Beaver WH - The Information Content of Annual Earnings Annou

8/8/2019 Beaver WH - The Information Content of Annual Earnings Annou

1/27

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

The Information Content of Annual Earnings AnnouncementsAuthor(s): William H. BeaverReviewed work(s):Source: Journal of Accounting Research, Vol. 6, Empirical Research in Accounting: SelectedStudies 1968 (1968), pp. 67-92Published by: Wiley-Blackwell on behalf of Accounting Research Center, Booth School of Business,University of Chicago

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2/27

The Information

ontent

fAnnual

Earnings

nnouncements

WILLIAM

H. BEAVER*

The informationontent fearningss an issueofobvious mportance

is

a

focal point for many

measurement

ontroversies

n

accounting.Th

paper

empirically

xaminesthe

extent to

which common tock invest

perceive

arnings

o

possess

nformational

alue. The

study

directs

ts a

tention o investor eaction

o earnings

nnouncements,

s reflected

n

t

volume

and

price

movements f

common tocks

n

the

weeks surround

the

announcement ate.

Valuation theory

has

long posited

a

relationship

etween arnings

thevalue of common

tock. Miller

and

Modigliani

postulate

that one

i

portant

lement

n

determining

he

value of common tock

s

the product

earnings

times

the

appropriate

arnings

multiplier

or

that

risk clas

Graham,Dodd,

and

Cottle take

a

similar

osition

with

respect

o the co

putation

of their

intrinsic alue

of common

tock securities.2

M

al

provideempirical

vidence

that

suggests

f

reported

arnings re

adjust

for

measurement rrors

hrough

he use

of nstrumental

ariables,

he

a

justed earnings

re useful

n

the

prediction

f the marketvalue

of elect

utility

irms.

n

fact,

he evidence

ndicated

hat

the earnings

ermwas

t

most mportantxplanatory ariable n the valuation equation.3The re

tionship

s a

necessary

ondition or

arnings

o

have

information

onte

*

Assistant

Professor,

niversity

f Chicago.

'Merton

H. Miller nd

Franco

Modigliani,

Some

Estimates

fthe Cost

of

Capit

to the

ElectricUtility

ndustry,

954-57,

American

conomicReview, VI

(Ju

1966),

341.

2

BenjaminGraham,

David L. Dodd,

and

Sidney Cottle,Security

nalysis

Ne


3/27

68

EMPIRICAL RESEARCH IN

ACCOUNTING: SELECTED

STUDIES, 1968

but the evidencedoes not preclude he possibility hat the oppositema

be true.

Although here re many reasonsfor

dopting he position hat earnin

lack informational alue, two are

frequently ffered. 1) Measureme

errors n

earnings

re so

large

that t would be better o estimate he val

of common tock

directly

rom

he

instrumental

ariables

rather

han

u

earnings

s an intermediate

tep. (2)

Even

though arningsmight onv

information,here are other sources

available to investors hat conta

essentiallyhe same

informationut are more

timely.By

the

time

annu

earnings

re

released, ny potential

nformationontent

has

already

be

processed y investors nd

is

impounded

n

the market

rice.The impli

tion

of both

arguments

s

earningsreports

have little or no

informat

content.

The issue

is

of major concern o the accountingprofession ecause i

outcome

directly

eflects

pon

the

utility

f the

accounting ctivity.

O

approach

o

examining

his

ssue

s to

specify

n

expectations

modelof ho

investors elate reported arnings o marketprices. The paper present

by Benstonat last year's Conference ollowed uchan approach.4 enst

found

price changes

were

argely

nsensitive

o

earnings,

which

taken

face value

is

unfavorable

o the

utility

f

earnings

data. But such

resu

are always

difficulto

interpret ecause the

ack

of

an

observed

elations

may be due to eitherone or both of

two

factors.

Either

no

relations

exists

or

the

expectations

model was

improperlypecified.

t is

impossi

to

determine he extent

o

which he

negative

indings

re due

to the att

rather han the former.

The approachtaken here s to apply

tests that requireno assumpti

about theexpectationsmodelsof nvestors.Note that the issue underco

sideration

s

of

a

positive

rather

than

a

normative

nature-that

is,

t

question

of concern

s

not

whether

nvestors

hould

eact

to

earnings

b

ratherwhether nvestors

o

react to earnings.

Definitions f nformation

ontent

Information

as been defined s a change

n

expectations

bout the ou

come ofan event.'Within he context fthis tudy, firm'sarnings epo

is said

to have informationontent

f

it leads

to a change

in

investo

assessments f

the probabilitydistribution f futurereturns or price

such

that there s a

change

n

equilibrium alue ofthe

currentmarket

ric

GeorgeJ. Benston, Published CorporateAccounting ata and Stock Prices

Empirical Research in Accounting: Selected Studies, 1967, Supplement to Vol.

Journal of Accounting Research, pp. 1-54.

I

Henri Theil, Economics and Information Theory (Chicago and Amsterda

Rand McNally and

North

Holland PublishingCompany, 967),Ch.

1.

6

A furthertipulations oftenmadethat nformationoncerns hangesnexpect

tions boutan event hat s a parameterf decisionmodel. efining arningsnfor

tion

n

terms

f

ts mpact nfuture eturns or prices) s consistent ith

hat

furt


4/27

CONTENT OF ANNUAL

EARNINGS

ANNOUNCEMENTS 6

Althoughneither he direction or the magnitude f the price change ca

be specifiedwithoutknowing he expectations

model(s) of investors,

variability f price changes s likely

to be greaterwhen earnings re a

nounced han at other imesduring he

year.7

Anotherdefinition finformationtates that

not

only must therebe

change n expectations ut the change must be sufficientlyarge to indu

a

change

n

the

decision-maker's ehavior.According o

this

definitio

firm's arnings eportpossesses nformational alue only f it leads to a

altering fthe optimalholding f thatfirm's tock n the portfolios f

dividual nvestors. he optimal adjustment

mightbe

to

buy more

shar

or

to

sell some or all

of the shares lready

held.

n

either

vent,

he shift

portfolio ositionwould be reflected

n

the volume.

f

earnings eports

av

informationontent, he number

f

hares

raded s likely o behigherwh

the

earnings eport

s

released

han at other

imes

during

he

year.8

Relationships etweenrice

and

Volume

Tests

The relationships osited above are consistentwith the economis

notion that volume reflects lack

of

consensusregarding he price. Th

lack of consensus

s

induced by

a new

piece of information,he earnin

report. ince

nvestors

may

differ

n

the

way they nterprethe report, o

time

may elapse

before

consensus s

reached, uring

which

ime ncreas

volume

would be

observed.

f

consensuswere reachedon the first

ransa

tion, there

would be a

price

reaction

but no

volume

reaction, ssumi

homogeneous

isk

preferencesmong

investors.

f

risk

preferences iff

there

till could be a volume

reaction,

ven

after he

equilibrium rice

ha

been reached.

An

important

istinction etween he

price

and

volume tests

s

that

t

former

eflects

hanges

n

the

expectations

f the

market s a

whole

whi

the

latter reflects

hanges

n

the

expectations

f

individual nvestors.

stipulation.

or

support,

ee the iterature

n portfolio heory, speciallyHarry

Markowitz,Portfolio election:Efficientiversificationf

InvestmentsNew

Yor

JohnWiley

&

Sons,

1959).

7

The change

n equilibrium rice s

in

additionto any price

changethat wou

normally ccur

n

the absence of any

earnings nnouncement. he assumption

that thetwopricechanges re positively orrelated, ndependent,r mildly or

lated. If therewere trongnegative

orrelation, he price

changevariabilitymig

not be greater t

the announcementate. In the light

of

previous

research

n

t

behavior

f

security

rices, he assumption

f

ndependences

most ikely o be t

correct ne. See Eugene

F.

