Timing Effect

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The Timing of Earnings Announcements and

Market Response to Earnings News

QI SUN

This Version: October 2006

College of Business Administration, California State University San Marcos, SUN:[email protected],(760) 750-4282;


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The Timing of Earnings Announcements and

Market Response to Earnings News

Abstract

In this paper, we investigate whether the timing of earnings announcements in the earnings

seasons affects market response to earnings surprises. We document that market response

is more favorable when news announcements are made early in the earnings season (timing

effect). Price reactions on earnings announcement dates and price movements in the following

60 trading days are significantly stronger (weaker) for positive (negative) earnings surprises

announced at the beginning of the earnings season. We explore two sources of the timing

effect: information transfer and firms strategic timing of news announcements. The timing

effect associated with positive earnings surprises is consistent with information transfer in

that late good news announcements are accompanied by significant pre-announcement price

increase. The timing effect associated with negative earnings surprises is mainly driven by

firms strategic delay of bad news announcements since the timing effect does not exist among

bad news announcements that are made earlier than expected.

JEL: Discretionary Disclosure, Information Transfer, Price Discovery, Strategic Timing of News

Announcements


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I. Introduction

To assist market efficiency, the Securities and Exchange Commission (SEC) requires that com-

panies file their quarterly earnings reports in a timely manner following the end of fiscal

quarter.1 As a result, earnings announcements are clustered in time. On one hand, since earn-

ings announcements are mandatory and their report dates are predictable to a large extent,

market response to earnings surprises should be independent of when the news announcement

is made in the earnings season.2 On the other hand, the unique information environment of

the earnings season implies that market reactions to earnings surprises are correlated with the

timing of news announcement. As the earnings season proceeds, market participants infor-

mation sets grow and information searching activity intensifies. Both of them complicate the

price discovery process at the beginning and the end of the earnings season. In this paper, we

investigate whether the relative timing of earnings announcements impacts market response to

earnings surprises and we explore what is the source of the impact.

Using a sample of quarterly earnings announcements between year 1985 and 2003, we docu-

ment that the timing of earnings announcements affects market responses to earnings surprises.

Announcements made early in the earnings season receive more favorable feedback than late

announcements.3 To illustrate, stocks with extreme positive earnings surprises released in

the first 10 days of the earnings season gain 3.10% over a three-day window surrounding the

earnings announcement date. The price of these stocks increases by additional 2.90% in the

1For example, companies are required to file their quarterly earnings report within 45 days after the fiscal

quarter end. Effective on Nov.15, 2002, the filing deadline for filing quarterly earnings reports are being reducedfrom 45 days to 35 days over three years, whereas the deadline for filing annual reports are being reducedgradually from 90 days to 60 days.

2Consistent with conventional wisdom, we define earnings season as the window of one month after fiscalquarter end in which a majority of corporate earnings are released to public.

3In this paper, we define early and late announcement based on the chronicle order of earnings disclosures inearnings season. In comparison, we define advanced and delayed announcement based on the reporting patternof individual firms. An announcement is advanced (delayed) if its report date is earlier (later) than the expecteddate. See subsection B in section V for more details.

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following 60 trading days. In total, these stocks appreciate by 6%. In comparison, stocks with

extreme positive earnings surprises disclosed in the last ten days of the earnings season appre-

ciate only 2.87% (1.93% on earnings announcement date and 0.94% in the following 60 trading

days). For negative earnings surprise announcements, the market response is less negative if

the news announcement is released at the beginning of the earnings season. For example, the

average value depreciation is -3.55% (-2.44% on announcement date and -1.11% in the follow-

ing quarter) for announcements made in the first ten days of the earnings season. The value

depreciation is much stronger for announcements released in the last ten days of the earnings

season: a total price decline of -6.50% with -2.38% on earnings announcement date and -4.12%

in the following quarter.

We further explore two possible sources of the timing effect: information transfer and

firms strategic timing of news announcements. Information transfer occurs when market

participants update their beliefs of a firms profitability by extrapolating other firms earnings

reports. Earnings information transfer occurs within the same industry (Foster (1981), Han

and Wild (1990)) and across industries since a firms earnings announcement not only contains

information about its own cash flows but also contains implications for the profitability of

its competitors, suppliers and clients. In the earnings season, massive corporate earnings

reports stimulate investors information searching activity, which in turn stimulates information

transfer. Consequently, the information content of non-released earnings reports has been

supplied by other channels before the public announcement is made. Because of information

transfer, the market response to late news announcements is weaker than for it is for early

announcements.

The timing effect could also be attributed to firms strategic timing of their bad news

announcements. Studies (Kross (1981), Givoly and Palmon (1982), Chambers and Penman

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(1984), Kross and Schroeder (1984), and Begley and Fischer (1998)) have shown that compa-

nies strategically time their public news announcements to optimize the post-announcement

stock price. These studies provide empirical evidence that good news is announced relatively

earlier than bad news. Delayed announcements more often contain bad news. Consequently,

market participants react less favorably to delayed announcements. Given the fact that pos-

itive (negative) earnings surprises concentrate at the beginning (end) of earnings season and

early (late) announcements tend to be advanced (delayed) from their typical announcement

dates, the timing effect could be driven by the penalty on delayed bad news announcements.

