days in most cases.

S.H.Penman, Earntngs

216

Consecur1re

Equally w&ted

five-day trading petiod T

news ondseasonalirtes

VI

stock returns

return,Index

Quarter 1

Quarters 2-4

Std.dev.

Std dev. Pr(R,,,,> Oi

R,,

CR,,)

0.0073 0.0091 -0.ooo5 -0.0066

0 0228 0.02x2 00138 0.0256 0.0217 0.0217 0.0244 00326 003:6

0710 0.726 0.548 0.468 0.645 0.661 0.532 0.532 062':

0.650 0.550 0600

0.760 0.710 0660 0.690 0.590 0.570 0550 0.580 nL_)n "."L" 0630 0570 0.560

0.0229 OOlY5 00206

0.5Y7 0.500 0627

0.645 0.656 0.526 0.484 0.613 0.584 0.519 0.577 0.63Y 0.603 0.521 0.548

00254

0663

0.623

00025

OOl5l

0.59X

0 318

OOO62 00048 00QlO

00245 0.0161 0.0137

0.7txr 0.700 0600

0640 0.590 0.540

ow69 0.0074 -0.O0Qx

00119 00273 00183

4 5

0006X -0OOOx

0.0241 00143

0700 0.600

0.560 0.520

-00051 0.0069

00111 0.0'27

0.645 062') 054x 0.468

0.5Y3 0.552 0.487 0.484

6 I

OOW8 -00011

0.0160 O.OL9Y

0.650 0550

0.560 0.480

8

-00022

0.0204

0 4O0

0.540

-0.0029 00017

0.0032 0.0053 -00002 OtN16

0.0212 00162 00164 0.0186

0550 0.750 0600 0.650

0.620 0.610 0500 0.550

00051 0.0030 -0.002Y 0.0034

o.w21

0.0185

0.621

0.553

R",,

CR,,,)

00368 0.0142 00093 0.0133 00048 00033 00017

0.0434 0.0237 0.0151 0.0286 00196 0.0191 0.0259 00206 nn,,i "."_,_I

OYOO 0.750 0750 0.750 0 550

10 11 12

OOO67 00023 OcMl28

O.OlYX 00208 001x9

All T

000x3

L 2 3

1 2 3 4 5 6 1

a 9

9 10 11 12 All r

- o.cms n nnn, v-j

Pr( R,,,'O)

0650 0650 0550 Ox%

0.0054 00043 -0.0026 00013 NOGO 0.0033 -0.0029 00033

0.0031

O.CiL!?

Pr(R,,'O)

Pr(R,,,'O)

OOi63

0.597 0.62')

0 5x1 0568

00229 00280 00253 0.0197 OOlYl 00178

0419 0.532 0.565 0.629 0.517 0.593

0.490 0.4Y-i 0.581 0.574 0.495 0.518

0.0222

0.564

0.535

0) IS ax,, is the mean five-dayindex return m period I over allsuch 62 periods in the 201.year period Pr( R,,,> the ratio of the number of times the five-dayIndex return was positivefor the period r to the totalnumber of the five-daypetiods T in the sample period.which is 62. Pr(R,,, ~0) is the ratm of the number oftradingdays obserwd in the five-dayperiod 7 with positive index returnsto the totalnumber of tradmgdays the sample period.which is 310.

in the five-dayperiod I during

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pue ‘p

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luaura3unouuE

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(5) :paiew!lsa sno?eA

s!

‘EfJ

+

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+

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laporu Ou!.tioIlo3 aqi ‘b @noJqi i: sJaiJEnb uqi!m

Jaho aIues aql aJr! suJnlaJ alEBaJ88E UE~UI luql s!saylodLq

spouad

Isal 01

aql

0.0077 0.488 - 2.45

0.0082 0.572 1.84

I? ,i L,)

Std. dev. (i?,,,)

-0.00015 - 0.76 0.0033 0.494 -2.19

- 0.00032

- 1.63 0.0037 0.5OY -1.47

0.0035 0.570 1.67

weighted index re/unrs -

0.0077 0.562 1.36

- O.OUOX - 1.77

0.00016 1.16

within

0.0037 0.574 1.91

- o.ooOO2 - 0.09

V&e-weighred

0.0091 0.526 - 0.45

- 0.010 - 2.30

index relurns

0.0095 0.576 -0.11

2 through

0.0033 0.527 - 0.48

o.OOoO1 0.04

itrdex rearm

0.0078 0.549 0.73

-0.0012 - 2.76

0.0076 0.588 0.55

-0.0012 - 2.79

+ 5,

quarters

0.0037 0.549 0.62

0.00012 0.61

0.0074 0.517 -0.113

-0.0012 - 2.68

0.0074 0.554 - 1.26

~ 0.001 I - 2.46

4 in the period

1.26 (0.22X)