Fama,

''The Behavior

of

Stock MarketPrices, Jour

of Business,

XXXVIII

(January, 965),

34-105.

8

As

a final

parenthetical

omment n

definitions

f

nformation,ote that red

tion

ofuncertainty

as not

one

of the definitionshosen.

t

shouldbe apparent

h

in a dynamic ituation i.e., where robability

istributionssessments

re changi

over

time),

decisionmakermaybe

more

ncertain bout a

given vent fter ecei

ing a message bout the event than he was beforehe received he message.To u

Theil's terminology,he entropymay

ncrease

s

a

result

f a

message,yet the m

sage

has information

ontent. ee

Theil,op. cit.,

Ch.

2.


5/27

70

WILLIAM H.

BEAVER

piece

of nformation

ay be neutral

n

the sense of

not changing

he

expe

tationsofthemarket s a wholebut itmaygreatly ltertheexpectatio

of ndividuals.

n this

situation,

here

would

be no price

reaction,

utthe

would be

shiftsn portfolio

ositions eflected

n thevolume.

Because

th

pricereflects

he

expectations

f

many nvestors,

t

may imply

very

ef

cientforecast

f earnings or

everal

weeks

prior o

the

announcement.'

so,

the price

estmay

be less

sensitive han

volume

to earnings

eports.

The

foregoing

iscussion

uggests

hat a

reaction

may be

observed

only one

of

the tests or that

the

two tests

may

not respond

equally.

I

neither estresponds, he utilityof earningsdata and the study'ssamp

design

will be suspect.

SampleDesign

Selection f

Sample.

The

study

s based

upon

a sample

of annual

earnin

announcements

eleased

by

143 firms uring

he years

1961 through

96

Six

criteriawere

used

n

the selection

f

the sample

firms.

(1) The firm

mustbe on the

Compustat

tape;

(2) the

firmmust

be

member ftheNewYorkStock Exchange; (3) thefiscalyearmust endo

a

date

other

than

December

31; (4)

no dividends

were announced

n

t

same

week

as

the

earnings

announcement;

5)

no stock splits

we

announced during

he

17 week

period

surrounding he

announcement

earnings;

nd

(6)

there

were less than 20 news announcements

er yea

appearing

n

the

Wall Street

ournal.

Table

1

indicates he

extent

o

whi

each

criterion

ffected

he

sample

size.

Criterion

1)

was selected

because

the

Compustat

population

represe

over

90

per

cent

of the

total market

alue of the

common

tocksof

public

heldcorporationsndhence s a relevant opulation or tudy.A seconda

reason

s

the

ease with

which inancial

tatement tems

an be

obtained

f

the

Compustat

firms elative o firms ot

on the

tapes.

Although

no

fina

cial

statement

ata are

needed

for the earlier

phases

of this

study,

eve

tually

the

scope

will

be

extended

o

relating

market

prices

o the

financ

statement

tems,

namely

he

earnings

numbers.

Criterion

2)

was used because

weeklyprice

and volume

data on

NYS

firms re relatively

asy

to obtain. The Center

for Research

in

Securi

Prices (CRSP) providedtapes which contain daily price,volume, an

transaction

nformation

n all

firms n the NYSE

for the

years

19

through

965.10

Criterion

3)

was selected

n

order

o avoid

a

clustering

f announcem

9

Efficiency

s defined

n terms

f

E(x6

x*)2,

where

x is the forecasted

alue

reported

arnings

nd x* is actual

value.

The closerthe

expectation

s to

zero,

t

more

fficienthe

forecast

s. Note

that

a forecast

may

be unbiased

but

very

ne

cient.

The

distinction

etween fficiency

nd unbiasedness

s more

mportant

o

t

interpretation

f thefindings

resented

ater.

10Without he cooperation fCRSP, thedata collection horewouldhave be

overwhelming.


6/27

CONTENT OF ANNUAL EARNINGS

ANNOUNCEMENTS 7

dates during any timeperiod.Without this criterion, he sample dat

would exhibit large clustering

f announcements

n the monthsof Feb

ruary,March,

and April because two out of

three Compustat

firms r

12/31 firms.

n subsequentanalysis,an attempt

will be made

to remo

the effects f market-wide vents

from he individual

security's olum

and price

data.

When earnings

nnouncements

luster, heybecome for

of market-wide

rice indexes

and

the volume statistics.Hence,

any at

tempt

to remove the effects f

market-wide

vents would eliminate

h

effectsftheearnings eport s well.

The purposes

f criteria 4) and (5) are similar

n that they

attempt

minimize ny

ambiguity ssociated

with an observedreaction

n

the wee

of

the

earnings

nnouncement.

f

these criteriawere not

applied,

the

would be a joint

effect,nd it

would be extremely ifficulto separate

th

announcement

ffects

f dividends

r stock

plits

from

hoseof the

earnin

report.

Criterion 6)

was chosen

o that therewould

be

weeks

wherefe

if

any,

announcements ere

released. To

the

extentthat

news

items ar

announced

n

weeks

other

han theearnings

nnouncement

eek,

compa

ing thoseweekswith he earnings nnouncement eek compares he info

mation

content

of

the earnings eports

with that

of

other types

of new

announcements,

hich

s

not the

issue under

tudy.

Both the direction

nd magnitude

fany potential ias introduced

y th

selection riteria

re

difficulto assess. Criteria

1)

and

(2)

led

to

the selec

tion

of the

arger

irms

n

the

economy.

he

average

total

assets

(per

fina

cial

statements)

or

he

143

firms

n

1965

was

167 million

ollars,

nd

the

average

market

alue

of common tock

outstanding

n

1965

was 189

millio

dollars.The effect f selecting argerfirmswould tend to induce a bia

againstearnings eports

ecause

the

larger

firms

re

generally

ssociate

with greater

low f

additional nformation

han smaller

irms.

The effect

f criterion3)

was

twofold: a)

Out of the subpopulation

Compustat,

NYSE

firms,

he criterion ended to

select

the smaller

fir

even

though

they

are

probably

till

arger

han

average

for

the

econom

as

a whole.

n

1965,

the

average

total assets for

Computsat,

NYSE fir

were

441

million

dollars,

nd

the

average

marketvalue of common

toc

outstanding

was

564

million

dollars.

b)

A

greater

roportion

f retaile

and foodprocessorsppears n thesamplethan would have beenobtaine

if firms ad

not

been

restricted

on-12/31

irms.

Retailers

comprise

14.

per

cent of the

sample,

while

17.5

per

cent

of

the

firms

re

food

processo

The expectedpercentages

would have been

6.8

and

10.0, respectively,

11

A pilot study

with

similarobjectives

did

not

exclude firmswith dividend

n

nouncements

n

the

ame week s earnings.

he investor

eactionn terms f

volu

was almost

twice as large

as the reaction bserved

n this study. Stock splits

we

excluded

because previousresearch

as found

hat stock

splits possess

nformati

content.

ee

Eugene

F. Fama,

et al., The Adjustment

f Stock Prices

to New In

formation, eport 6705 (Centerfor MathematicalStudies in Businessand Eco

nomics,

GraduateSchool of Business,

University

f Dhiiago, 1967),

forthcomin

i

the nternational

conomicReview.


7/27

72 WILLIAM H. BEAVER

a random ample were drawnfrom he Compustat,NYSE subpopulati

With

respect

o

the implications or nformationontent, hereare to

no obviousreasonswhy thesefirmswould constitute biased sample,

wi

the

one

exception hat retailers end to reportfinancial tatementda

monthlywhichwould tend to induce a bias against findingnformatio

value

in

annual earnings eports. n fact,

n the analysis described ate

boththe price nd volumereactionswere

ess dramatic or he retailers n

foodprocessors han for he other irmsn

the sample.