If the timing effect is due to firms strategic timing of bad news announcements, the timing

effect should be the most pronounced among delayed bad news announcements.

Our tests show that the timing effect associated with positive earnings surprise announce-

ments is consistent with information transfer. Price reaction and price drift are weaker toward

the end of the earnings season. The average price reaction to positive earnings surprises an-

nounced at the beginning of the earnings season is 3.10%, which is significantly stronger than

the price reaction of 1.93% associated with announcements made at the end of the earnings

season. Information transfer is reflected by the significant abnormal price increase before the

public announcement. The size-adjusted cumulative abnormal return of late announcing firms

is 0.52% in the first 10 days and 1.22% in the middle 10 days of the earnings season. The sig-

nificant pre-announcement price increase suggests that part of the positive earnings news has

been extrapolated from other information channels and thus been incorporated into the stock

price. Consequently, the price drift after the earnings announcement is much weaker if the

announcement is made at the end of the earnings season. The pre-announcement t price ad-

justment also applies to negative news announcements. For stocks with negative news released

in the last ten days of the earnings season, the average price decline is a significant -1.30% over

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the first 20 days of the earnings season. However, these late bad news announcements are also

accompanied by strong negative price drifts after the announcement date, indicating that the

timing effect is not purely driven by information transfer.

Our further investigation indicates that firms strategic delay of bad news announcement

significantly contributes to the timing effect associated with negative earnings surprise an-

nouncements. First, we study the reporting pattern of individual firms and find that only 62

percent of bad news announcements are released on time. While firms show little intention

to advance or delay good news announcements, they tend to delay bad news announcements.

Twenty-five percent negative earnings surprises are announced after the expected announce-

ment date, whereas only twelve percent are disclosed earlier than expected. The proportion of

delayed announcements increases from 7.6% at the beginning of the earnings season to 37.21%

toward the end of the earnings season. As expected, the timing effect is the most pronounced

among delayed bad news announcements. Both price reaction (-2.96%) and price drift (-5.16%)

are significantly more negative than for advanced or on-time bad news announcements. In ad-

dition, the timing effect does not exist among advanced bad news announcements. The price

reaction and price drift of these stocks do not vary with the timing of the news announcements.

Moreover, these stocks do not significantly underperform their size decile benchmarks in the

following quarter.

Our paper is the first to link the market response to earnings news with the relative tim-

ing of earnings announcements in the earnings season. It provides evidence that helps better

understand how news about fundamentals is incorporated into stock prices and how clus-

tered corporate events affect the price formation process. For example, the divergent post-

announcement price movements indicate that the post-announcement price formation process

could be motivated by other events other than solely by a firms own earnings news. Therefore,

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post-earnings announcement drift may reflect price adjustment to other firms earnings news,

which implies that the widely accepted underreaction explanation is overly simplistic.

Our results have applicability to policy makers and market participants. Policy makers are

promoting timely disclosure for market efficiency purposes since there could be incentives and

frictions in the reporting process that distort the price discovery process. Evidence documented

in this paper justifies policy makers promotion of timely information disclosure. Market

participants are interested in our results because the relationship between the timing of news

announcement and the subsequent price movement will affect their information gathering and

trading activities.

The remainder of the paper is organized as follows. Section II describes our research sample

and variable measurements. Section III presents the evidence on the timing effect. Discussions

on the sources of the timing effect are present in section IV and V. Conclusions are drawn in

section VI.

II. Sample Description and Variable Measurement

Our research sample includes stocks listed on the New York Stock Exchange (NYSE), American

Stock Exchange (AMEX), and National Association of Securities Dealers Automated Quotation

system (NASDAQ). We exclude real estate investment trusts (REITs), American Depository

Receipts (ADRs), and closed-end mutual funds from our sample. To mitigate microstructure

effects, we also exclude stocks priced below $5.

We obtain actual earnings and financial analyst earnings forecasts from the Institutional

Brokerage Estimate System (I/B/E/S) raw unadjusted earnings dataset (provided upon re-

quest). The standard I/B/E/S dataset reports the actual and forecasted earnings-per-share

(EPS) that are adjusted for stock splits (i.e. EPS is based on the number of shares outstand-

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ing as of today along with a split factor). After making retroactive and cumulative stock split

adjustments, estimated and actual EPS are rounded to the nearest cent. The problem with

this practice is that comparisons of actual with forecast EPS for firms that have executed

stock splits are less precise. Consequently, there is a disproportionate number of firms that

exactly meet expectations when in fact they miss or beat expectations.4 Had we utilized the

commonly used I/B/E/S standard files, we would have missed a lot of earnings surprises.

We obtain data on stock returns and other financial information from CRSP/COMPUSTAT

merged quarterly files and the prices-dividends-earnings files. To ensure that fiscal quarters

are aligned, our sample is restricted to firms with March, June, September and December fiscal

quarter end. By doing so, we drop roughly 15% observations. The sample period runs from

1985 through 2003 because of the constraints of I/B/E/S data.5

We measure earnings surprise by analyst forecast error (AFE). AFE is defined as the dif-

ference between the actual EPS for quarter q and the most recent mean consensus analyst

forecast for quarter q. The difference is scaled by the book value per share at the end of

quarter q-1.6

We use analyst consensus forecasts as a benchmark because financial analysts

are believed to be the most important information intermediaries between firms and investors.

