The effect of the summer doldrums on earnings announcement returns and ERCs

THE FLORIDA STATE UNIVERSITY
COLLEGE OF BUSINESS

THE EFFECT OF THE SUMMER DOLDRUMS ON EARNINGS ANNOUNCEMENT RETURNS AND ERC’S

By
GREGORY B. GAYNOR

A Dissertation submitted to the
Department of Accounting
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy

Degree Awarded:
Fall Semester, 2011


UMI Number: 3502846

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Gregory B. Gaynor defended this dissertation on September 15, 2011.
The members of the supervisory committee were:

Richard Morton
Professor Directing Dissertation

Thomas Zuehlke
University Representative

Bruce Billings
Committee Member

Tim Zhang
Committee Member

The Graduate School has verified and approved the above-named committee
members, and certifies that the dissertation has been approved in accordance
with university requirements.

ii


ACKNOWLEDGEMENTS

I

would

like

to

acknowledge

Rick

Morton

(chair)

for

his

extensive

help

throughout this process, as well as my committee members for their helpful
comments and guidance.

All errors are my own.

iii

TABLE OF CONTENTS
LIST OF TABLES................................... Error! Bookmark not defined.
ABSTRACT................................................................... vi
1.

INTRODUCTION............................................................ 1

2.

BACKGROUND.............................................................. 6

3.

4.

5.

2.1

Noise vs. Sophisticated Traders...................................... 6

2.2

Investor Inattention and Delayed Price Response...................... 9

HYPOTHESIS DEVELOPMENT................................................. 12
3.1

Noise Traders’ Effect on Returns.................................... 12

3.2

Noise Traders’ Effect on the ERC.................................... 12

3.3

Pre-Announcement Period Returns..................................... 14

3.4

The Effect of the Online Period..................................... 14

3.5

Post-Earnings Announcement Drift.................................... 15

3.6

Trading Volume...................................................... 17

3.7

Investor Interest................................................... 17

RESEARCH DESIGN........................................................ 19
4.1

Sample.............................................................. 19

4.2

Measuring Return.................................................... 20

4.3

Measuring Earnings Surprise......................................... 21

4.4

Measuring Trading Volume............................................ 21

4.5

Models.............................................................. 21

4.5.1

Testing of H1-H3................................................ 21

4.5.2

Testing of H4-H6................................................ 23

4.5.3

Testing of H7................................................... 24

4.5.4

Testing of H8................................................... 25

4.5.5

Test of H9 & H10................................................ 25

RESULTS................................................................ 28
5.1

Descriptive Statistics.............................................. 28

5.2

Analysis............................................................ 28

5.2.1 Test of H1....................................................... 28
5.2.2

Test of H2...................................................... 29

5.2.3 Test of H3....................................................... 30
5.2.4 Test of H4 - H6.................................................. 31

6.

5.2.5

Test of H7...................................................... 33

5.2.6

Test of H8...................................................... 35

5.2.7

Test of H9-H10.................................................. 35

CONCLUSION............................................................. 61

REFERENCES................................................................. 64
BIOGRAPHICAL SKETCH........................................................ 67
iv


LIST OF TABLES
Table 1:

Sample and Descriptive Statistics ................................37

Table 2:

Descriptive Statistics of Summer vs. Non-Summer and Test of
Differences in Mean ..............................................38

Table 3:

Test of H2: Regression of Announcement-Period CAR ................41

Table 4:

Test of H3: Regression of Pre-Announcement-Period {-10,-1} CAR ...43

Table 5:

Test of H4: The Effect of the Online Period on Announcement-Period
{0, 2} CAR .......................................................45

Table 6:

Test of H5: The Effect of the Online Period on ERC’s .............47

Table 7:

Test of H6: The Effect of the Online Period on Pre-AnnouncementPeriod {-10,-1} CAR ..............................................48

Table 8:

Test of H7: Regressions of Post-Announcement-Period CAR ...........49

Table 9:

Test of H8: Regression of Summer/Non-Summer Differences in
Announcement-Period CAR ..........................................56

Table 10: Test of H9 and H10 ...............................................57

v

ABSTRACT
Conventional wisdom, as well as recent research (Hong and Yu 2009),
suggest that trading activity and returns decrease during the summer months,
possibly due to decreased market participation by net-buying noise traders.
I extend previous research by specifically testing for differences in returns
in the period surrounding both summer and non-summer earnings announcements.
I document lower abnormal returns surrounding summer earnings announcements
compared

to

non-summer

announcements.

My

results

suggest

that

this

difference in abnormal returns is greater in the online-trading period-- an
era characterized by increased noise trading.

However, I do not find this

difference between summer and non-summer announcement-period returns to be
related to a firm’s analyst following, market-to-book ratio, or the summer
vs. non-summer difference in a firm’s announcement-period trading volume. In
addition, I do not find evidence that the summer vs. non-summer difference in
announcement-period returns is affected by the level of unexpected earnings
revealed in the earnings announcement.

vi


CHAPTER 1
INTRODUCTION
It is a widely-held belief that trading activity decreases during the
summer months, spawning the term ―summer doldrums‖ to
period.