It is possiblethat the selection riteria, specially riterion6), may i

duce

some

bias in

the oppositedirection.

s long

as

the

criteria

re visib

ex

ante,

the

populationfor

which

the

study's findings

re relevant an

easily dentified. lso, the sample criteria

an be relaxed

n

future

tudi

to discover he

generality f the findings

resented

ere

forother

popul

tions.

Data Collection. he first tep was the identificationf firms hat wou

comprise

he

sample. Meeting the criteria

n

any one

of the five

yea

(1961-1965) was a sufficientondition or

a firm's nclusion orthat yea

The resultwas a sample of 143 firms. ecause all firms id not meet t

criteria

n

everyyear,

the 143 firms

ave rise

to

506

annual

earnings

nouncements. he date of the earnings

nnouncement as obtainedfr

the

Wall

Street ournal ndex.

The distributionsf financial tatement ates and announcement at

appear

in

Table

2.

Restricting he sample

to

non-12/31

irmswas

succe

ful n

reducing he clustering f dates.

The most frequent

month

n

whi

the fiscal

year

ended

(June) represents

nly 23.8 per cent

of

the samp

whilean unrestrictedample would have resultedn 67 percent n a sin

month

(December).

With

respect to

announcementdates,

the

high

three-month

eriod September, ctober,

nd

November)

ontains 7.6

p

centof

the

announcements,

hileunder

n

unrestricted

ampling roced

the

highest ercentage

would

have been approximately 7 per

cent

duri

February,March, and April). The most frequentmonthof announcem

(October) represents

3.4

per

cent of the

announcements,

hich

s

on

slightly igher

han the

percentage hat

would be obtained under

a

co

pletely

uniform

istribution

hroughouthe

year 9.1 per cent).

One by-productf the data gatheringwas some insight nto the ti

lag

between

he

financial

tatement ate

and

the

announcement

ate

(s

Table 3). The median ag was 9 weeks,only 3 per cent

of

the announ

mentswere made by

the

end of

4

weeks,

and 93

per

cent

of

the

earni

had been reported y the end

of 13

weeks. A

possible

avenue

for

fut

researchwouldbe to studythe information

ontent

f

the

time

ag

its

(e.g.,

s bad

news

reported

ess

rapidly

han

good news?).

Definition

f

Variables. The

next step

was to

compute

the

follow

variablesfor achfirm n a weeklybasis forthe261 weeks fromJanua

1,

1961 to December31, 1965):


8/27

CONTENT OF

ANNUAL

EARNINGS ANNOUNCEMENTS

7

no.ofshares of firm

it=

traded

n

week

t

X

I

no.

of shares outstanding

no. of trading

forfirm

in

week t

days inweek

t

no. of sharestraded

for ll NYSE firms

VMt

in

week

t

I

no. ofshares outstanding

no. of trading

for ll NYSE firms days in weekt

in

week

t

it=

In

[Dit

+

P]

Rmt

=

In

(SP)~

L(SP)

t-1J

Dit

=

cash dividend

paid on

share of firm

in

weekt,

Pit = closingpricefor hare offirm at end of week t,

=

closingprice

at

end

of

week

t

-

1, adjusted

for

apital

chang

(e.g.,

stock

plits

and stockdividends),

(SP)

=

closing

alue of

Standard nd

Poor's

Price ndex at

end

of

week

(SP)

t-1

=

closing

alue

at

end

of

week

t

-

1.

Vit

is

a

weekly

verage

of

the

daily percentage

f sharestraded.Week

volume

was

divided

by

the

number f hares

outstanding

o that

the

resu

would not be

dominated

by

those

firms

with

the

largest

number

f

shar

outstanding. he percentage fsharestradedperweekwere thendivid

by the

number f tradingdays

in

order o adjust

forthe fact that

not

a

weeks

have the

same

number

f

tradingdays.

VMt

eflectshe

evel

of

volume

for ll NYSE

firms.

he

weighting

che

implicit

n this

volume

ndex

assignsgreater

weight

o

percentage

f

shar

traded

of

firmswith the

larger

number

f shares

outstanding.

While

t

feature

s not

entirely

atisfying,

ts

use

is defended n the

grounds

h

this ndex

s

much easier

to obtain

than

an

index that

assignsequal weig

to all firms nd because there s no reason to believethe use ofthis nd

leads

to either

n

upward

or a downward

ias

in

the

findings egarding

informationontent

f earnings eports.

Jit

is

the natural

ogarithm

f the

price

relative nd can

be viewed

as

measure

of

price

change

or as the

rate

of return f the

security

ssumi

continuous

compounding.12

Mt

is a similar

measure

for 425

indust

12

The

properties

f

Rit

are further

escribed

n

Fama, op. cit.;

Benjamin

F. Kin

Market

and

Industry

Factors

in

Stock

Price Behavior, Journal

of

Busine

XXXIX (January,

966), 139-90;James

H. Lorie

and

Lawrence

Fisher, Rates

Return n Investmentn Common tocks, Journal fBusiness,XXXVII (Janua

1964),

1-21.


9/27

74 WILLIAM

H.

BEAVER

NYSE firms. his statistichas some limitations s a market-widend

of pricechange and in many respects s less preferable

han some recen

developed ndexes,notably

Fisher's Link Relative.'3

However, again i

use is defended n thesame grounds s those for

he market-widendex

volume. The Fisher Link Relative has been computed

for monthlyda

only. To construct

similar ndex on a weekly

basis is a research roje

in

itself.Not only s the

S & P index easier to obtain but it was found

other tudiesthat resultswere nsensitive o

which ndex

s used.'4

With

thecontext f this study, here s no reason to

believe that the

use

of

t

S & P based indexwill ead to an overstatementr understatementf t

informationontent f earnings eports.

VolumeAnalysis-

Unadjusted

or

Market nfluences

Vjt

was

computed

or ach week t n the report eriodfor ach

of the 5

earnings nnouncement. The report eriod s defined

s the 17 weekperi

surrounding he announcement

ate (8 weeks

before he announcem

week,

and 8 weeks

after).

Then

the

[t

(averaging cross )

was

comput

for ach of the17weeks, nd theresults ppear nFigure1.The dotted i

denotes

the value of

Vt

n

the

nonreport eriod

i.e.,

that

portion

of t

261 weeksnot ncluded

n

the 17 week report eriods).

The evidence ndicates

ratherdramatic ncrease n volume n the a

nouncementweek (week

0). In fact,the mean volume n week 0 is 33 p

cent

larger

han

the

mean

volume

during

he

nonreport eriod,

nd

it

by

far the

largestvalue observedduring he 17

weeks. nvestorsdo

sh

portfolio ositions

t

the time

of

the

earningsnnouncement,

nd this

h

is consistentwith the contention hat earningsreportshave informat

content.

The contention

s

further upportedby the behavior

of

nvestors

n

t

other

weeks.

Eight

weeks

prior

to

the

announcement,

olume

is bel

normal,

which

uggests

hat investorsmay postpone

theirpurchases

sales of

the

security

ntil the earnings eport

s

released.

The four

wee

after

the

announcement,

hen the

annual

reports

re

received,

exhi

slightly

bove

normal

olume nd hence

permit

more

horough

valuati

of

the

earnings

ata.

The investorresponse ppears to be very rapid, for almost all of t

above-normal

ctivity

ccurs

during

week

0.

This

findingupports revi

studies

that

also

show

investors

respond quickly

(as

reflected

n

pri

changes)

to

new

pieces

of nformation

see

Fama,

et

al.).

Perhaps some

comment

s in

orderregarding

he

overall

evel

of

volu

throughout

he

year.

The

volume

tatistics

eported

n

Figure

1

are mul

13

For

a

discussion

f the S & P Index

vis-A-vis

isher's

Index, see Lawre

Fisher, Some New

StockMarket ndices, Journal fBusiness,

XXXIX (Janua

1966),191-225.