They routinely collect and process information from various channels and disseminate informa-

tion to the market. Academic studies in accounting and finance have increasingly used analyst

forecast as a proxy for market expectation. Empirical studies have shown that financial ana-

lysts help interpret new information. Stock prices react more strongly to earnings that are not

4

For example, Dell delivered an earnings per share (EPS) of $1.36 in 1994, which beat analysts consensusforecast $0.96 by 40 cents. According to the standard-issue I/B/E/S, however, Dell met analysts expectationswith an EPS of $0.02. The much smaller EPS is due to an adjustment factor of 64 for Dell in 1994 in theAdjustment File of I/B/E/S.

5I/B/E/S starts reporting analyst quarterly earnings forecast in 1984. As a result, few observations areavailable for 1984.

6Results using median analyst forecast are not tabulated but have similar pattern. In fact, the median andmean forecasts are similar, with a correlation coefficient of 0.998. Untabulted results with lagged price as thescalar are similar to those reported.

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predicted by financial analysts. In addition, AFE does not require a particular model design

for the earnings generating process.

To ensure the robustness of our results, we use another earnings surprise measure that is

derived from the individual financial analyst earnings forecast. The consensus earnings forecast

is computed every month. As a result, the monthly consensus may not reflect the most recent

information. Furthermore, if some analysts do not update their forecasts frequently, their

forecasts become stale but are still used in the computation of consensus forecasts. Using the

most recent individual analyst forecast circumvents the above two problems. The earnings

surprise measure based on individual analyst forecast is calculated similarly to the one based

on the consensus forecast.

The market response to an earnings surprise is measured by price reaction (CAR3) and

price drift. Price reaction reflects the immediate price change surrounding the earnings an-

nouncement date. We estimate CAR3 by the sum of daily abnormal returns over the window of

[-1, 0, 1], where 0 represents the earnings announcement date from I/B/E/S. Daily abnormal

return for firm j on day i is calculated as the difference between the raw daily return of firm

j and the value weighted average returns for NYSE, AMEX and NASDAQ firms in the same

size decile based on NYSE breakpoint at the end of the previous year. Including day -1 and 1

is motivated by fact that COMPUSTAT receives reported earnings data from various sources,

including newswire, newspapers, and brokers. Since newswire services run beyond the close

of trading, announcements appearing during that time interval are dated to the subsequent

trading day. As a result, information may have been impounded into security prices on day -1

or 0 for announcements whose announcement date is from the news media, and on day 0 or 1

when announcement date is from newswire services.

Price drift reflects the price movement in the following quarter after the earnings announce-

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ment date. Following existing studies, we estimate price drift over a window of sixty trading

days. Specifically, we calculate the holding period return (HPR) of a stock over the interval

of [2, 61]. We also calculate the HPR of its size benchmark portfolio over the same holding

period. Price drift is defined as the difference between a stocks HPR and the HPR of its re-

spective size benchmark portfolio. When calculating the sixty trading day cumulative return,

we make sure that we do not include stock returns during the next earnings announcement

period. For a small number of observations, the next earnings announcement date falls into

the sixty trading day period, we stop the calculation of price drift one day before the next

earnings announcement date.

III. Timing of Earnings Announcements and Market Responses

to Earnings Surprises

A. Distribution of Quarterly Earnings Announcements

The SEC explicitly requires that quarterly earnings reports be filed within 45 days following

the end of fiscal quarter. As a result, earnings announcements are clustered in time. Table I

details the distribution of quarterly earnings announcements between 1985 and 2003.

The distribution pattern based on overall quarterly earnings announcements shows that

only 8.13 percent of announcements are made in the first 15 calendar days after the fiscal

quarter end. Within 45 calendar days after the fiscal quarter end, 90.02 percent of firms

announce their quarterly earnings performance. On average, 81.90 percent of announcements

are made in the earnings season, the time period in which a majority of corporate earnings

are released to the public.7 In addition, half of the announcements made in the earnings

7In this paper, we define earnings season as a window starting from day16 of the first calendar month afterfiscal quarter end and ending on day15 of the second calendar month after fiscal quarter end. Our definition isbased on the conventional wisdom and the distribution of earnings announcements in 5-day intervals after fiscalquarter end (untabluated).

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season concentrate in the first ten days. Only 9.98 percent of earnings announcements are

made beyond the earnings season (among which only 3.85% are made beyond 2 months after

the fiscal quarter end).

Table I also presents the distribution pattern of earnings announcements with extreme earn-

ings surprises. At the end of calendar quarter q, we rank all quarterly earnings announcements

released in quarter q into quintiles based on the magnitude of earnings surprises. Extreme

positive (negative) earnings surprises are those ranked top (bottom) 20 percent. Despite the

extreme magnitude of earnings surprises, a majority of those announcements are still made

in the earnings season. The proportion of in-season announcements is 75.86% for extreme

negative earnings surprises and 82.67% for extreme positive earnings surprises. However, the

proportion of negative news reports released after the earnings season significantly outnumbers

that of positive news reports. 19.31 percent extreme negative earnings reports are disclosed

after the earnings season, while it is only 10.36% for reports with extreme positive earnings

surprises.