1

describe this time

Hong and Yu (2009) confirm the existence of significantly lower

trading volume and returns on U.S. exchanges during the summer (measured as
the months of the 3rd calendar quarter (July through September)).

They find

that trading volume decreases by 8.9% and monthly returns decrease by 1%
during

the

summer.

They

also

document

lower

summer

countries with summer decreases in trading volume.
findings

of

lower

summer

returns

and

trading

returns

for

other

They attribute their

volume

to

the

relative

inattention/absence of both institutional investors and noise traders.
Much accounting literature has examined the market reaction to earnings
announcements (Ball & Brown 1968, Beaver 1968, among many others).

Some

research has focused on how this price and/ or volume reaction is affected by
the timing of the earnings announcement, such as the day of the week of the
announcement

(Dellavigna

and

Pollet

2009)

or

the

time

of

day

of

the

announcement (Doyle and Magilke 2009).

However, to my knowledge, my study

represents

the

the

first

to

examine

how

market

reaction

to

earnings

announcements is affected by the pervasive and predictable summer slowdown in
trading activity.

I extend the work of Hong and Yu (2009) by examining the

effect that this summer decrease in investor attention may have on the market
reaction to U.S. earnings announcements made during the summer.

My study

focuses primarily on the relative summer absence of noise traders and its
effect

on

earnings

announcement

price

reactions

and

earnings

response

coefficients (ERC’s), or the market price reaction to a unit of earnings
surprise.
Though noise traders are thought to be unsophisticated, a considerable
amount of research suggests that their trading can affect stock returns.
Barber and Odean (2008) find that noise traders tend to trade in stocks that
1

Abundant references to the typical summer slowdown in trading activity can be found
in the popular literature using a key word search. Examples include:
/> /> /> /> />
1


catch their attention.
which

The personal preferences of noise traders can dictate

attention-grabbing

stocks

they

will

buy.

The

authors

suggest

that

contrarian investors may choose to buy out-of favor stocks that catch their
eye, while momentum investors may chase recently high-performing (glamour)
stocks.

Due to noise traders’ aversion/ inability to sell short, they act as

net-buyers of these attention-grabbing stocks.
Lee

(1992)

positive

finds

and

magnifying

that

noise

negative

reactions

traders

earnings
to

are

net

surprises.

positive

Consistent with this belief,
buyers

This

surprises

can

and

subsequent
have

tempering

the

to

both

effect

of

reactions

to

negative surprises. Frazzini and Lamont (2010) show that stock prices rise
around earnings announcements and suggest that this earnings announcement

premium is driven by small (noise) investor buying when the announcement
catches their attention.

Huo, Peng, and Xiong (2009) suggest that individual

investor attention can both increase price overreactions in up markets as
well as attenuate underreactions to events such as earnings reports.

Lamont

and Thaler (2003) suggest that the mispricing caused by noise traders may not
be fully corrected by arbitragers.

Other research argues that increased

online trading has lead to greater noise trader participation and greater
ERC’s (Ahmed, Schneible, and Stevens 2003).
Given

this

body

of

research

suggesting

that

the

presence

of

noise

traders can affect announcement-period price reactions, it stands to reason
that differences in attention levels among these investors between summer and
non-summer earnings announcements may produce differences in price reactions
around these announcements as well. Specifically, newsworthy events, such as
earnings surprises, may catch the attention of fewer net-buying noise traders
during the summer.

Therefore, I hypothesize and find that there is a less

positive price reaction around the time of a summer earnings announcement
relative to a non-summer announcement.

These results hold for both my full

sample as well as sub-samples of positive and negative earnings surprises.
I also consider how noise trader inattention and an absence of net
buying

might

affect

the

market

reaction

to

the

earnings

news

itself.

Research suggests there is significant noise-trader buying following both
positive and negative earnings surprises (Lee 1992) that catch the attention
of noise traders (Barber and Odean 2008).

It is reasonable to suggest that

the magnitude of an earnings surprise is directly related to the ability of
an

earnings

announcement

to

catch

investors’

attention.

Therefore,

the

relative inattention of net-buying noise traders during the summer may result
in a smaller positive price reaction to a unit of positive earnings surprise,
2


especially for large positive surprises.

However, this summer decrease in

net-buying noise trading may result in a larger downward price reaction to a
unit of negative earnings surprise, especially for large negative surprises.
Therefore, I hypothesize that summer ERCs will be less positive following a
positive earnings surprise, but more positive following a negative earnings
surprise.
evidence

However, my results do not support this view since I do not find
of

earnings.

a

differential

summer

vs.

non-summer

reaction

to

unexpected

This is consistent with the view that a noise-trader’s decision to

trade following an earnings announcement is based primarily on the event
itself, as opposed to the level of unexpected earnings.
Based upon the predicted and/or actual behavior of noise traders, other
types of investors may help create differences between summer and non-summer
earnings announcement price reaction and ERC’s.

Frazzini and Lamont (2010)

provide evidence of a general increase in institutional-investor buying just

before

earnings

announcements.

However,

this

buying

is

followed

by

institutional selling beginning just after the announcement, as noise-trader
buying

emerges.