I4

Fama, et al.,

op. cit.


10/27

CONTENT

OF ANNUAL EARNINGS ANNOUNCEMENTS

plied by thefactor f 103.The averagevolume n thenonreport eriod

.00112-that is, the average

daily percentage

f sharestraded s

sligh

greater han

one-tenth f

one per centof the shares

outstanding. his

i

plies an annual

turnover f approximately

5 per cent

and a weekly u

overof 5 of

one percent.

f corporation has 10 million

hares utstandi

during normalweek 50,000

hareswill

be tradedwith n expected

olu

of66,667 haresduring he

earnings eportweek.

VolumeAnalysis-AdjustedforMarket nfluences

The section

willpresent n analysis

which ttempts

o remove heeff

ofmarket-wideventsupon

the individual

ecurity's olume.The

moti

tionfor he

analysis s two-fold.

1) It is possible hat

the abnormally

i

volumemay be caused

in part by market-wide ieces

of nformation

h

are released at the same

time as the

earnings nnouncements. ince

t

earnings

nnouncementsre released lmost

uniformly

hroughoutheye

this

is

not a very plausible

explanation

of the findings. evertheless,

movingthemarketwide effects hould allay any fearsthat this unlik

situationdoes

account forthe results.

2) More importantly,

he analy

will

serve

to reduce noise in the volume

data. Noise

is any moveme

in volume

due to unspecified actors,

ne of which s

market-wide ve

that would cause increases

n the volume.

Analysis

orNonreport

eriod. The followingmodel

was used to abstr

frommarket-wide

actors

15

Vit

=

ai

+

biVMt

+

eit.

Estimates

of

as

and

bi

were obtained

from inear

regressions

ased

up

observations

rom he

nonreport eriod.

The observations

rom

he

rep

period

weredeleted

from he

regression

ecause

f

earnings

nnounceme

have informationontent,

he assumptions

f the

classical

regression

o

are

violated

during

he

report eriod e.g.,E(eit)

-

0).

Some

summary

tatistics

elating

o

the

regressions

ppear

in Table

The mean volume of the

sample

firms

s

much higher

han

that

of t

market

ndex.One reason

s

the different eighting

cheme

mplicit

n

ea

measure.The marketndexassignsgreaterweight ofirms iththegrea

number f

sharesoutstanding.

f

these

firms ave lowervolume

expres

as

a

percentage

f shares

outstanding),

hen the market ndex would

expected

to

have a lower

mean.

Another

xplanation

s that the

sam

15

The

rationale

for

using

this

particular

model

is two-fold:

1)

It is

a

sim

relationship,

nd there s

no

obvious

reasonwhy

a

more

complex

model would

more

ppropriate. 2)

It

is

analogous

o the model

hatwill

be used

to

remove ff

ofmarket-widevents

upon

the

price hanges

f

ndividual

ecurities.

he

paper

later

ndicate hat uch

a

model eems

to

be

a

reasonable

way

to characterize

r

changes.Hence, twouldseemreasonable o assumea similar rocess s generat

volumeover

time s

well.


11/27

76

WILLIAM H. BEAVER

selection riterionmplicitly avored igher urnoverecurities. ut it is n

obviouswhythat shouldbe truenor

what mplication

t has for nferen

regardingnformationontent.

The average

correlation oefficient as low, mplying

hat removing

influence f VMt

hould have littleeffect pon the analysis. n spite of t

low association,

he sign of the correlation

oefficient as positivefor 1

firms

nd negative

for only 4. These two findings aken

together ugge

that the market

nfluence n an individual

firm's olume s significan

differentrom ero but that ts magnitude s small.16

The residual,

it,

is that portion

f an individual ecurity's

olumeth

cannotbe explained

by market-wide

vents s reflected

n

VMt The mea

of

es (averaging

cross

time for

given

firm

)

is

forced o be

zero

by

t

mechanics f the

regression omputations. owever, he

mean of et (ave

age across

firms

ora given week

t) may be nonzero.

An inspection

f

i

distribution or

the 261 weeks provides

some interesting nsights s

Figure2).

The distribution

s skewed o the right, s indicated

by the fact that

5

percentof t are negative nd 42 per centare positive.The medianof

is -.02 and its mean is zero (again

this must be true

because of the m

chanics of the

regression omputations).

The

ei's

are even more asy

metrical,with

64.6 per cent negative nd 35.4 per cent

positive.One inte

pretation f the

asymmetrys that

nformations provided o investors

discontinuous

lumps rather han smoothly

r

continuously

ver time.

Residual

Analysis or

the

Report

eriod.

The

residual,

jt,

was

comput

for ach week

t of

the report eriodfor

ach

of

the 506

earnings

nnoun

ments in the followingmanner:

ejt

=

Vjt

-

bVMt

_

I..,

5

t = 8,

...

+

where

i

and

bi

wereobtained

rom

he

regressions

n

the

nonreport eriod

Then

the

t

was

computed

or ach

of the 17

weeks,

nd

the

results

ppe

in

Figure 3.

A positive residual mplies

above normal volume; negati

below normal;

and zero,normal

volume.

The behavior

of the volume residual

s

the same

as

that of the

previo

analysis. There

is

a

large peak

in

week

0,

where

the mean volume

s

a

proximately 0

per cent higher

than

during

the nonreport eriod (i.e

.33/1.12,mean residual

n

week 0/mean

volume

n

the

nonreport erio

and

is

about

40

per

cent

higher

han the mean volume

n

the

weeks

pri

I6

The probability

hat the

expected

alue

of

he correlationoefficient

s

less

th

or

equal

to

zero

s less

than

1

chance

n

100,000.

17

Note

that the

ubscript

refers

o firm or

security,

but

refers

o

an

earnin

announcement.ence as andbimaybe useda maximumffive imes; tsfrequen

of

use

will

depend

upon

the number

f

earnings

nnouncements

f firm

or

securi

i

included

n

the

sample

of 506 announcements.


12/27

CONTENT

OF ANNUAL

EARNINGS

ANNOUNCEMENTS

to theannouncement. gainthe volumeduring heseweeks s abnorm

low, while slightly

bove

normalvolume

persists

orfourweeks

follo

the announcement

eek.The

interpretation

fthese

findingss

the sam

that of the previous

nalysis. n short,

he results

re veryconsistent

w

the contention

hat earnings

nnouncements

ossess

nformation

onten

Because a

comparison

f mean values

can

often e misleading,

wo

ad

tional

comparisons

were made

to see

how unusual is

an

it

of .33, w

was the value

observed n

week 0.

The first omparison

xamined

values of it in the reportperiodand those in the nonreport eriod (

Figure

2). Out of the

261 nonreport

eriodvalues

of

t,

only4 had val

exceeding 33.

Although

uch a

comparison

s

admittedly

crude appr

mation,

t does suggest

hat the

value in week

0 is unusually

high.

Moreover

this comparison

ends

to understate he

unusual

natur

the week

0 residual.The

it

during

he nonreport eriod

s

based upo

maximum f

143 observations

er

mean, while

the

it

in week

0 (as

as

the rest of

the report

eriod)

was based upon

506

observations.

i

the

eit's

are

less than

perfectlyorrelated,

he

dispersion f the

distribu

of

et

would decreaseas the numberof observations er mean increa

Hence,

if

the distribution

n

the nonreport

eriod

were also based

u

506 observations

er

mean,

ts

dispersion

would be smaller nd the

nu

of

values above

.33

would be fewer.

Anotherfactor eading

to an

un

statement

s thatet

in

the nonreport eriod

was based

upon residuals

a

from he same week,

while

the mean residual

n

week

0

was based

u

observations

aken

from

different eeks.