Within the earnings season, there is no apparent concentration of negative news announce-

ments in a particular time period. Bad news reports are evenly distributed over the earnings

announcement month with 27.76% in the first 10 days and 21.08% in the last 10 days. In com-

parison, extreme positive news announcements tend to cluster at the beginning of the earnings

season. 40.33% of good news reports are released in the first 10 days, compared with only

14.41% in the last ten days.

B. Evidence on the Timing Effect

In this section, we investigate whether the timing of earnings announcements affects the market

response to earnings surprises. Market response is measured by the immediate price reaction

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surrounding the earnings announcement date and price drift in the following quarter. Table

II summarizes the evidence based on earning surprise quintiles. The overall impression is that

market reacts more favorably to the news released early in the earnings season.

For positive earnings surprise announcements, the magnitude of price reaction and price

drift monotonically decreases as the earnings season proceeds. To illustrate, stocks with ex-

treme positive earnings surprises on average gain 3.99 percent over three trading days sur-

rounding the earnings announcement date if the news is released before the earnings season

starts. The value appreciation continues in the following quarter by additional 4.13 percent.

Meanwhile, market reactions to extreme positive earnings surprises disclosed beyond the earn-

ings season are lack of luster. The average immediate price reaction is 1.91 percent, only a half

of what can be achieved if news is announced early in the earnings season. Announcing-late

stocks also outperform their size benchmark portfolios by a much smaller margin in the fol-

lowing quarter. The 60-day size-adjusted cumulative abnormal return is only 1.34% compared

with 3.99% for early announcements. The timing effect is robust throughout the earnings

season. Announcements released in the first 10 days of the earnings season are responded by

3.10% price increase surrounding the earnings announcement date and 2.90% in the following

quarter. Both price reaction and price drift are significantly higher than for announcements

made in the last 10 days of earnings season (average price reaction of 1.93% and price drift of

0.94%).

For negative earnings surprises, price reaction and price drift are less negative if announce-

ments are made early in the earnings season. Firms with bad news reported before earnings

season starts get the least penalty. Average price decrease on announcement date is -1.76 per-

cent, the weakest compared with price reaction to bad news announced in the earnings season.

Moreover, these stocks do not underperform their size companion portfolios in the following

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quarter. The cumulative abnormal return over sixty trading days is 0.39 percent, indicating

there is no further price decline after the earnings announcement date. In contrast, market re-

acts strongly to bad news disclosed late in the earnings season. For example, extreme negative

surprises released in the last 10 days of the earnings season are accompanied by a total value

deprecation of 6.40% (-2.38% surrounding the announcement date and -4.12% in the following

quarter), which is more than twice the value depreciation (-3.55%) for early announcements.

The differential market response to news of the same magnitude but occurs at different

time in the earnings season implies that the timing of announcements affects price discovery

process. In the following sections, we explore two sources of the timing effect: information

transfer and firms strategic timing of news announcements.

IV. Information Transfer and the Timing Effect

Studies such as Foster (1981), Han and Wild (1990) have shown that earnings information

transfers within the same industry, i.e. stock prices of competing firms react to earnings an-

nouncements made by other firms in the same industry. The price comovement arises because

firms in the same industry have similar cash flow characteristics. A firms earnings announce-

ment not only discloses firm specific cash flow information, but also contains information about

the common elements that affect the profitability of all firms in the same industry. Earnings

information also transfers across industries. Because the earnings reports of a firms suppli-

ers and clients also shed light on the business growth potentials of a firm. These alternative

information channels help alter investors beliefs of a firms profitability and induces price

changes.

In the earnings season, massive corporate earnings reports not only broaden information

transfer channels, but also stimulate market participants information searching activities. At

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the beginning of the earnings season, the lack of massive earnings news to set a distinctive

tone to trade in equity market causes investors to wait and hold their interests. As more

earnings news hits the market, the buying and selling interests grow. As investors and financial

analysts intensify their information searching and processing, the surprise component in non-

released earnings reports becomes smaller. Consequently, information transfer causes pre-

announcement price adjustment, weaker price reaction and weaker price drift for earnings

surprises released late in the earnings season.

To test the contribution of information transfer to the timing effect, we track stocks abnor-

mal price changes in the earnings season. We divide the earnings season into three subperiods

BGN, Middle, and END, with BGN and END refer to the first and last ten calen-

dar days of the earnings season. We calculate the cumulative abnormal returns over each time

interval as the difference between the holding period return (HPR) of an individual stock and

the HPR of its size decile benchmark portfolio.8 Table III summarizes the results based on

extreme earnings surprise announcements made in the first and last ten days of the earnings

season.

The timing effect associated with positive earnings surprise announcements is consistent

with information transfer. The price reaction to news released late in the earnings season is

1.17% smaller than for early announcements. However, before the public disclosure, the size-

adjusted price of late announcing firms has gone up by 1.68% (with 0.52% in the first 10 days

and 1.22% in the following 10 days). The significant pre-announcement price increase indicates

that part of the earnings surprise has been anticipated, and justifies the much smaller price

reaction and price drift for late announcements.

However, the timing effect associated with negative earnings surprise announcements can-

8We obtain the value-weighted daily returns of size deciles from Professor Kenneth R. Frenchs web site.