Therefore,

Frazzini

and

Lamont

institutional investors front-run noise traders.

(2010)

conclude

that

Noise-trader-induced price

appreciation immediately following the announcement can make institutionalinvestor

pre-announcement

investors

choose

announcement.
buyers

not

buying

to

profitable

sell

the

even

shares

if

the

immediately

institutional
following

the

In such situations, these institutional investors act as net-

during

the

combined

pre-announcement

and

announcement

periods.

Because they may anticipate it to be less profitable, institutional investors
may decrease the amount of their pre-announcement buying in the summer since
there are fewer net-buying noise traders to boost the stock price following
the announcement.

I find evidence consistent with this view as I document

lower pre-announcement-period abnormal returns in the summer period compared
to those of the non-summer period.
increased

in

the

(noise) trading.
to

the

effects

online

period,

I conclude that this difference has

perhaps,

due

to

the

increase

in

online

Therefore, the behavior of other investors may contribute
under

examination

based

upon

the

perceived

and/or

actual

behavior of noise traders.
In

addition

announcement-period

to

examining

event

window,

price
I

reaction

test

for

within

possible

the

shorter-term

differences

in

the

longer-term price reaction to summer announcements compared to that of nonsummer

announcements.

investor

attention

at

Research
the

time

suggests
of

an
3

that

earnings

in

some

cases

announcement

may

decreased
cause

a


reduced

immediate

price

reaction

(Dellavigna and Pollet 2009).
whether

decreased

followed

by

increased

price

drift

Consistent with this notion, I investigate

investor

attention

during

the

summer

also

causes

differences in the delayed price reaction to summer vs. non-summer earnings
announcements.

I find a direct relationship between announcement-period

cumulative abnormal returns (CAR’s) and longer-term, post-announcement CAR’s.
In addition, my results suggest that, on average, mean abnormal returns over
the longer post-announcement period are lower during the summer than during
the non-summer period, even after controlling for announcement-period returns
or unexpected earnings.

I find some evidence of a summer vs. non-summer

difference in post-announcement price drift.

Taken together, these results

support the belief that post-announcement returns are also affected by the
summer absence of net-buying noise traders.
Even

though

the

summer

slowdown

may

produce

differential

effects

regardless of whether a firm announces good or bad news, it is reasonable to
suggest that not all firms will be affected equally.

Specifically, the

stocks that experience the largest noise trader participation in the nonsummer period may be associated with the largest change in price reaction and
ERC’s

during

absent.

the

summer

when

those

net-buying

noise

traders

tend

to

be

All else equal, a decrease in noise trader participation translates

to an overall decrease in net-buying trading volume and, consequently, an
overall decrease in returns.

Therefore, I hypothesize that the difference in

announcement-period abnormal returns is directly related to the difference in
summer vs. non-summer announcement-period trading volume; however, my results
do not support this prediction. Barber and Odean (2008) suggest that noise
traders are more likely to trade in stocks that catch their attention.
analyst

following

interest.

and

market-to-book

ratio

(MTB)

to

proxy

for

I use

investor

I control for unexpected earnings (UE) because it is reasonable to

suggest that the magnitude of an earnings surprise is directly related to the
ability of an earnings announcement to catch investors’ attention.
after

controlling

relationship

for

between

unexpected
the

summer

earnings,
vs.

I

do

non-summer

not

find

difference

a
in

However,

significant
a

firm’s

announcement-period abnormal returns and either its MTB or analyst following.
Similarly, I do not find a significant relationship between either MTB or
analyst following and the summer vs. non-summer difference in announcementperiod trading volume.

It may be the case that overall trading volume is

driven, in large part, by forces other than those under consideration (e.g.
high-frequency trading).
4


My study contributes to the literature by examining how stock prices
impound the information contained in accounting disclosures based upon both
the size and composition of the audience for the disclosure.

It stands to

reason that inattention on the part of sophisticated investors who trade
according to estimates of fundamental value may cause the price discovery
period

to

be

prolonged.

However,

the

inattention

of

net-buying

noise

traders, as appears to be the case in the summer, may actually alleviate
upward pressure on prices.
2009,

Patell

between

and

firm

Wolfson

disclosures

While previous research (Dellavigna and Pollet
1982,
and

among

others)

investor

addresses

inattention

the

in

relationship

other

specific

situations, little attention has been paid to the differences in trading
environment between the summer and non-summer period.

Prior research has

addressed noise-trader behavior (Barber and Odean 2008; Lee 1992; Ahmed et
al. 2003, among others) as well as the effects of the typical summer slowdown
in trading activity (Hong and Yu 2009).

However, to my knowledge, mine is

the first study to examine the effects that the summer inattention of noise
traders has on earnings announcement returns and trading volume.

Because the

summer slowdown is a recurring, predictable phenomenon affecting the vast
majority of publicly-traded firms, my results may help investors make better
trading decisions, especially during the summer.

In addition, my findings

may encourage accounting researchers to control for summer effects to better
test for other earnings announcement phenomena.
The
provides

rest
a

of

this

discussion

paper

of

is

organized

background

as

follows.

literature.