If

contemporaneous

esid

are more

highly orrelated

han

noncontemporaneous

esiduals and

evidencesuggeststhey are), then a distribution f it in the nonre

period

based

upon

noncontemporaneous

bservationswould

have

a

sma

dispersion

nd

fewer alues

above .33.18

The

major point

s the compar

indicates

hat the mean

residual

n

week 0

is unusuallyhigh,

n

spite

of

fact

that the

comparison

ends

to

understate

ow unusual t

really

s.

A second

comparison

nvolved

the

analysis

of the

frequency

f

posi

residuals

n each report eriod

week

as

compared

with the

numberdu

the

nonreport

eriod see

Figure4).

The

behavior f the

positive

resid

is consistent

with the previous

relationships

bserved

n

Figures

1

an

Prior to the announcement,he frequency f positiveresiduals s be

that of the

nonreport eriod,

while the

frequency

s

slightly

bove

nor

after he

announcement. y

far

the

argest

requency

ccurs

n week

0,

there

s

an extremely

mall

probability

hat

such a

high

number f

posi

residuals

could have

occurredby

chance.'9

This second

comparison

gests

the same inference

rawn rom he

first-namely,

he volume

n

w

0

is

an

unusuallyhigh

value.

In

sum,

the

behavior

of volume

unifo

18

The serial

correlation

s

reflected

n

the

positive

autocorrelation

oefficie

theresiduals seeTable 4). Another ndication s that thefour aluesofe excee

.33 occurred

n a

five-week

eriod.

19

The probabilitys

less

than

1

chance

n

100,000.


13/27

78

WILLIAM H. BEAVER

supportshe contentionhat earnings ave informationontent or ndi

ual investors.

In some

respects,

hesefindings o not reflect

he

entire

xtent o wh

activity

s above

normal

n

week

0. Not all of the earnings

nnouncem

of the

143 firmswere used-in

fact,only 506

out of a possible715.

The

week periods

urroundinghe remaining 09

are included

n the nonre

period.

This

will tendto induce bias against

earnings eports ince

volu

activity

s increased n the nonreport

eriod

by the inclusion f the

report

periods. The extentof

this bias could

be seriousbecause

one

the reasons

for

placing

a

report

n

the 209

group was the announce

of earnings

nd dividends

n

the

same

week which

would producee

moreprice nd volume

ctivity han

the 506announcements

tudied.

Ho

ever,

here re also

compensating

actors.Although

he activity n

wee

was above normal, he

activity n the weeks

priorwere

below normal

the

506

observations.

f

this tendsto

be

trueof the deleted

nnouncem

as

well,

the bias may

not be so

great.

f

the 209 observations

weredele

from he nonreport eriod,

o be completely

onsistent, ther ypes

of n

announcements ould also have to be deletedfor the same reasons.T

resultwould

be

virtually

no observations

n

the nonreport

eriod.

Si

the

nonreport eriod

does nclude hese

events,

t is

important

o stress

fact that

comparing

he

earnings

eport eriods

with the

nonreport

er

involves

comparison

f

the

informationontent f earnings

eportsw

the average

amountof information

eing

released during

he nonre

period.By necessity,

his

s a bias

againstearnings eports

incethe app

priate omparison

ould

be a nonreport eriod

with

no

informationt all

Price

Analysis-Adjustedfor

nfluence

fMarket-Wide

vents

If earnings eports

onvey

nformation

n the

sense of

eading

to

chan

in

the

equilibrium

alue

of the

current

market

price,

he

magnitude

f

price

change (without

respect

to

sign)

should

be

larger

n week 0 t

during

he

nonreport

eriod.

The

first

tep

n

making

his

prediction pe

tional

is

to remove

he effect f

market-wide

vents

upon

the indivi

security's

price

change.

The

reasons

for

wishing

o abstract from h

eventsare similar o those cited n the volumeanalysis.20he modelu

herewas first uggested

y

Sharpe,

nd

it

provided

he motivation

or

s

an

analogous

modelfor

volume.2'

he

Sharpe

model

states:

Rit

=

at +

biRMt

+

uit.

Rit

is a measureof

the

price

change

of

security

during

ime

period

,

a

RMt

is a measure

of

average price

change

during

ime

period

t

for

425

dustrial

NYSE firms.

Both variables were

defined arlier.

The

resid

20

See p.

75.

21

William

F.

Sharpe,

A

Simplified

Model forPortfolio

Analysis, Manage

Science,

X

(January,

963),

77-93.


14/27

CONTENT OF ANNUAL

EARNINGS ANNOUNCEMENTS

7

uit,

representshatportion fthe individual ecurity's ricechangeth

cannot be accounted

forby the effects f market-wide

vents as reflec

in

RMt

The Sharpe

model has been investigated y Fama

et

al.

and by Schol

and

was

helpful

n

abstracting

rom he influence f market-wide acto

King's studyof

monthly ricechangesfound hat, on

the average,31

p

cent of the variation

n an individual

security's rice

change can be

e

plained by market-wideactors s

reflectedn a market-wide

ndexof pri

change.22

or these reasons,

a

price

change analysis, unadjusted for t

influence f market-wide actors,was not conducted.The evidencew

later ndicate hat

f uch an analysis

had been conducted,he resultswou

be essentially

he same as those reported ere.

Since

the direction f the

price

change

cannot

be specified, knowle

of the investors'expectationmodel(s),

some

transformationf

uit

th

abstractsfrom

ts

sign,

s

needed.

One

such transformations the squa

of the

residual

i.e.,

ui

t).

If

earnings eports ossess

nformation

onte

2

b

U2 t

should

be

greater

uring

week

0 than

during

he

nonreport eriod.

T

mean of

U2t

during he nonreport eriod s simplythe variance of th

variable

s,2).23

The relationship etween

he

squared

residual

n week 0 and the avera

squared

residual

during

he

nonreport eriod

can

be

expressed

n

the

fo

of

the ratio,

Uit,

where he

numerator

s

uit

and the

denominator

s

si2.

the

ratio

s

greater

han

one,

the

residual

rice hange

s

larger

han

norm

and

conversely

or ratio

of

ess

than one. The

prediction

s

the

mean of

(averaging

cross

announcements)

ill

be

greater

han one

during

week

if

earnings eports ossess

nformationontent.

AnalysisofNonreporteriod.Estimatesofas,

bi,

and

s,2

wereobtain

from

egressions

ased

upon

the

nonreport eriod.

The

observations

r

the

report eriod

i.e.,

the

17

weeks

urrounding

ach

announcement)

e

deleted

from he

regression

ecause

if

earnings

have information

onte

the

assumptions

f the

classical

regression

model are violated

during

reportperiod e.g.,

the variance of the

residuals

during he reportperi

is not

equal

to the

variance

during

he

nonreport eriod).

Some

summary

tatistics

elating

o the

regressions

ppear

in

Table

The mean pricechanges endto be lowerfor he samplefirmshanfor

market

ndex.Since the

Rit

call

also

be

interpreted

s

a

rate

of

return,

lower returns

or the sample

firms

would suggest

hat

they are

less ris

22

Fama, et al., op.

cit.; Myron choles,

The Effects f Secondary

Distributi

upon theMarket Price

(paper presented

t the November, 967

session of

t

Conference

or he Studyof Security

ricesheld

at the Graduate chool of Busine

University

f

Chicago);

and King,op. cit.The percentage

efers o theperiod

Augu

1952

hrough ecember,

960.

23

The

variance

(j2

=

[

-

E(uj)]2.j2

is the estimate

f

yj2

computed

r

sample data.

Sz2

=

[Ze=i(uit) ]/T, where T = number of weekly observations f

the nonreport

eriodfor

ecurity .