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not be attributed to information transfer. For bad news disclosed in the last ten days of the

earnings season, the pre-announcement price decline is -1.30% over the first 20 days of the

earnings season. Despite the significant pre-announcement price decline, the price reaction to

late announcements (-2.38%) is not significantly smaller than that for early announcements

(-2.44%). The insignificant difference between price reactions may be caused by the bad

news travels slowly phenomenon documented by Hong, Lim and Stein (2000). However, bad

news travels slowly cannot explain why late announcements are accompanied by a much

stronger negative price drift of -4.12%. The strong post-announcement price decline for news

announced late in earnings season indicates that the timing effect is not purely driven by

information transfer.

V. Strategic Timing of News Announcements and the Timing

Effect

Corporate managers have become increasingly aware of the potential impact that corporate

disclosure strategies can have on a firms value. An important element of a firms disclo-

sure strategy is the timing of its public news announcements. Through strategic timing, the

management hopes to optimize the post-announcement stock price.

Studies have shown that firms strategically choose the time of the day or the day of the

week to make news announcements. For example, Gennotte and Trueman (1996) demonstrate

that under reasonable conditions, market prices better reflect the valuation implications of an

earnings announcement when it is made during trading hours rather than after the market has

closed. They predict that the average price reaction to news made during trading hours will

be more positive than news disclosed after the market is closed. Their prediction is consistent

with the empirical evidence documented by Patell and Wolfson (1982), Damodaran (1989),

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and Francis, Pagach and Stephan (1992). At the intra-week level, Vigna and Pollet (2004)

show that firms tend to release bad news on Friday because investors are more distracted

from job-related tasks. The limited attention on Friday will mitigate market reaction to bad

news. Vigna and Pollet find that, despite the smaller market reaction due to distraction on

Friday, the post-Friday price drift is stronger than that for non-Friday announcement. Since

the total value depreciation is indifferent for Friday and non-Friday bad news announcements,

it indicates that the quality of decision-making is not affected by the timing of bad news

announcements.

Besides intra-day and intra-week strategic timing, firms also intentionally advance or delay

news announcements, depending on the nature of the news. Studies in 1980s (Kross (1981),

Givoly and Palmon (1982), Chambers and Penman (1984), and Kross and Schroeder (1984))

document that the announcement delay is negatively related to earnings surprises. Therefore,

delayed announcements are accompanied by more negative or less positive abnormal returns

on earnings announcement dates. These studies show that reward and penalty are robust

after controlling for the sign and magnitude of earnings news. Begley and Fischer (1998)

confirm that the good news early, bad news late phenomenon persists in the new litigation

environment in 1990s, which would discourages the delay of bad news announcements.

There are several reasons why the management have incentives to delay bad news announce-

ments. First, they may be able to complete contract negotiations or security issuance at more

favorable terms without the bad news. Second, the management need extra time to resolve

disagreement with auditors. Third, the management needs more time to prepare response to

criticism or come out with a recovery plan that tones down the negative impact on firms value.

Fourth, longer reporting lag gives the management flexibility to decide whether to reverse the

poor earnings performance through complicated accounting practice such as accruals manage-

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ment. Last, announcing late in the earnings season allows investors to anticipate the bad news

so that the impact on the post-announcement stock price is mitigated. It is not common for

firms to advance good news announcements. However, firms sometimes advance their good

news announcements before the industry leader weighs in with strong earnings performance

that steals their own thunder.

Strategic timing implies that market response to delayed earnings announcements is less

favorable than for advanced or on-time announcements. If announcements released at the end

of the earnings season are dominated by delayed ones, the timing effect may be attributed

to firms strategic delay of bad news. In the following subsections, we first investigate the

reporting pattern of individual firms. We then check whether the timing effect is the strongest

among delayed announcements.

A. Reporting Pattern of Individual Firms

The distribution of quarterly earnings announcements in Table I indicates that positive earnings

reports concentrate at the beginning of earnings season while negative earnings reports cluster

at the end of the earnings season. Does the concentration signal firms strategic timing?

We examine whether the reporting pattern of individual firms is stable over time. Empirical

analysis is done on firms with records of quarterly earnings performance for at least three

consecutive fiscal years. The evidence is presented in Table IV.

We calculate the reporting lag (RepLag) for each firm-quarter observation to see how much

time it takes a firm to release its quarterly earnings report. RepLag is defined as number of

days between the fiscal quarter end and the day prior to the earnings announcement date.

The cross-sectional mean of the within-firm measures indicate that firms on average spend one

month (26-32 days) on earnings report preparation. The report for the 4th fiscal quarter takes

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a slightly longer time since firms tend to release the annual result together with the 4th fiscal

quarter result. The mean within-firm standard deviation of reporting lag is about 5 days,

which is relatively small considering that weekends and holidays will naturally introduce some

variation.

The stability of a firms reporting pattern is reflected in the announcement delay (DEL).

In the same manner as in earlier studies (e.g. Begley and Fischer (1998)), we define DEL for

firm i in quarter q and year t as

DELi,q,t = RepLagi,q,t RepLagi,q,t1

The mean and median DEL are negative but not significantly different from zero, representing

little time trend of reporting lags for individual firms. The mean absolute deviations from

the previous year (Mean |DEL|) are of the same magnitude (4-5 days) as the mean standard

deviations from the mean reporting lag. It shows that the within-firm variation of reporting

lags over time is mainly due to swings in successive reports for the same fiscal quarter. In a

nutshell, evidence in Table IV suggests a relatively regular and predictable reporting behavior

by individual companies. However, firms do have some flexibility on when to release their

quarterly earnings reports.