The

Chapter

3

next

chapter

contains

the

theoretical background for the hypotheses that I test.

Chapter 4 provides a

discussion

analyze

of

my

research

design.

In

Chapter 6 concludes.

5

Chapter

5,

I

my

results.


CHAPTER 2
BACKGROUND

2.1 Noise vs. Sophisticated Traders
Due

to

their

information

content,

earnings

announcements

significant market reaction (Beaver 1968, Ball & Brown 1968).

cause

a

Accounting

research has extensively studied this reaction in an effort to determine the
factors

affecting

ERC’s

(Collins

and

Kothari

1989;

Easton

and

Zmijewski

1989), stock price (Atiase 1985), and trading volume (Bamber et al. 1995)
following

the

announcement.

While

much

of

the

literature

focuses

on

identifying firm characteristics that help determine the nature of the market
reaction, my study focuses primarily on the characteristics of the audience
of investors for the announcement.

The differential beliefs and behavior of

these investors can help dictate the nature of the market response to the
announcement.
According to Beaver (1968), the change in price reflects the average
change in investors’ beliefs whereas trading volume reflects the sum of the
differences in investors’ reactions to the earnings announcement.

Several

trading models involving price change and volume have since been constructed
(Kim and Verrecchia 1991, 1994, Abarbanell et al. 1995, Kandel and Pearson
1995, among others).

An important drawback of many early models of trade in

speculative

markets

is

both

information

identically

as

the

well

assumption
as

the

that

agents

simplifying

change is directly related to trading volume.

interpret

prediction

public

that

price

With such assumptions, some

models are unable to explain the often-observed situation of heavy trading
volume accompanied by little or no price change or vice-versa (Bamber and
Cheon

1995).

Kandel

and

Pearson

(1995)

improve

upon

much

of

the

prior

literature by modeling the scenario in which agents are heterogeneous in
their interpretation of news as well as their prior beliefs.
allows

for

the

presence

of

―noise‖

traders

whose

naïve

Their model
trading

can

significantly alter the price move that would otherwise be caused by the

trading of informed investors (Kyle (1985), Hasbrouck (1991)).
these

noise

traders

take

the

opposite

side

of

a

trade

with

The more that
an

informed

investor, the less an informed investor’s trades will change the price of a
stock and reveal private information.

Consequently, noise trading can both

distort the assumed positive relationship between trading volume and price

6


change

as

suggest

well
that

as

cause

price

noise-trader

movement

behavior

away

from

helps

fundamental

drive

the

value.

effects

I

under

consideration in my study.
Though

to

be

uninformed, evidence suggests it could introduce an upward price bias.

By

analyzing

the

noise

intraday

trading

transaction

of

small

data,

Lee

investors

(1992)

finds

is

thought

that

noise

traders

(those placing orders of less than $10,000) are net buyers subsequent to both
positive and negative earnings surprises.

Consistent with these results,

Barber and Odean (2008) suggest that individual investors are net buyers of
attention-grabbing stocks following events such as earnings announcements.
By analyzing stock transactions in individual brokerage accounts, the authors
find that individual investors are net buyers on high volume days, days when
stocks

are

in

the

news,

and

days

following

extremely positive one-day returns.

both

extremely

negative

and

Huddart, Lang, & Yetman (2009) document

increased noise-trader buying when examining the increased trading volume
that occurs when stock prices cross either the upper or lower limit of a key
trading range—another example of an attention-grabbing event.

Barber and

Odean (2008) cite the time and resource constraints that noise traders face
in selecting stocks to buy.

These individuals cannot thoroughly screen the

thousands of possible selections; thus, they will more likely purchase a
stock that has grabbed their attention.

An earnings announcement itself can

prompt noise-trader buying, regardless of the earnings news.

Stocks that

miss an earnings forecast may be favored by bargain-hunting noise traders who
take a contrarian view to that of the market.

Stocks that meet or beat a

forecast may attract buying from momentum investors chasing high-performing
(glamour) stocks.
Noise traders do not face the same daunting selection task when selling
stock since they will most likely sell one of the stocks they already own
instead

of

traders

are

mechanical

selling

short.

especially
impediments

Lamont

burdened

and

by

Thaler

short-sale

administered

by

(2003)

suggest

constraints

regulators.

This

that

noise

through

the

aversion

or

inability to sell short tends to cause noise traders to be net-buyers who
exert upward price pressure on stocks following both positive and negative
earnings surprises.

This net-buyer effect of noise traders is consistent

with Miller (1977), who suggests the holders of a stock will tend to be those
who are most optimistic about its prospects and that, given institutional (or
self-imposed)
potential

constraints

owners

on

(potential

short-selling,
buyers)

should

7

any

increase

result

in

a

in

the

price

set

of

increase.


Lamont

and

Thaler

constraints

and/or

(2003)

suggest

that

risk,

stock

liquidity

in

the

prices

presence
can

be

arbitragers are unable or unwilling to correct them.

of

short-sale

mispriced

because

They discuss examples

of such clear mispricing, including the well-documented spin-off of Palm by
its parent company 3Com in 2000.