(0.004)

3.45

(0.000)

4.65

July 1962 through

the number

corresponding to successive half-monlh periods in calendar quarters 2 through 4. Pr( R,,,,, 1 0) is the ratio of of positive daily market returns observed in the relevant half-month period, j, to the total number of trading days in Ihe period. r[Pr( R,,,,, > O)] is a binomial r-statistic relevam to a test of whether the ohservcd value of Pr( R,,,,, > 0) is different from the average value over ah periods. It is distributed standard normal conditional upon the null hypothesis. ‘Numbers in parentheses indicate probability values for thr observed F-statistics under the null hypothesis.

6, are dummy variablrs ‘cI,~, j=2 ,...,

Pr( R,,, > 0) r(Pr( R.,,, > 011

Std. dev. (A,,,)

Cl l(q)

s.

Pr( JL,, > 0) r(Pr( R,,,,, > 011

Std. dev. (R,,,)

A,,,, = Eywlly

-0.0018 - 3.96

0.0014 4.36

Pr( L, > 01 rIPr( R,,,, > 0))

j

- 0.0010 - 2.38

period,

i,,,, e Value-weighrerl

0.0073 0.589 0.59

0.0076 0.510 - 3.58

Half-month

0.0075 0.656 3.97

l((i)

Table 4 in half-month periods December 1982.”

= c, + Cada, + c,da, + c4d4, + c5d5, + c&,

index returns

- 0.0009 -2.15

1

R,,

of mean daily market

- OS!021 - 4.78

of tests of equality

0.0016 4.96

r,

Results

S. H. Penman. Earmngs new and seasonalines UIsrock rerums

219

significant at the 0.025 level. Thus, in both cases, the null hypothesis can be rejected. Similar results are obtained from a comparison of rankings on I+{ R,, > 0} (defined in table 3) for all the twelve five-day periods. Repeating the tests on the differences between EW and VW index returns results in a value of ,r:i of 9.97, which is not significant at the 0.10 level. These non-parametric results indicate that the mean five-day return differences are not due primarily to a few outliers.i3 A further inspection of the distribution of daily returns within each five-day period also reveals that the higher mean daily returns observed in the first half month of quarters 2 through 4 in table 3 reflect a general location shift and not just an increase in positive skewness in daily returns during those periods. It is not the case that bull markets (or few bear markets) tend to occur in the early part of quarters. Further, the higher mean returns in the first half month of quarters 2 through 4 are not realized primarily on a few days within that period, as in the case of the early January effect. Ariel (1987) has found that market index returns over the period 1963 to 1981 are higher in the first half of calendar months than in the second half. The t-statistics on all coefficients in table 4 are large (in a negative direction), including those on coefficients 3 and 5 (corresponding to the first half of the second and third months of the quarter). Mean returns in the first half of the first month of quarters are higher than those in all other half months, not just in second half-month periods. Thus the observed effect here is not a withinmonth effect but rather a within-quarter effect identifiable with the first half of the first month of the quarter. A within-month effect may also be evident for, when Ariel excludes the first month of each quarter, he still finds differential mean returns within months. However, he defines a half month as beginning the day prior to the literal half-month period and ending the day before the end of it. The coincidence of higher mean market returns with the period during which aggregate earnings news is good is striking. In an attempt to discover whether differences in market returns can be explained by the arrival of earnings news, the following regression model is estimated from returns for the period October 1971 to December 1982:

R,, = cf+piQ+_t. fi,,,, is the market return for the five-trading-day periods for which returns are summarized in table 3, and nT is an index of earnings changes reported in the 13Besides giving less weight to outliers, this test has the advantage that the observed serial correlation in five-day returns is far less than that in the daily returns used in the regression tests on means.