Based on the reporting pattern of individual firms, we define that an earnings announcement

is on time if its DEL satisfies -5DEL5. An announcement is defined as being advanced

(delayed) if its DEL is less (more) than 5.

B. Strategic Timing of News Announcements and the Timing Effect

In this subsection, we investigate whether the timing effect is a surrogate of reward on advanced

announcements or penalty on delayed announcements. Our analysis focuses on announcements

with extreme earnings surprises.

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Table V highlights the average announcement delay (DEL) of announcements made before

the earnings season starts, in the earnings season, and after the earnings season. Announce-

ments released at the beginning of the earning season on average are made earlier than the

same quarter last year. These early announcements on average are advanced by 2 to 4 days

relative to the same quarter last year. Announcements made in the last ten days of the earn-

ings season are on average delayed. The delay is more severe for bad news announcements.

For instance, bad news announcements made in the last ten days of the earnings season are

delayed by 3 days, compared with less than 1 day for good news announcements.

Table V also presents the distribution and proportion of advanced and delayed news an-

nouncements. There is little evidence that firms intentionally advance good news announce-

ments. For extreme positive earnings surprises, 70.14% are disclosed on time. The proportion

of advanced announcements, although slightly higher, is not significantly different from that

for delayed announcements (16.65% versus 13.21%). Advanced good news announcements are

spread evenly throughout the earnings season. Among the good news announcements made

in the first ten days of the earnings season, 15.64% are advanced, which is not significantly

higher than the proportion of 14.40% for advanced announcements made in the last ten days

of the earnings season.

However, firms show a strong intention to postpone their bad news announcements. The

proportion of delayed announcements is more than doubled compared with advanced announce-

ments (25.25% versus 12.33%). Delayed announcements are clustered in the last ten days of the

earnings season and beyond the earnings season. For example, 37.21% of the announcements

made in the last ten days of the earnings season are delayed, which is almost 5 times of the

proportion for delayed announcements made early in earnings season. Despite the tendency

of delaying bad news announcements, 62.43% of bad news announcements are still on time,

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which confirms the relatively stable reporting pattern by individual firms.

Table VII reports evidence on the contribution of strategic delay of bad news announce-

ments to the timing effect associated with extreme negative earnings surprise announcements.

Consistent with the prediction of strategic timing, the timing effect is the most pronounced

among delayed bad news announcements. The price reaction to delayed announcements made

at the end of the earnings season (-2.96%) is significantly more negative than for advanced

(-1.60%) or on-time announcements (-2.18%) released in the same time period. Delayed an-

nouncements are also accompanied by the most negative price drift (-5.16%), which is 4 times

of the price drift for advanced announcements and doubles the one for on-time announcements.

The timing effect does not exist in advanced bad news announcements in that price reaction

does not vary with the timing of advanced announcements. Moreover, firms announcing bad

news earlier than expected do not significantly underperform their size benchmark portfolios

after earnings announcement date. In summary, the timing effect associated with extreme

negative earnings announcements is mainly driven by firms strategic delay of their bad news

announcements. The contribution of strategic delay of bad news announcements is robust to

the definition of advanced or delayed announcements.9

VI. Conclusions

In this paper, we study the relationship between the timing of earnings announcements and

the market response to earnings surprises on earnings announcement dates and in the following

60 trading days. We find that announcements made at the beginning of the earnings season

receive more favorable feedback (timing effect). Positive earnings surprises reported early in

the earnings season are accompanied by larger price increases on and after earnings announce-

9We run robustness checks by defining on time as -3DEL3, or -1DEL1. Results are similar to thereported ones.

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ment dates than late announcements. Early announcements of negative earnings surprises are

associated with the smallest value depreciations.

We explore the contribution of information transfer and firms strategic timing of news

announcements to the timing effect. The timing effect associated with positive earnings an-

nouncements is consistent with information transfer. The price of late announcing firms has

significantly increased before the public news announcement. The pre-announcement price

increase indicates that the information content of late announcements has been extrapolated

from other information channels, such as earnings reports of firms in related industries and

financial analysts research reports. As a result, the price reaction and price drift are both

weaker for late announcements.

The timing effect associated with extreme negative earnings announcements is consistent

with firms strategic delay of bad news announcements. We study the distribution and pro-

portion of advanced and delayed announcements in the earnings season. We find that firms

have little intention to advance news announcements. Advanced news announcements are dis-

tributed evenly in earnings season. However, firms tend to delay the news announcements that

deliver bad news to the market. The proportion of delayed announcements increases toward the

end of the earnings season. As predicted, the timing effect does not exist among advanced bad

news announcements. And the timing effect is the strongest among delayed announcements.

In this paper, we have identified two sources of the timing effect. However, we cannot rule

out the possibility that other factors also contribute to the timing effect. For instance, the

time a firm spends on its earnings report preparation determines the timing of announcement

in the earnings season. Therefore, the timing effect could be a proxy for firm characteristics

that affects a firms report preparation. We also cannot rule out the possibility that the timing

effect is due to investors irrationality. Investors may take announcing late in the earnings

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season as a signal of poor earnings quality because it allows management to evaluate whether

to do earnings management and how much the earnings management should be. The timing

effect may reflect the cost of that flexibility. The impact of investors irrationality and firm

characteristics such as investor base, litigation risk, proprietary cost, accounting complexity

and the nature of earnings news deserve further explorations.