In this case, despite the fact that there

was a simple, relatively risk-free arbitrage opportunity, the shares of the
two companies remained wildly mispriced for months because of the short-term
constraints on selling short.
Frazzini

and

Lamont

(2010)

provide

additional

trading can introduce an upward price bias.
around

earnings

announcements

earnings

announcement

intraday

transaction

and

premium
data

that

to

―quantitatively

consistently

address

that

noise

They show that stock prices rise

this

appears

evidence

which

since

set(s)

of

substantial‖

1927.

Using

investors

are

responsible for the premium, the authors use small trades (less than $5,000)
as a proxy for individual investors and big trades (over $50,000) as a proxy
for institutional investors.

They conclude that the earnings announcement

premium is driven by noise-trader buying when the announcement catches their
attention.

They find evidence that large investors are aware of the premium

and trade in anticipation of it.

They document abnormal net-buying by large

investors in the two-week period preceding the earnings announcement.

This

large-investor buying activity reverses on announcement day and on the two
trading days subsequent to the announcement, when noise-trader buying is most
intense.

Large

diminishing
premium.

what

investors
would

appear

otherwise

to
be

be
an

front-running
even-larger

noise

earnings

traders

and

announcement

However, the presence of abnormal returns immediately following

announcements indicates that large investors have not eliminated the premium.
The

premium

may

continue

to

exist

because

of

market

frictions

such

as

transaction or holding costs (Lamont and Thaler 2003).
Evidence suggests that, in addition to affecting returns, noise traders
can also affect ERC’s.

Ahmed et al (2003) address the assertion that the

advent of online trading has increased the ratio of naïve (noise) traders to

sophisticated traders.

Because sophisticated investors are thought to have

more precise information than do noise traders, the online period is thought
to

be

associated

information
precise

prior

prior

with
to

a

decrease

earnings

information

will

in

the

average

announcements.
rely

more

on

precision

Since
the

of

investors
earnings

investor
with

less

announcement

information, this decreased average precision of prior information in the
online period would translate to larger revisions in investor beliefs post8


announcement and, hence, larger ERC’s.

Consistent with these views, Ahmed et

al (2003) cite increased noise trading for their finding of larger ERC’s in
the online period (1996-99) than in the pre-online period (1992-95).

The

authors combine positive and negative earnings surprises in their analysis,
implicitly

assuming

a

symmetric

relation.

However,

it

is

possible

that

noise-trader effects on the ERC may depend upon the sign of the earnings
surprise.
Prior research finds that noise traders are net-buyers following both
positive and negative earnings surprises (Lee 1992) in stocks that catch
their

attention

likelihood

(Barber

that

a

and

stock

Odean

catches

2008).

a

It

noise

stands

trader’s

to

reason

attention

that

is

the

directly

related to the magnitude of the earnings surprise for both positive and
negative surprises.

This would suggest there may be significant noise-trader

buying following both large positive and negative earnings surprises.

Stocks

that miss an earnings forecast can attract bargain-hunting, contrarian noise
traders.

Stocks that meet or beat a forecast may induce buying from momentum

investors chasing high-performing (glamour) stocks.
Evidence indicates not only that noise traders are net-buyers around
earnings announcements, but also that this behavior can have a significant
effect

on

returns

and/or

sophisticated investors.

ERC’s

because

it

is

not

fully

counteracted

by

It follows, then, that returns and/or ERC’s are

likely to vary according to the attention levels of noise traders.

The next

section provides a discussion of evidence supporting this view.
2.2 Investor Inattention and Delayed Price Response
Research
affect

the

announcement.

suggests

size

and/or

the

reaction

composition

more

of

of

an

the

earnings

investor

announcement
audience

for

can
the

Doyle and Magilke (2009) examine the difference in trading
for

announcements

before-the-market-open (BMO).
attract

timing

In turn, this can affect the price and/or volume reaction to

the announcement.
volume

that

investor

made

after-the-market

close

(AMC)

and

It has been suggested that AMC announcements

attention

because

of

the

larger

amount

of

time,

compared to that of BMO announcements, that elapses between the announcement
and the resumption of trading in the stock the following morning.
evidence

consistent

with

increased

noise-trader

participation

They find
for

AMC

announcements as they document larger abnormal trading volume following an
AMC

announcement.

Dellavigna

and

Pollet
9

(2009)

suggest

that

investor-


attention levels for earnings announcements also vary according to the day of
the week the announcement is made.
that

there

weekdays,

is

less

they

investor

document

less

Consistent with the traditional view

attention
immediate

on

Fridays

price

compared

response

and

with

trading

other
volume

following a Friday earnings announcement.
If

low

investor

attention

levels

at

the

time

of

an

earnings

announcement result in a lower immediate price response to the announcement,
it is reasonable to believe that the stock price may continue to ―drift‖ as
investors revisit the information contained in the announcement and correct
the initial mispricing.

Indeed, this reasoning has been used to explain the

phenomenon of post-earnings announcement drift (PEAD).

PEAD describes the

well-documented tendency of post-announcement stock prices to continue to
move in the direction of an earnings surprise (Ball and Brown 1968, Bernard
and

Thomas

1989).2

While

Dellavigna

and

Pollet

(2009)

find

less

of

an

immediate price response to Friday earnings announcements, they find that
Friday earnings announcements are associated with more price drift in the
post-announcement

period

(up

to

75

trading

days

after

the

announcement).