220

S. H. Penman, Earnings n-s

and seasonahes

IIIsock returns

relevant five-day period. To calculate dl,, the earnings change (from the same fiscal period in the previous fiscal year) reported by each firm is standardized by the standard deviation of earnings changes estimated from the time series of prior earnings changes for the firm. Then an arithmetic average is taken over all firms reporting in each five-day period, T. Five-day periods are specified rather than daily periods because of uncertainty in identifying the precise day of earnings reports. The purpose of this estimation is not only to see whether aggregate stock returns are related to aggregate reported earnings changes, but also to discover whether the seasonalities evident in A,,,, are also evident in the disturbances, ?,, which capture market returns adjusted for the implications of earnings news. Estimation of (6), however, yields a slope coefficient close to zero. Similar results obtain when the earnings variable is specified as median standardized earnings changes and median percentage earnings changes (as reported in table 1) and when the analysis is repeated for one-day and ten-day periods. Security prices react to the news component in earnings, and it is likely that measures based on published earnings capture the surprise element of earnings with considerable error. Note that mean standardized earnings changes reported by firms on a calendar-fiscal-quarter basis during the first four half-month periods of quarters 2 through 4 are 0.483, 0.449, 0.224 and 0.159, respectively. The results in table 4 are evident in various subperiods during the years 1962-1982 and for quarters 2 and 4. Twenty years, however, is rather a short time from which to generalize about market behavior. Table 5 summarizes returns on the Standard & Poor’s (S&P) Composite Stock Price Index for half-month periods from the date of its first availability, January 1928, to June 1962, immediately prior to the availability of CRSP indexes of daily returns. This is a value-weighted price index and returns calculated from it do not include a dividend component. It covered 90 NYSE stocks until March 1, 1957 and 500 NYSE stocks thereafter. Values of the index were obtained for the 15th and the last day of each calendar month (or the last trading day before if these days were trading holidays) and half-month returns were calculated from these values. Table 5 gives mean and median values and standard deviations for these returns, together with r-statistics on the means, for the six half-month periods in calendar quarter 1 and quarters 2 through 4 pooled. Values are given for the whole period and for two (roughly equal) subperiods, 1928-1945 and 1946-June 1962. Mean and median values indeed appear to be substantially higher than average in the first half-month periods in quarters 2 through 4, and consistently so over subperiods. The effect in the first half of January appears only in the 1928-1945 period. A half-month return on the valueweighted S&P index (which is made up of relatively large firms) may not pick up what is primarily a smalLfirm phenomenon in the first few days of January.

0.0025

All half-months

0.0186 0.0065 0.0065 0.0050 0.0080 0.0039

0.0093 0.0054 0.0006 - 0.0006 0.0036 0.0014

Median

Full period,

Table 5

0.0460 0.0546 0.0448 0.0448 0.0479

0.0396 ,0.0411 0.0355 0.0320 0.0434 0.0623

Std. dev.

1928-1962

0.0018

0.0151 - 0.0068 0.0059 - 0.0050 - 0.0008 0.0049

0.0226 - 0.0036 0.0071 -0.0017 0.0079 - 0.0289

Mean

within calendar

period

0.0057

0.0133 - 0.0052 0.0066 0.0021 0.0032 0.0030

0.0203 - 0.0017 0.0149 - 0.0006 0.0017 -0.0121

in quarter

0.0603

0.0581 0.0723 0.0557 0.0574 0.0602 0.0595

0.0466 0.0509 0.0418 0.0380 0.0599 0.0801

Std. dev.

1928-1945 Median

for each half-month

1.53

2.83 - 0.33 1.08 -0.81 0.35 0.68

1.65 0.36 -0.10 - 0.37 1.05 -0.94

I

stock price index over half-month periods 1962.”

“For the full period, there are 35 return observations half-month period in quarters 2 through 4. I = mean/estimated standard error of the mean.

0.0128 -0.0018 0.0047 - 0.0036 0.0016 0.0031

1 2 3 4 5 6

2-4

0.0112 0.0025 -0.0006 - 0.0020 0.0077 - 0.0099

Mean

1 2 3 4 5 6

Halfmonth

Quarter

on S&P composite

1

of returns

Summary

1 (except

0.62

1 .Yl - 0.69 0.711 - 0.64 - 0.09 0.60

2.00 - 0.30 0.72 -0.19 0.60 - 1.53

I

quarters

192X through

0.0071

0.0196 0.0094 0.0017 0.0053 O.oOY7 0.0040

-0.0166 0.0054 - o.cQ79 - 0.0035 0.0108 0.0053

Median

0.0259

0.0275 0.0224 0.02xx 0.0250 0.02Y2 0.0249

0.0206 0.0251 0.0236 0.0227 0.0256 0.0260

Std. dev.