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TableI:TheDistributionofQuarterlyEarningsAn

nouncements

Thistablereportsth

edistributionofquarterlyearnings

announcementsbetweenyear1985

and2003.Thesampleofobservatio

nsisrestricted

tofirmswithMarch,June,SeptemberandDecemberfi

scalquarterends.Announcement

dateisobtainedfrom

theInstitutionalBrokerage

EstimateSystem

(I/

B/E/S).Earningsseasonisdefined

asamonthstartingfrom

calendar

day16ofthemonthafterthefiscalquarterend.

Totalnumberofqua

rterlyearningsannouncementsmadeineachcalendaryear,thepropo

rtionofannouncementsmadebefo

re,duringand

afterearningsseason

(Before,EarningsSeasonand

After)arereported.Earningsseasonisfurtherdividedinto3intervals.BGN

andMiddlecoverthefirstandsecond10calendarday

softheearningsseason.ENDco

verstherestoftheearningsseason.Theevidence

fortheextremepositiveandnegativeearningssurprises

isalsoreported.

All

EarningsAnnouncements

ExtremeNegativeEarningsSurprises

ExtremePositiveEarningsSurprises

(Nobs=182,412)

(Nobs=35,846)

(Nobs=36,137)

EarningsSeason

EarningsSeason

EarningsS

eason

Year

Before

BGN

Middle

END

After

Before

BGN

Middle

END

After

Before

BGN

Middle

END

After

1985

7.59

43.29

23.83

14.19

11.11

4.78

35.17

23.28

17.03

19.73

4.87

40.56

23.26

15.35

15.96

1986

8.25

41.22

25.42

13.50

11.61

4.84

26.10

26.66

18.45

23.96

6.01

42.09

24.94

14.25

12.69

1987

9.63

34.55

30.81

12.67

12.33

4.35

21.26

30.97

18.62

24.80

8.12

36.67

31.26

12.53

11.42

1988

6.92

31.83

37.02

11.31

12.92

4.05

19.76

33.99

17.49

24.70

6.26

31.18

37.15

11.93

13.49

1989

5.94

37.55

31.16

13.51

11.84

3.25

23.25

29.91

18.97

24.62

5.86

36.87

31.65

12.61

13.01

1990

6.09

44.57

24.52

14.16

10.66

3.91

28.56

25.31

21.16

21.07

5.16

43.78

25.19

15.40

10.47

1991

9.30

40.01

26.48

12.76

11.46

6.16

27.72

26.37

18.78

20.96

8.17

38.96

26.93

12.78

13.16

1992

9.40

40.35

27.36

12.57

10.32

6.83

29.72

28.43

17.21

17.79

8.20

38.66

26.78

14.48

11.89

1993

8.00

35.54

33.22

11.48

11.76

5.59

24.00

33.88

18.01

18.52

7.19

35.95

32.14

11.29

13.43

1994

9.28

38.22

29.64

13.15

9.71

5.32

23.95

30.07

22.02

18.64

9.12

40.45

27.79

13.09

9.55

1995

6.71

44.80

24.99

14.35

9.15

4.33

32.14

24.46

21.24

17.84

6.54

44.99

24.63

15.69

8.15

1996

9.02

49.91

18.44

14.85

7.78

6.08

37.39

19.31

22.21

15.02

7.29

51.01

18.97

14.93

7.80

1997

11.55

41.68

23.82

13.82

9.14

6.47

29.79

24.11

21.66

17.97

9.75

40.99

24.92

14.57

9.78

1998

11.60

34.10

30.46

11.96

11.89

8.15

22.01

27.93

19.26

22.64

11.07

35.50

30.67

11.24

11.51

1999

10.48

32.42

34.56

11.20

11.34

5.51

18.11

32.94

19.98

23.47

10.59

33.32

33.68

11.31

11.10

2000

6.13

41.27

28.97

13.93

9.71

2.63

28.16

26.94

21.98

20.28

4.93

40.42

31.46

14.84

8.35

2001

4.01

47.71

23.58

16.36

8.33

2.39

32.93

22.49

24.84

17.35

2.24

41.40

27.37

19.44

9.54

2002

5.60

49.07

21.55

16.40

7.38

2.63

34.69

22.16

26.41

14.10

3.68

46.41

23.44

18.21

8.26

2003

6.53

41.10

29.19

15.33

7.85

3.12

26.61

30.64

24.54

15.09

3.70

40.16

30.42

16.99

8.73

Average

8.13

40.86

27.38

13.66

9.98

4.83

27.76

27.02

21.08

19.31

6.97

40.33

27.93

14.41

10.36

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Table II: Price Reactions and Price Drifts associated withEarnings Surprises Released at Different Time in Earnings Season

This table presents evidence of the impact of announcement timing on the price discover process.At the end of each calendar quarter, earnings surprises (measured by analyst forecast error (AFE))released in the quarter are ranked into quintile. Extreme positive (negative) earnings surprises arethose ranked top (bottom) 20 percent. Price reaction is measured by the cumulative abnormal returnover a window of three trading days [-1, 1]. Price drift is measured by the difference between theholding period return (HPR) of individual stock and the HPR of its size decile benchmark portfolioover a window of 60 trading days [2, 61], where 0 is the earnings announcement date from I/B/E/S.