They suggest that PEAD represents a delay in the price discovery process

caused by investor inattention at the time of the announcement followed by a
price drift as investors continue to process the earnings information well
after the announcement.
Huo,

Peng,

attention

and
can

This explanation is supported by the evidence of

Xiong

(2009),

who

suggest

mitigate

the

drift

that

associated

increased
with

noise-trader

initial

earnings

announcement underreaction.
I build upon the existing literature on investor inattention and PEAD
in my study of summer earnings announcements.

In addition, I extend research

indicating that investor attention is lower during the summer period.

Hong

and Yu (2009) find that, for the period 1962-2005, monthly share turnover
(trading

volume

divided

by

shares

outstanding)

summer than during the rest of the year.

is

8.9%

lower

during

the

They use intraday transaction data

to determine which set(s) of investors are responsible for the decrease in
summer

trading

activity.

Consistent

with

the

technique

of

Frazzini

and

Lamont (2010), the authors use small trades (less than $5,000) as a proxy for
individual

investors

and

institutional investors.

big

trades

(over

$50,000)

as

a

proxy

for

They find a summer decrease in trading activity for

2

Instead of attributing PEAD to investor inattention at the time of the announcement,
Bernard and Thomas (1989) suggest that it is caused primarily by an apparent inability
of the market to understand the implications of current quarterly earnings for future
earnings.

10


both sets of investors.
in

summer

returns

for

In addition, Hong and Yu (2009) document a decrease
a

total

of

51

countries

significant decrease in summer trading volume.

which

also

experience

a

The authors conclude that

the decrease in summer returns is related to the decrease in summer trading
volume and that both are caused by inattention on the part of investors,
including noise traders.
Research indicates that inattention on the part of net-buying noise
traders

can

announcements.

affect

returns

and

trading

volume

following

earnings

In addition, existing evidence suggests that there is less

investor attention during the summer.

However, mine is the first study, that

I know of, to examine if and how this general summer slowdown affects both
the short and long-term reaction to summer earnings announcements.

Because

the summer slowdown is both pervasive and predictable, insights from my study
should be of use to researchers and capital market participants both inside
and outside the firm.

11

CHAPTER 3
HYPOTHESIS DEVELOPMENT
3.1 Noise Traders’ Effect on Returns
Because
traders

are

of

their

normally

inability

net-buyers

or
of

unwillingness
stocks.

Due

to

sell

short,

to

time

and

noise

resource

constraints, they tend to buy stocks that catch their attention through a
newsworthy event such as an earnings announcement (Barber and Odean 2008).
Evidence suggests they are net-buyers following both positive (―meet-or-beat‖
forecasts) and negative (―miss‖ forecasts) earnings surprises (Lee 1992).
Sophisticated

traders

may

nullify its effects.
announcement
investors,

is

the

not

rationally

anticipate

noise-trader

behavior

and

But if this noise-trader buying at the time of the
fully

upward

counteracted

pressure

leads

to

by
an

the

trading

earnings

of

sophisticated

announcement

premium

(Frazzini and Lamont 2010). Thus, it stands to reason that inattention on the
part of noise traders will have a negative effect, on average, on stock
returns and trading volume following an earnings announcement (Dellavigna and
Pollet 2009).
Hong and Yu (2009) suggest that investor attention is lower during the
summer for both institutional investors and noise traders.

Institutional

investors are willing to both buy stocks as well as sell short according to
their more sophisticated beliefs regarding fundamental value; hence, their
inattention

should

not

have

a

pronounced

asymmetric

effect

on

returns.

However, for noise traders, earnings announcements by themselves can trigger
buying

regardless

of

the

earnings

news.

Therefore,

I

suggest

that

inattention on the part of net-buying noise-traders during the summer results
in lower returns immediately following the announcement for both positive and
negative earnings surprises.

This leads to my first hypothesis:

H1: Announcement-period abnormal returns are lower during the summer period
than during the non-summer period.
3.2 Noise Traders’ Effect on the ERC
Hypothesis 1 predicts an overall shift in the level of announcementperiod returns, irrespective of the earnings news.

12

In addition, I examine


how

differential

underlying

levels

earnings

of

investor

information.

attention

Ahmed

et

impact

al.

the

(2003)

pricing
suggest

of

the

that

an

increase in noise trading during the online-trading era has increased the
ratio of noise traders to sophisticated investors participating in the stock
market.

Since noise traders are assumed to have less precise information

than

sophisticated

do

traders,

they

argue

that

this

has

resulted

in

a

decrease in the average precision of investor information prior to earnings
announcements.

The authors conclude that this translates to larger ERC’s as

investors revise their beliefs to a larger degree based on the earnings
surprise because of their less precise information pre-announcement.

Thus,

they suggest that noise traders are responsible for their finding that ERC’s
have increased in the online period (beginning in 1996) for a combined sample
of both positive and negative earnings surprises.
If net-buying noise traders tend to increase ERC’s for all earnings
surprises, then one might expect that summer noise-trader inattention may
produce lower ERC’s for all summer announcements.