15/27

80

WILLIAM H. BEAVER

than the firms omprising he ndex.An inspection f the distributionf

also lends support o that contention. harpe states that

bi

can be view

as an

operationalmeasureof a security's iskiness, ith argervalues of

implying reaterriskiness.24

bi

of one denotes a security f averag

riskiness. he average

bi

forthe sample firmss less than one (.89), whi

suggests hat the samplefirms re ess risky.However, he discussion n t

section n definitionf variables ndicated hat the definitionfRMt base

upon the S &

P

indexmay be subject to measurement rror.An errors

variablesmodel uggests hat measurement rror n the ndependent ari

ble, even if it has a zero expectation,will induce a downward ias in t

estimates of

the regression

oefficientssociated

with the

independe

variable (i.e.,

bi).25

Effortswere undertaken o assess the extent of t

downward ias by computing

i

forthe sample firms, singmonthly a

and Fisher'sLink Relative as a definitionfRMt

.

The median

bi

was .99

suggesting he sample

firms

re of average riskiness elative to NYS

firms i.e., the firms hat comprise he Fisher ndex).

On

the average, the associationbetween

Rit

and

RMt

was low.

Only

percent ofthe variation nRit can be explained by the variation n

R

as

measuredby the square

of

the average correlation

oefficient.

he

i

plication s two-fold: 1) Removing he influence f

RMt

should have lit

effect

pon

the

results,

elative

to what would

have

been

obtained

f

M

were analyzed rather

han

uit.

(2)

The

explanatory ower

s

much

ow

than

that obtainedby King, suggesting

hat

eitherweekly

data have mo

noise than monthly ata or that

RMt was not

properly efined,

r

bot

The presence f either actor

will

make

t

more

difficulto

detect ny pri

effects

f

the

earnings eports.

The distribution f UC (averaging across 143 firms,

=

2, ,261

during he nonreport eriod

s

shown

n

Figure

5.

It will

be used

as

a

bas

for

ssessing he significance

f

the

Ut's

observed

uring

he

report eriod

Price Residual Analysisfor Report eriod. The residual,

ujt,

was

co

puted

for

ach week

t

of the report eriod

and

for

ach

of the

506

earni

announcements

in

the

following

manner:

i=

1,***,

14

ujt==

Rjt-aa-bi-Mi

j=

1, ***,506

t

=-8,

**,+8.

The residualwas then quared

and divided

by

the variance

of the residu

for

ts firm

uring

he

nonreport eriod,

s follows:

24William

.

Sharpe,

Capital

Asset

Prices:

A

Theory

of Market

Equilibri

under

Conditions f Risk,

Journal f Finance,

XIX (September,

964), 25-42.

25

J. Johnston,

conometric

ethods New

York: McGraw-Hill,

963),148ff.

26

The distribution

s skewed

to

the right.

One explanation

orthis phenome

is the

eptokurtic ature f

theunderlying

it's

(see Fama,

op.

cit.).

The

distribut

ofust s also skewed n the samedirection. lthough he meanof

u~t

s onefor ea

security

uring he

nonreporteriod,

nly26 per

centof theobservations

xceed

on


16/27

CONTENT OF ANNUAL EARNINGS ANNOUNCEMENTS 8

i-= 1,.. , 14

Ujt

=

u

j

,t

,

50

t

--8

...

,+8.

U,

(averaging cross )

was

computed or

ach

of the

17

weeksof the repo

period, nd the results ppear

in

Figure

6.

The magnitude f the price hanges

n

week0

is

much arger 67 per ce

higher) han the average during he nonreport eriod. The above nor

price activity

s

what would be expected

f

changes

n

equilibrium ric

are more ikelyto occur whenearnings eportswerereleased, nd hen

the evidence

s

very

consistentwith

earnings eports ossessing

nfor

tional

value.

Although

he

price activity

s

highest

n

week

0,

the next

argest

valu

occur

n

the weeks mmediately ontingent

o week 0.

Price

changes a

above average

n

the

week

mmediately rior

o the

announcement,

hi

may reflectnformationeakage

or the fact that the Wall

StreetJour

was not the first ource

o

report

he

earnings

n

some

cases.

Above nor

activity

s also

present

or woweeks fter he

announcement,uring

whi

time

he annual

reports

rereleased nd are evaluated

by

nvestors.

The below price activity

n

weeks

-8

through

2

is

open

to at

lea

two

interpretations:1)

There is a below normal amount of

informat

coming

nto the

market t

this time.

2)

The

below normal

price activi

is

a result of

the below

normal

volume also

observed

during

the

sa

period.

More

will be said about

both

(1)

and

(2)

later.

The behavior

f the mean residual,

t

,

also indicates

greater rice

cti

ity

n

week

0

(see

Table

6).

The mean

n

week

0

is

.00500,

which s

the

arg

value observedduring he17 weeksand is four imes arger han the ave

age

value of

Rit

during

he

nonreport eriod (.00125,

see Table

5).

T

means give

the

impression

hat serial correlation

may

be

present n

t

data.

However,

he

average

utocorrelation

f the

price

residualswas

qui

low

(-.08) during

he

reportperiod.

The

low

degree

of

autocorrelat

supports

he similar

indings

f Fama

and

his

conclusion

hat

the mar

moves to new equilibrium ositionsquickly.27

urther

videnceof this

reflected

n

the factthat the

bulk of the

price

reaction oes

occur

n

wee

(see Figure6).

The low autocorrelation

lso

suggests

hat

the

price han

were permanent

n

nature

and

were

not reversed

n

subsequent

weeks.

fact, the autocorrelation

f the

residuals

n the

weeks

mmediately

ft

the announcement eek

was

slightly ositive.28

Two additional comparisons analogous

to those made

in

the volu

analysis)wereconducted

o

see

how unusual

an

Ut

of

1.67

s.

The first

o

parison

examined

UO

n

the

nonreport eriod (see Figure 5).

Out of

2

values,

only

11

exceeded 1.67.

The

comparison uggests

hat

the

price

a

27

Fama,

op.

cit.

28

The autocorrelation as examinedon a week-by-week,ross-sectional asi

i.e.,

o

=

-=i

(ejtejetA)1/[Z'0

(eit)2],

t

=

-8, *.,

+8.


17/27

82 WILLIAM H. BEAVER

tivity n week 0

is

unusuallyhigh, n spite of the fact that such a com

son tends to understate ow unusual t really

s.29

The second compa

examined he frequency f

Up's

larger han one relative o the frequ

that occurred uring he nonreport eriod see Figure 7). The frequ

of values above one

is

greatest n week 0, with the next highest alue

curring

n

the weeks adjacent to the announcement eek. There s an

tremelymallprobability hat such a high number 181 in week 0) c

have occurred y chance.30 he interpretations the same as that of

mean analysis-namely,there

s

above normal rice ctivitywhen ar

reports re released.What this analysisreveals hat the mean analysis

not is the fact that the abnormally ighmean is not caused by a fe

servationsdominating he resultsbut ratherby a substantialpropo

of the

sample

data.

In

summary,

he

behaviorof the price changes uniformlyupport

contention

hat

earningsreportspossess information ontent.Obser

a

price reaction

s

well

as a

volume reaction ndicates

that not onl

expectations

f ndividual nvestors

lteredby

the

earnings eport ut

the

expectations

f

the market s a

whole,

as

reflected

n

the chang

equilibrium prices.

Relationship

etween

he

Volume nd

the

Price

Findings.

The

pre

sentence aises

the

issue, how much

of

the

ncreased riceactivity a

attributedmerely

o the fact

that

there

s

more action'

in

the

secu

rather han to changes

n

equilibrium rices?

One

way

to

approach

this

question

s

to view

the

price change du

a

given

time

period

s

a

sum of

pricechanges

on

each transaction ha

curred uring

hat

period.

n

a worldof

uncertainty,

he

pricechange

each transaction an be treated s an observation rom probabilit

tribution

f the investor's ssessment

f what the

price change

shoul

The

price change per period, hen,

s

a

sum

of randomvariables.

f

t

actions occur

as

if

they

are

independent

ver time

(evidence

on

d

weekly,

nd

monthly rice changes suggest hey do),

the variance

o

weeldy price change

will

increase

n

direct

proportion

o the numb

transactions

hat

occur

during

he time

period.3

29

The reasons orunderstatementre similar o those

tated n thevolume

sis. See p. 77.