Panel A Price Reactions

Earnings Season

Before BGN Middle END After BGN-END

Extreme Negative Earnings -1.76 -2.44 -2.51 -2.38 -1.87 -0.062 -0.37 -0.93 -0.79 -1.05 -0.53 0.123 0.55 0.16 0.08 0.26 -0.02 -0.104 1.75 1.10 1.29 1.18 1.10 -0.09

Extreme Positive Earnings 3.99 3.10 2.66 1.93 1.91 1.17

Panel B Price Drifts

Earnings Season

Before BGN Middle END After BGN-END

Extreme Negative Earnings 0.39 -1.11 -2.58 -4.12 -2.18 3.01

2 -0.43 -0.94 -1.97 -1.80 0.51 0.86

3 0.30 0.53 -1.07 -1.05 -0.32 1.58

4 0.66 0.77 0.24 0.88 2.06 -0.10Extreme Positive Earnings 4.13 2.90 1.65 0.94 1.34 1.96

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Table 2.2 (continued): Price Reactions and Price Drifts associated with Earnings SurprisesReleased at Different Time in Earnings Season

Panel C presents the number of earnings announcements released in earnings season, before and afterearnings season (Before/After). Earnings season is further divided into 3 intervals. BGN andMiddle refer to the first and second 10-day interval of earnings season. END covers the restdays of earnings season. Numbers in bold bracket are the proportion of total announcements madein these event windows.

Panel C Numbers and Proportions of Observations

Earnings Season

Before BGN Middle END After Total Obs

Extreme Negative Earnings 1,702 9,881 9,633 7,532 6,891 35,639[4.78] [27.73] [27.03] [21.13] [19.34] [100.00]

2 2,975 15,362 10,024 4,376 2,766 35,503[8.38] [43.27] [28.23] [12.33] [7.79] [100.00]

3 4,492 17,857 9,553 3,721 2,282 37,905[11.85] [47.11] [25.20] [9.82] [6.02] [100.00]

4 2,952 16,539 10,400 3,993 2,454 36,338[8.12] [45.51] [28.62] [10.99] [6.75] [100.00]

Extreme Positive Earnings 2,490 14,502 10,040 5,183 3,725 35,940[6.93] [40.35] [27.94] [14.42] [10.36] [100.00]

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Table III: Information Transfer and the Timing Effect

This table reports price reactions and price drifts associated with extreme earnings surprises an-nounced in the first and last ten calendar days of earnings season. Earnings season is divided intothree 10-day intervals (BGN, Middle, and END). The cumulative abnormal returns overeach 10-day interval are reported. Cumulative abnormal return (CumAbnRet) is calculated as

the difference between the holding period return (HPR) of individual stock and the HPR of itsvalue-weighted size decile benchmark portfolio. Numbers with are significant at 5% significancelevel.

CumAbnRet (SizeAdj)

Extreme Surprises Timing Price Reaction Price Drift BGN Middle END

Positive BGN 3.10 2.90 3.72 0.77 0.56

END 1.93 0.94 0.52 1.22 2.00

BGN-END 1.17 1.96

Negative BGN -2.44 -1.11 -2.58 0.21 0.28

END -2.38 -4.12 -0.77 -0.43 -2.62

BGN-END -0.06 3.01

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Table IV: Quarterly Earnings Reporting Pattern of Individual Firms

This table reports evidence on the reporting pattern of individual firms. Reporting lag (RepLag) isdefined as the number of days between the fiscal quarter end and the day prior to the actual earningsannouncement date. Announcement Delay (DEL) is the difference between the RepLag for thecurrent quarter and the RepLag for the same quarter in the previous year. A negative (positive)DEL indicates that earnings report is advanced (delayed). Mean DEL (Median DEL) is thecross-sectional mean (median) of the within-firm measures. The quartile statistics of the absolutevalue of DEL is also reported.

Fiscal Mean Std. Range Mean Median Mean Q1 Median Q3Quarter RepLag RepLag RepLag DEL DEL |DEL| |DEL| |DEL| |DEL|

1 25.82 4.88 14.77 -0.23 0.00 4.41 2.45 3.56 5.332 26.43 4.74 14.22 -0.24 -0.06 4.14 2.28 3.33 5.003 25.64 4.91 14.81 -0.19 0.00 4.33 2.40 3.46 5.254 32.47 5.64 16.73 -0.56 -0.20 4.69 2.40 3.60 5.63

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Table V: The Timing of Earnings Announcement and Earnings Announcement Delay (DEL)

This table reports the announcement delay (DEL) for announcements with extreme earnings sur-prises. DEL is defined as RepLag(i,q,t) RepLag(i,q,t 1), where RepLag(i,q,t) is the numberof days between the fiscal quarter end and the day prior to the earnings announcement date. Earn-ings announcements are On Time if -5DEL5. Announcement are Delayed (Advanced) ifDEL>5 (DEL


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Table VI: Strategic Timing of Negative Earnings Surprise and Timing Effect

This table presents the impact of strategic timing of negative earnings surprise announcements onprice reactions (CAR3) and price drifts. Earnings announcements are On Time if -5DEL5. An-nouncement are Delayed (Advanced) if DEL>5 (if DEL

Documents

Timing Effect