However, it is possible

that noise-trader effects on the ERC depend upon the sign and/or magnitude of
the earnings surprise.

This is because there may be significant noise-trader

buying following both positive and negative earnings surprises (Lee 1992),
especially for large surprises in either direction that catch noise traders’
attention (Barber and Odean 2008). It follows that the relative inattention
of

net-buying

noise

traders

during

the

summer

may

result

in

a

smaller

positive price reaction to a unit of positive earnings surprise, especially
for large positive surprises.
net-buying
negative

may

result

earnings

in

a

However, this summer decrease in noise trader
larger

surprise,

downward

especially

price

for

reaction

large

to

a

negative

unit

of

surprises.

Therefore, while a strict extension of Ahmed et al. (2003) would predict that
summer

ERC’s,

compared

to

those

of

non-summer,

are

smaller

for

negative

earnings surprises, I expect that the absence of net-buying noise traders

causes summer ERC’s to be larger for negative earnings surprises.
hypothesize

that

announcements,

are

summer

earnings

associated

with

announcements,
a

smaller

ERC

surprises and a larger ERC for negative surprises.

compared
for

to

Thus, I
non-summer

positive

earnings

This forms my second

hypothesis:
H2: For positive (negative) earnings surprises, the ERC is smaller (larger)
for summer announcements than for non-summer earnings announcements.

13


3.3 Pre-Announcement Period Returns
The relative summer inattention of noise traders may prompt changes in
institutional
decide

to

investor

profit

behavior.

from

this

Sophisticated

noise-trader

investors

behavior

by

may

buying

rationally

in

the

pre-

announcement period and then selling into the noise–trader buying following
the announcement.

Consistent with this view, Frazzini and Lamont (2010) find

increased institutional-investor buying pre-announcement along with increased
institutional-investor selling pressure following the announcement. However,
this selling does not completely eliminate the earnings announcement premium.
This could be due to market frictions that prevent arbitragers from fully
correcting the mispricing caused by noise traders (Lamont and Thaler 2003).
If institutional investors front-run anticipated buying of noise traders,
then, during the summer, fewer institutional investors may be buying in the
pre-announcement
traders

to

be

period.
buying

This

in

the

profit opportunity to exploit.

could

be

announcement

because
period

they
and,

expect

fewer

noise

consequently,

less

This would be consistent with the findings of

Hong and Yu (2009), who suggest that trading activity decreases in the summer
for both noise traders as well as institutional investors. This leads to my
third hypothesis:
H3:

Pre-announcement-period

abnormal

returns

are

lower

during

the

summer

period than during the non-summer period.
3.4 The Effect of the Online Period
The proliferation in recent years of 24-hour news dissemination and
online, low-cost trading may have impacted the traditional differences in the
summer vs. non-summer periods.

Prior research (Ahmed et al. 2003, Barber and

Odean 2002) suggests that the emergence of online trading has led to more
overall

noise

trading,

where

online

investors,

compared

to

professional

investors, are thought to be less sophisticated and profitable (Barber and
Odean 2002).

It is reasonable to suggest that the overall increase in noise

trading in the online period has created a larger difference between the
summer vs. non-summer levels of noise trading.

This is because the more

noise trading there is in the non-summer period, the larger the potential
decrease in noise trading that will occur due to the summer inattention of
14


noise traders.

Simply stated, the level of inattention on the part of noise

traders is relevant only when they have the ability to trade in the first
place.

The innovations of the online period have enhanced this ability.

My

focus is on differences in investor attention between summer and non-summer
periods; therefore, I examine whether the effects hypothesized in H1 through
H3 are stronger in the online period than in the pre-online period.

Since I

believe the summer vs. non-summer difference in noise-trading activity has
increased in recent years, I believe the effects that I am already testing
have become more pronounced in the online period. This leads to my next three
hypotheses:
H4: The difference between summer and non-summer announcement-period abnormal
returns is greater in the online period than in the pre-online period.
H5: The difference between summer and non-summer ERC’s is greater in the
online period than in the pre-online period.
H6:

The

difference

between

summer

and

non-summer

pre-announcement-period

abnormal returns is greater in the online period than in the pre-online
period.
Consistent with my analysis of H1- H3, I test H4- H6 by examining
positive and negative earnings surprises separately as well as in a combined
sample.
3.5 Post-Earnings Announcement Drift
As previously discussed, I believe that an absence of net-buying noise
traders in the summer results in less positive returns immediately following
the earnings announcement.
term

returns

Expectations

that

As part of my study, I also examine the longer-

occur

regarding

these

in

the
returns

post-announcement
are

less

clear.

(drift)
The

period.
relative

inattention of net-buying noise traders in the summer is expected to result
in a less upward-biased price immediately after the earnings announcement.
All else equal, any post-earnings announcement drift would be relatively more
symmetric than the drift following non-summer announcements, assuming prices
gravitate to fundamental values during the summer post-announcement period as
they

may

in

the

non-summer.

However,
15

if

there

is

also

relatively

less


attention

on

the

part

of

institutional

investors

who

trade

according

to

fundamental value then there may be a greater delay in the price discovery
process during the summer.