30 The probability s less than

1

chance

n

100,000.

31

The evidenceregarding erial correlation f daily and monthly rice cha

can be found

n

Fama, op. cit.

and

Fama,

et

al., op. cit.,

respectively.

he

ave

autocorrelation

oefficientor

weekly hanges

n

this amplewas

--.08,

which

w

cause the variance

o increase ess than

proportionately

ith he number f tra

tions. Within given rading ay, the autocorrelation ay be higher e.g., bec

of certain nstitutional

actors,

uch

as

clustering

f

imit

rders

r

stop

oss

ord

However, he existence f arbitragershouldprevent he autocorrelationrom

very arge. n order or heprice ctivity

o be

explained ntirely y

ncreased

action activity,the

autocorrelation

ould

have

to

be one. This

would

be hi

unlikely ecause of theempirical vidence itedand the opportunitiesor rbit


18/27

CONTENT OF

ANNUAL EARNINGS

ANNOUNCEMENTS

8

The issue now is what

is the

appropriatemeasure

of the number

o

transactions ccurring uring given period. f the volume s used as

measure,

hen

Ut

in week

0

would

be expected

o be

1.30

merely

ecau

of more ction

n the

security. he remaining

ortion

would be attribut

to changes

n the equilibrium

rices of

the securities.

However,

t is n

at all

clear

that volume or

even number

f transactions)s

the appropria

measure,

ecause

t reflectsnly

the explicit

ransactionshat

occur.

It

could

be argued,

with considerable upport

fromeconomic

theor

that the expectations

f all investors nfluence hemarket

price,

wheth

ornotthey ngage na purchase ra sale. If themarket cts n thismanne

the

total number

of

transactions, xplicit

nd

implicit, re

the same pe

timeperiod.

Hence all

of the above

averageprice ctivity

an

be

attribut

to

changes

n

equilibrium

rices.

Additional

mpirical esearch

s

needed

before his ssue

will

be

resolve

The

researchwould consist

of

studyingncreased

volume

activitydue t

reasonsother

han

nformationoming nto

the

market.An initial

nalys

of the seasonal

variation

n

volume

VMt)

from

946

through 966

reveal

that the

volume

s

greatest

uring he

monthsDecember

nd January. h

explanation eemsto stem from ax considerations ather han an abov

normal

low f

nformation.

esearch

also

indicated

hat

the

price

variabi

ity ofRMt

during hese

months i.e.,

Ut)

was only 996, ndicating

o abov

average price

variability uring

hesemonths.

This

finding

ends

suppo

to

the position

hat

none of

the

price

activity

n

week

0

is

due merely

more

motion.

Before

eaving

this topic,

note that solating he

volume effects

n

pri

changes

s

of concern

nly

to the extent ne

wishes o

distinguish

etwe

informationhataltersthe expectations f themarket s a wholefrom

formation

hat

alters

only

the

expectations

f

individual

nvestors.

All

the

price

activity

an be

attributed o information

n the atter

ense.

Frequency

f

Other

News

Announcements

uringReport

eriod

The purpose

of

this

analysis

was to

discover

f

therewas any clusteri

of

other

news

announcements

round

week

0

that

might

possibly

ccou

for he

volume and

price

reactions.

As indicated

arlier,

he

sample

desi

excluded

ny

firms

hat announced

dividendsn the same

week as

earnin

or

any

firms hat

split

their

tock

during

he

report eriod.

However,

t

i

conceivable

hat

dividends

nnouncements

might

luster

n

weeks

mme

atelyprior

o and

afterweek

0

or thatother

ypes

of announcements

e.g

management

arnings orecasts)

might

luster

n week

0.

To examine

h

possibility,

he occurrence

f

othernews

announcements

n the Wall

Str

Journal

uring

he 506

report eriods

was

examined

see

Table

7).

By

far

the

most

frequent ype

of

announcement

was

dividends,

whi

exceeded hefrequencyf all othertypesof announcementsy a factor


19/27

84

WILLIAM

H. BEAVER

9 to 1. Withrespect o

the purpose f thisanalysis, here s no clusterin

dividend nnouncementsnweeks

-1

or +1; infactthe opposite eemst

be true.Also there s no

clustering f any other ype

of announcementa

any time during heperiod, ncludingweek 0. The

volume and pricerea

tion n week

0

does not

appear to be attributableo the clustering f oth

news announcements.32

Suggestionsor

FutureResearch

The dramaticprice

and volumereaction ndicates hat nvestors o loo

directly t reported arnings nd do not use othervariables o the exclusi

of

reported arnings.

he evidence lso indicates

hat news announceme

occurring rior

o

the

earnings eport

o not

entirely

reempt he nfor

tion contentof reported arnings.Given these

findings, ne of the

fi

extensions

f

the study will be to explorethe possibility

f construct

expectations

models that

will

permit

a

prediction f the direction

n

magnitude

f

the price residual.

The resultsof a recent tudy by Ball and

Brown n this area are ver

encouraging.33hey used an earningsmodelsimilar n form o the pri

and

volume

modelsdescribed

n

this

tudy e.g.,

changes

n

the

earnings

an

individual

ecurity

ereviewed

s

a linearfunction

f

market-wide

nd

of

earnings hanges).

The

sample

was divided

nto

two

groups:

nstanc

where he earnings

esidualwas

positive actual

earningswerehigher

ha

expected )

and

instances

where

he

earnings

esidual

was

negative actu

earnings

ower than

expected ).

The behaviorof the

price

residualsf

these

two

groups

was

examined,

nd the

findings

ere: 1)

The

sign

of

t

cumulative

price

residual

summed

over

a

12

month

period ncluding

announcementmonth)was highly ssociatedwiththesignoftheearnin

residual. 2) There

was

a

persistent pward

drift

n

the

cumulativemea

price

residuals

or

he

positive arnings

esidual

group.

This drift

tarted

monthsprior

o

the earnings nnouncement,

nd

over

90

per

cent

of

t

drift

ad

taken

place

by

the

beginning

f

the

announcement

month.Th

negative arnings roup

xhibited

n

analogous

behavior

pattern.

The

findings

ndicate

hat

reported arnings

re associated

with

underl

ing events

that are

perceived

by investors o

affect he marketprice.Be

cause earliernewsannouncementsonvey ome of thesame informatioa

the

earnings eports,

nvestors re

able to

use this information

o revi

theirforecasts

f

earnings

nd to

adjust

the

price accordingly.

n

fact,b

the

beginning

f the

announcement

month,

nvestors orm

argely

unbias

forecasts f

reported

arnings,

ven

though

he

reported arnings

re

abov

32

As measured

n

terms

f

number f

news announcementser week, the

flow

informationuring he

weeksprior o the announcement

oes not appearto be belo

normal nd hence

wouldnot account or hebelow

normal

rice

ctivity uring

wee

-2 through 8.

33

Ray Ball and Philip Brown, An EmpiricalEvaluation of Accountingnco

Numbers, Journal

of AccountingResearch, 6 (Autumn, 1968),

pp. 159-78.


20/27

CONTENT

OF ANNUAL EARNINGS

ANNOUNCEMENTS

or belownormalrelative o theirhistorical elationshipwithmarket-

earnings.

Although

he forecasts re unbiased, they

are not very

efficient,o

theywere, herewouldbe no

volumeor pricereactionwhen arnings

ep

were released.34 he Ball and

Brown findingsnd the findings rese

here are mutually

upportive

with respectto the information

onten

earningsreports nd also

are uniformly onsistent

with the findin

previous tudies

n the behavior f security

rices.One extension

f the

search

presented

ere

will

be to replicate he

Ball and Brown

tudyon

sampleofnon-12/31irmstheBall and Brown tudydealt exclusively

12/31firms) nd then to attempt

o predict

he magnitude, s well as

sign,of thepriceresidual.