1946- 1Y62

January

2.47

‘2.63 1.16 0.85 -- 0.57 1.03 0.31

- 0.02 1.46 - 1.52 - 0.40 1.21 1.60

I

June

the first, which has 34) and 103 for each

0.0032

0.0104 0.0037 0.0035 - 0.0020 0.0043 0.0011

- 0.0001 0.0089 - 0.0087 - 0.0022 0.0075 0.0101

__ Mean

in the period

222

S. H. Penman, Earnmgs new and seawnaltrles in sock returns

A Kruskal-Wallis statistic calculated from the relative rankings of these returns in these six half-month periods in calendar quarters 2 through 4 yields a value of x: of 10.50. Given the null hypothesis of no differences in the distribution of the half-month returns, the probability of observing this value or greater is 0.062. Given that the &i-square approximation provides a conservative test for significance levels of 0.10 or less [Kruskal and Wallis (1952)], the null can be rejected with some confidence. It appears, then, that a beginning-of-quarter mean effect in aggregate returns persisted during the 55 years from 1928 to 1982. As with the 1962-1982 period, the standard deviations of returns in the 1928-1962 period (reported in table 5) do not appear to be higher in the early part of quarters 2 through 4 than at other times during these quarters. Higher mean returns without an associated increase in variance of returns suggests a market inefficiency.i4 5. The distribution of good and bad earnings news over days of the week Cross (1973), French (1980), and Gibbons and Hess (1981) among others, have documented that aggregate returns are, on average, lower on Mondays than on other days of the week. Keim and Stambaugh (1984) found that mean Monday market returns have been persistently negative since 1928. Attempts to provide explanations for the phenomenon [Lakonishok and Levi (1982) and Keim and Stambaugh (1984), for example] have been unsuccessful. Given the association observed above between earnings news arrival and a market seasonality, it is reasonable to ask whether the Monday seasonality is associated with the arrival of bad (earnings) news. The popular wisdom appears to support this conjecture: firms tend to release bad news after the close of trading on Friday to give investors the weekend to absorb the shock.i5 14The observed seasonality in market returns suggests another explanation for the results in the previous section. If the market returns tend to be higher than average in the early part of quarters 2 through 4, and if tirms reporting in that period are, on average, firms with higher systematic risk, one would expect the measured market-adjusted returns observed in the period to be higher than those expected on the basis of returns observed in periods outside the early part of these quarters. Thus the abnormal announcement returns observed could merely reflect higher expected returns in this period. Estimates of systematic risk were calculated for all firms in the sample from daily returns, using procedures outlined in Cohen, Hawanini, Maier, Schwartz and Whitcomb (1983). The mean estimated betas for firms reporting in the first half-month of calendar quarters 2 through 4 are not significantly different from the mean estimated betas of all firms in the sample and are close to unity. t5The practice is not peculiar to corporations: apparently public relations people in the White House and federal agencies tend to release bad news or politicahy sensitive news late Friday. “It was one of the first lessons I learned when I arrived in Washington,’ said David R. Gergen, who recently left his post as assistant to the president for communications. ‘If you’ve got some news that you don’t want to get noticed, put it out Friday afternoon at 4 p.m.” See ‘TGIF in D.C., good timing for bad news: Unpopular policies are disclosed late on Friday’ by Stephen Engelberg of the New York Times. Reprinted in The (&k&d) Tribune, April 7, 1984, page 1, column 1.

S. H. Penman, Earntngs new and seasonahes

VI stock returns

223

Pate11 and Wolfson (1982) discovered that, on any day, bad-news announcements are more likely to appear after the close of trading than good-news announcements. Further, they found that a higher proportion of announcements appears after the close of trading on Friday than on other days of the week. Post-closing Friday announcements will affect Monday prices. To discover whether bad earnings news tends to be reflected in Monday prices, the following model was estimated: R; = y; + yjdz,