This could exacerbate the price drift in the

direction of the earnings surprise (positive and negative) as these investors
later revisit the earnings information.
Dellavigna and Pollet (2009) find that Friday earnings announcements
are associated with significant price drift in both directions as investors
re-emerge and begin to correct the initial underreaction as early as the
following week.

While Friday earnings announcements may be characterized by

relatively high levels of inattention on the part of both sets of investors,
the results of Dellavigna and Pollet (2009) are likely driven primarily by
institutional
announcement.

investor

inattention

at

the

time

of

a

Friday

Relative inattention of noise and sophisticated traders are

likely to have distinct effects on the nature of the summer PEAD.
institutional

earnings

investor

inattention

may

cause

an

initial

As noted,

underreaction

in

price followed by a symmetrical price drift in the direction of the earnings
surprise.

Thus, prices might be slower to gravitate to fundamental values in

the summer.

Alternatively, noise-trader inattention may cause a lack of

upward-biased price reaction to the earnings announcement.

Assuming that the

earnings information is not fully impounded in prices at the time of the
announcement, as suggested by prior research, summer announcements might be
followed by a more symmetric price drift than for non-summer announcements.
Announcement-period inattention on the part of both sets of investors may
result in price drift in both directions, with the positive price drift being
stronger than the negative drift.

Adding to the difficulty in predicting

price drift is the uncertainty regarding the timing and extent of the reemergence of investors necessary to create the price drift.

Hong and Yu

(2009) find that returns for the entire summer period are generally lower
than for the non-summer period.

This is consistent with there being less

summer noise-trader attention during the announcement period as well as the
post-announcement period—at least until the end of the summer.

In other

words, investors may not re-emerge before the end of the summer period to
correct any initial underreaction.
dominate.

Therefore,

difference

in

I

expect

post-announcement

I am not sure which of the effects will
that
price

hypothesis:

16

there

is

drift.

a

summer
This

vs.

becomes

non-summer
my

next

H7:

There

is

a

summer

and

non-summer

difference

in

longer-term,

post-

announcement price drift.

3.6

Trading Volume
Hong and Yu (2009) find that both trading activity and returns are

lower during the summer.

Both effects may be caused, at least in part, by

the relative inattention of noise traders and, thus, the relatively less
upward price pressure during the summer.
should

be

difference

positively
in

total

correlated
trading

with

volume

Because noise trader attention

total
between

trading

the

volume,

summer

and

I

use

the

non-summer

announcement periods as a proxy for the difference in noise trader attention.
I suggest that the greater the difference in summer vs. non-summer attention
of noise traders (as

proxied by the difference in summer vs. non-summer

announcement-period trading volume), the greater the difference in summer vs.
non-summer announcement returns as well.

However, it may be the case that

factors such as high-frequency trading sufficiently distort the relationship
between returns and trading volume such that I do not find an association.
This leads to my next hypothesis:

H8:

The

returns

difference
is

in

increasing

summer
in

and

the

non-summer

difference

announcement-period

between

summer

and

abnormal

non-summer

announcement-period trading volume.
3.7

Investor Interest
The

possibility

that

the

summer

slowdown

produces

an

appreciable

decrease in noise trader activity is directly related to a stock’s level of
non-summer, baseline noise trader participation.

Simply put, it is those

stocks that noise traders normally trade that should experience a greater
effect on volume and returns due to less attention.
noise

traders

will

be

more

likely

attention (Barber & Odean 2008).

to

trade

in

Evidence suggests that

stocks

that

catch

their

Salience of a stock is likely reflected by

the number of analysts following the stock since it is reasonable to assume
that analyst following is positively related to overall investor interest
17


(O’Brien and Bhushan 1990).

Therefore, analyst following for a stock should

be directly related to both noise trader participation in the baseline, nonsummer period as well as the drop-off in noise trader participation during
the summer.

This large reduction in noise trader participation may result in

a large reduction in both announcement-period abnormal returns and trading
volume.

This leads to my next hypotheses:

H9A: The difference in summer and non-summer announcement-period abnormal
returns is increasing in analyst following.
H9B:

The

difference

in

summer

and

non-summer

announcement-period

trading

volume is increasing in analyst following.
Another
ratio (MTB).

possible

proxy

for

investor

interest

is

the

market-to-book

The MTB has been used to differentiate ―growth‖ or ―glamour‖

stocks from ―value‖ stocks.

Therefore, all else equal, high-MTB stocks may

be more likely to catch the attention of noise traders (Hong and Stein 2007).
Therefore,

a

stock’s

MTB

may

be

directly

related

to

both

noise

trader

participation in the baseline, non-summer period, as well as the drop-off in
noise trader participation during the summer.

This large reduction in noise

trader participation for high MTB stocks may result in a large reduction in
announcement-period returns and trading volume for these firms.

My next

hypotheses are as follows:
H10A: The difference in summer and non-summer announcement-period abnormal
returns is increasing in market-to-book ratio.
H10B: The difference in summer and non-summer announcement-period trading
volume is increasing in market-to-book ratio.

18