+ y;d,, +

yid4,+ Yi’dst+ e;t

where RF, the mean abnormal announcement return on day t, is the earnings news variable defined earlier. The dj,, j = 2,. . . ,5, are dummy variables corresponding to Tuesday through Friday, respectively, and take the value 1 if the day t corresponds to the index j, and 0 otherwise. The coefficients y,‘, j=2 , . . . ,5, correspond to excess mean abnormal announcement returns on Tuesday through Friday, respectively, over those on Monday. The null hypothesis that y; = y; = yd = y; = 0 is equivalent to the statement that mean abnormal announcement returns do not differ by the day of the week on which reports appear. The results of the estimation over the period October 1971-December 1982 are given in panel A of table 6. The value of the F-statistic indicates that the null hypothesis can be rejected, and the relative sizes and signs of the coefficient estimates indicate that mean abnormal announcement returns on Tuesdays through Fridays are higher than those on Mondays.i6 The estimated coefficient corresponding to Monday is not negative, however, although this could reflect that a premium for announcement risk has not been subtracted. When such an adjustment is made, the estimated coefficient values are - 0.0010, 0.0014, 0.0022, 0.0017 and 0.0007, respectively, and the F-statistic is 2.71 with p-value of 0.029. In definin, 0 the dependent variable in these regressions, the market return is subtracted so that the results do not reflect differential mean market returns over days of the week. Results similar to those in panel A of table 6 are found when expected returns were estimated from returns for the same day of the week as the report day. In panel B of table 6 results are presented with the dependent variable defined as the news variable Pr{ Rf, > O}. Although the F-statistic is large, note the negative sign and size of the coefficient corresponding to Friday. This (together with the small value of 4; in panel A) suggests a relatively high number of bad-news reports on Friday (prior to the close of trading) as well as on Monday. In a separate analysis, mean Friday abnormal announcement returns were found to be significantly less than those on other days of the 16As before, days with fewer than five reports are excluded in the estimations.

returns 1982.”

Table 6

$d.)

Day, i

127.3 60.0 34.4 21.2 13.2 5.1 -6.3 - 25.5 -61.5

13704

122.4 58.X 34.0 21.9 14.1 6.X - 3.6 -23.8 -61.2

16759

0.0023 3.21

+ ~;d.,r + y;d,,

+ e:

117.9 56.4 33.3 21.8 13.4 5.9 -4.9 - 24.3 - 60.0

16896

0.497 (84.74)

0.0145 1.78

0.0054 0.66

Pr( Rrl > 0) = 0; + u$d,, + U;d,, + u&d.,, + u;d,,

+ p:

0.0037 0.45

13156

0.0009 1.16

5 (Fri.)

indicating

- 0.0250 - 3.02

6.53 (O.OW

3.39 (0.009)

December

days Tuesday

1971 through

126.6 58.5 32.5 20.0 11.1 2.3 - 11.1 - 32.6 - 73.5

variables

Prrael B: Proportion ofreports for which uhnornwl reams an report dure is positive. Pr( Ry, > 0)

126.9 58.5 33.3 19.6 10.3 1.0 - 14.0 - 36.1 - 80.7

+ y;d,,

0.0018 2.43

R: = v; + y;d,,

0.0020 2.12

4 (Thurs.)

over days of the week, in the period October

‘Rf is defined in the notes to table 1. Pr( Rf, > 0) is defined in the notes to table 2. (I,, , j = 2,. ,5, are dummy through Friday. bNumbers in parentheses indicate probability values for the observed Fstatistics under the null hypothesis.

,{a; )

65’

Deciles of percentage in earnings reported: 9 8 7 6 5 4 3 2 1

14697

0.24

I(?;)

No. of reports

2 (Tues.)

announcement

Punel A: Meutr ubtrorn~ul rr~urm on emwings report due, Ry

0.0001

change

earnings

1 (Mon.)

of mean abnormal

?,I

Results of tests of the equality

M P

S. H. Penman, Earnrngs news and seosonalrr~es III srock returns

225

week except Mondays. This result could be due to a misclassification of Monday and/or Friday report dates, but this does not seem likely, given Standard & Poor’s (stated) procedures for recording report dates.” In general, however, results in table 6 contain some error due to the imprecision in specifying report dates. A Kruskal-Wallis test on both news measures, RT and Pr{ Rft > 0}, for the five days of the week produces highly significantly &i-square values. Panel A of table 6 presents deciles of percentage changes in earnings (over the same fiscal period in the previous year) reported on the respective days of the week. Consistent with the return results, median percentage earnings changes are lower on Mondays (and, to a lesser extent, on Fridays) than on other days. More significantly, values of the first, second, and third deciles are substantially less than those on other days. Mean standardized earnings changes [as calculated in (6)] reported on the five days of the week are 0.170, 0.412, 0.430, 0.417 and 0.243, respectively. Thus, it appears that the price effects are related to amount of earnings reported.‘* Although earnings information is only a part of total information arriving at the market, the results here (the Friday result aside) do suggest an informational reason for the Monday effect in security returns, particularly if similar disclosure practices are followed for other (bad-news) information. Rogalski (1984) finds the negative Monday returns in the S&P500 Index and DJIA Index during periods in the 1970s and 1980s accrued from Friday close to Monday open and not during trading on Monday.” This is consistent with the arrival of bad news over the weekend and thus with the informational explanation.20

“When the report date is defined as the day with the highest absolute value of return in the three-day period covering the day before, the day of, and the day after the Standard & Poor’s date, the null cannot be rejected. When the report period is defined as the day of and the day before the Standard & Poor’s date, results similar to those in table 5 are obtained. ‘*To discover whether reports released on the various days of the week can be characterized as arriving early or late in relation to a prediction, the dummy variable regressions were repeated but with the dependent variable defined as mean days early. If firms do follow the strategy of releasing bad-news reports on Friday or after the Friday close, this may require some delay in relation to past practice. The estimated coefficients were -0.02. 0.25, 0.14, 0.17 and 0.05, respectively. These estimates indicate some delay in Monday and Friday reports in relation to those on other days of the week. However, the F-statistic is an insignificant 1.27. 19Smirlock’s and Stark’s (1986) hourly observations of the Dow Jones Index over the period 1968 to 1983 (but not 1963 to 1968) are consistent with this result. Using transaction data from December 2, 1981 to January 31, 1983, Harris (1986) finds that, for relatively large firms, the negative effect is apparent from Friday close to Monday open but for smaller firms it is apparent during trading on Monday. He finds, however, that for all firms the first 45 minutes of trading on Mondays generate returns significantly below those during the first 45 minutes of other days of the week. *‘The negative

beginning-of-quarter returns seasonality observed in section Monday returns in the first half month of calendar quarters.

4 is not

due

to fewer

226

6. Summary,

S. H. Penman. Earmngs news and serrronahes in stock returns

and discussion of results

An intraquarter distribution of aggregate earnings news is evident from the preceding analysis. The news in earnings reports released during the first two weeks of calendar quarters 2 through 4 in the sample period was, on average. good news that affected the stock prices of the reporting firms favorably. Reports issued later in the quarter were more likely to affect stock prices negatively. The analysis indicates that this phenomenon can be explained, in part at least, by firms’ practice of releasing earnings reports early when they have good news and delaying reports when the news is bad. In addition, an intraweek reporting pattern is evident. Bad news was more likely to reach the market on Mondays and Fridays during the sample period than on other days of the week. No explanation is provided, although the reported practice of firms’ releasing bad news over the weekend could explain the Monday result. The arrival of (on average) favorable earnings news at the beginning of calendar quarters 2 through 4 coincides with a seasonality in aggregate returns. Mean market returns were significantly higher on average in the first two weeks of these quarters over the period January 1928-December 1982 than at other times during the quarters, and this pattern persists over subperiods. For the period July 1962-December 1982, the effect is evident for both the equally weighted CRSP index and the value-weighted CRSP index, but not for their difference. So the effect cannot be identified particularly with small firms, as can the January effect which is evident in the early part of the first calendar quarter. With no factor identified that can explain the mean returns shift, the observed beginning-of-quarter seasonality in market returns admits the possibility of market inefficiency. No extant model describes expected returns on (risk of) corporate wealth being related to calendar time. In the absence of satisfying explanations for the phenomenon, one is left guessing. One might conjecture that higher mean returns during the early part of quarters 2 through 4 reflect higher risk in holding corporate assets during periods when information about aggregate corporate earnings arrives at the market. T’he higher mean returns during these periods, however, are not associated with higher variance of returns. This observation suggests a market inefficiency: one apparently can be rewarded with higher mean returns without taking on higher variance. It may be, of course, that the perceived probability of large bad-news outcomes during the early part of quarters 2 through 4 is greater than the relative frequency of those outcomes during the 55 years investigated, so that the sample means and variances of market returns are overstated and understated, respectively, in relation to their ex ante values. One might further conjecture that the beginning-of-quarter seasonality is a tax-induced phenomenon (following a rationalization for the January effect)

S. H. Penman, Eammgs

news and searonahries

in stock refums

227

with a significant number of investors (non-residents and corporations, for example) on non-calendar tax years. The evidence here does not point to a small-firm effect, however, which the tax rationalization predicts. The coincidence of positive aggregate earnings news and higher mean returns in the early part of quarters and the coincidence of negative aggregate earnings news and negative mean returns on Mondays gives rise to speculation that the market reacts mechanically to the arrival of news.*’ This conjecture is hardly pleasing, however, from an equilibrium perspective.

References Abdel-Khalik. A. Rashad, 1984, A note on the WSJ as a source of ‘event’ dates, Journal of _&counting Research 22, 758-759. Ariel. Robert A.. 1987. A monthlv effect in stock returns. Journal of Financial Economics 18, 161-174. Chambers, Anne E. and Stephen H. Penman, 1984, Timeliness of reporting and the stock price reaction to earnings announcements, Journal of Accounting Research 22. 21-47. Cohen, Kahnan J.. Gabriel A. Hawanini, Steven F. Maier, Robert A. Schwartz and David K. Whitcomb, 1983, Friction in the trading process and the estimation of systematic risk, Journal of Financial Economics 12, 263-278. Cross, Frank, 1973, The behavior of stock prices on Friday and Monday, Financial Analysts Journal, 67-69. French, Kenneth R., 1980, Stock returns and the weekend effect, Journal of Financial Economics 8, 55-70. Gibbons, Michael R. and Patrick Hess, 1981, Day of the week effects and asset returns, Journal of Business 54, 579-596. Harris, Lawrence, 1986, A transaction data study of weekly and intradaily patterns in stock returns, Journal of Financial Economics 16, 99-117. Kalay, Avner and Uri Loewenstein, 1985, Predictable events and excess returns: The case of dividend announcements, Journal of Financial Economics 14, 421-449. Keim, Donald B. and Robert F. Stambaugh, 1984, A further investigation of the weekend effect in stock returns, Journal of Finance 39, 819-835. Kross, William and Douglas A. Schroeder, 1984, An empirical investigation of the effect of quarterly earnings announcement timing on stock returns, Journal of Accounting Research 22. 153-176. Kruskal, WiBiarn H. and W. Allen Wallis, 1952, Use of ranks in one-criterion variance analysis, Journal of the American Statistical Association 47, 583-621. Lakonishok, Josef and Maurice Levi, 1982, Weekend effects in stock returns: A note, Journal of Finance 37, 883-889. Lawrence, Edward C., 1983, Reporting delays for failed firms, Journal of Accounting Research 21, 606-610. Patell, James M. and Mark A. Wolfson, 1982, Good news, bad news, and the intraday timing of corporate disclosures, Accounting Review 57, 509-527. Penman, Stephen H., 1984, Abnormal returns to investment strategies based on the timing of earnings reports, Journal of Accounting and Economics 6, 165-183. “Rozeff and Kinney (1976) conjecture informational reasons for observed January effects in stock returns. Conjectures about informational explanations for January effects are far less plausible than those here, at least with respect to earnings information. Earnings reports in the first calendar quarter are largely annual reports, which are published with greater delay than interim reports (as observed in fig. 2). Very few reports appear in the early part of January, when the effect is observed.

J.F.E.-

B

228

S. H. Penman,

Earnmgs

news and seasonalirres

in stock returns

Rogalski, Richard J., 1984, New tindings regarding day of the week returns over trading and non-trading periods: A note, Journal of Finance 39. 1603-1614. Roll, Richard. 1983, Vas ist das? The turn of the year effect and the return premia of small firms, Journal of Portfolio Management 9, 18-28. Rozeff, Michael S. and William R. Kinney, Jr., 1976, CapitaJ market seasonality: The case of stock returns, Journal of Financial Economics 3, 379-402. Smirlock. Michael and Laura Starks, 1986. Day-of-the-a-eek and intraday effects in stock returns. Journal of Financial Economics 17, 197-210. Vinod, Hrishikesh D., 1976, The effects of ARMA errors on the significance tests for regression coefficients, Journal of the American Statistical Association 71, 929-933. Whittred, Greg and Ian Zimmer. 1984, Timeliness of financial reporting and financial distress, Accounting Review 59, 287-295.