A

second

area of furtheresearch s the application

f this

methodo

to othertypesof news announcements.

t

an earliermeeting f the

C

ference,

Green

and

Segall explored

he informationontent

f interi

ports.An analysis fvolume

nd price hanges

during he announceme

interim arningswould provide

differentpproach

o this ame ssue.

informationontent f dividend nnouncementss another opic that

receivedmuch

ttention ndstill s in need of

additional mpirical

nvest

tion.

Such

research

will indicate the importance f annual

earnings

nouncements

elative o otherkindsof nformation.

Perhaps

the

most important

xtension f this study would

be deal

with he

normativessue, Should

decision

makers erceive arnings ep

to

possess nformationalalue?

The normative

uestion anbe approac

by selecting

n event

of nterest o decisionmakers preferably

s fre

possible

from

he

influence

f their

perceptions)

nd

by investigatin

ability f arnings ata topredict hatevent.A few tudies fthistypeh

been

presented

t earliermeetings

f the Conference,

ut muchmorew

is

needed

n

this area.85Hopefully,

he findings resented ere

with

res

to

the

positive

question

will

provide greater

nsight nto

the

norma

issue as well.

34

The distinction

etween

nbiasednessnd efficiencyas

discussed n footno

35

James0. Horrigan,

The Determination

f Long-Term redit Standing

Financial Ratios,

Empirical

ResearchnAccounting:elected tudies, 966, up

ment to Vol.

4, Journalof

Accounting esearch, p. 44-62,

and

William

Bea

FinancialRatios as Predictors f Failure, ibid, pp. 71-102.


21/27

86

WILLIAM H. BEAVER

TABLE

1

Effect

fSelection

riteria

pon Sample

Size

Criteria

No.

of

firms

Compustat

irms

step

1)a.896

Less:

12/31

irms

599

Non-12/31 irmsstep

2)

297

Less:

Non-NYSE

firms

. .55

NYSE and non-12/31

step

3)

.242

Less:

More

than 20 announcements

er

year...

48

Dividends

n

earnings

nnouncement eek................39

Stock

split

during eport eriod.

7

Otherb........................................ ...................5

9

Sample

size

(step

4)

..143

a Sample criteriawere appliedsequentiallyn four tages.The samplesize aft

each

stage

s denoted

by parenthetical

omment

e.g.,

steps 1, etc.).

b

Miscellaneous

reasons

such as firm's

arningswere

not

reported

n

Wall Stre

Journal.

TABLE

2

DistributionfFinancial Statement

nd

Announcement

ates

Pecntage

f

times

ari

Month

Percentage

ffirms hose iscal

Percents wre

arning

year ended n each month

in

eachmonth

January

... .

....................

.0

7.5

February

........................

6.3 2.3

March.....

.

7.8

2.8

April

.........................

6.3

5.0

May.

1.4

8.7

June

.... .

....................

3.8

6.5

July

.........................

9.6

6.8

August.

7.8 11.3

September.

15.3

11.9

October. .... 9.1 13.4

November

.......................

5.6

12.3

December.

..

0.0

11.5

Total............................100.0

100.0

a

Total

number

f

firms

quals

143,

nd total

number

f

nnouncements

quals 50


22/27

CONTENT

OF ANNUAL EARNINGS

ANNOUNCEMENTS

TABLE 3

Number f

Weeks

etween iscal Year-End

nd Date

of

Announcement

No. of

weeks

Percentagef

announcements

Cumulative ercentage

Less

than

4 1.7

1.7

4

1.5

3.2

5

4.1

7.3

6

11.6

18.9

7

14.0

32.9

8

13.8

46.7

9 11.2 57.9

10

11.0

68.9

11

8.6

77.5

12

8.6

86.1

13

6.9

93.0

14

3.0 96.0

15

2.2

98.2

More than

15

1.8

100.0

Totala

100.0

a

Total

number

f

announcements

s

506.

TABLE

4

Summary f

Regression

tatisticsVolume

Analysis

No. of obser-

Mean

of

depend-

Meanof

inde-

Autocorrelat

Item fvations

er

ent variable

pendent

ariable

Correlation

coefficientf

tem

~~firm

n non-

-coefficient

coefficient

report eriod

(Vi)

x

lo0

(Vi)

X 10lrsdul

Fractile

.10

165

.33

.577 .06

.21

.25

176

.53 .583

.16

.29

.50

193

.88

.588 .28

.39

.75

210

1.56

.595 .39

.50

.90

227 2.36

.608

.46

.62

TABLE

5

Summary

fRegression

tatistics

rice

Analysis

No. of obser-

Mean of

depend-

Mean of inde-

Regression

oef-

Correlati

Item

~~vations

er

ent

variable

pendetvraltem

~~firm

n

non-

-

etaibeficient of

Rmt

coefficie

report

eriod

(Ri)

X

108

(Rm)

X

10'

Mean

187

1.25

1.73

.89

.26

Fractile

.10

165

-2.13

.96

.42

.13

.25

176 -.26

1.25

.62

.22

.50

193

1.51

1.51

.87

.27

.75 210 2.88 2.04 1.13 .32

.90

227

3.98

2.96

1.44 .37


23/27

88

WILLIAM H.

BEAVER

TABLE 6

Analysis f

Mean

Price

Residual

Week

Mean

residual

. .

~~~~~~~~(25iz6

uitIS06)

-8 .00183

-7

- .00105

-6

- .00029

-5 -

.00064

-4

-

.00096

-3

.00019

-2

-

.00047

-1 .00229

0

.00500

1

.00204

2 .00163

3 .00120

4 .00109

5 .00354

6

-

.00040

7

.00257

8

.00343

TABLE

7

Occurrence

f

Other

ews Announcements

No

of dividend

No. of

all other

Week

announcements

types

f

~~~~announcements

-4

43 3

-3 39 2

-2 42

4

-1

16 5

0

0

4

1

16

4

2 33 4

3

32

3

4 41

2

Total 262

31


24/27

CONTENT

OF

ANNUAL

EARNINGS

ANNOUNCEMENTS

Vt

1O

L5

,

=2;6

(

/506,

here

=-8,**.,

+8.

---Average

Ft

X

103

during

on-

g

i~~~~l

a

I I

~~~~report period

1.12.

L4

1.2

1.0-

0.9'

-8

-6

-4

-2

0 +2

+4

+6

+9

Weeks

fter

nnouncement

FIG. 1. Volume

Analysis

Relative

frequency

et1

C /143,=1,, 261

oi8

ssTil=

-a

-

biVt

@

.14

.10

.06

1

observation

I

.02

-.40

-.30 -.20

-.10

0

.10

.20 .30

.40

Value

f

,

FIG.

2. Distribution

of

et

in

the

Nonreport

Period


25/27

90

WILLIAM H. BEAVER

et

X

l03

.40

/

6

.30 e,

j62j

26)

506,

wheret

-8,,

+8 -Mean

j,

X 10' during non

=,

i

-

report

period=

0.

.20

.10

-.10

-.20

-8

-6 -4 -2

0 +2 +4 +6 +8

Week after nnouncement

FIG. 3. Residual

Volume

Analysis

No.

of

Vejts

260

-Expected

no.

of

positive

epys

based on relative

frequency

n

240

nonreport eriod.

220

200

180

s _

160

-8

-6

-4 -2

0

+2

+4

+6 +8

Weeks

FIG. 4. Frequency fPositiveeit's-Residual VolumeAnalysis


26/27

CONTENT OF

ANNUAL EARNINGS

ANNOUNCEMENTS

Relative

frequency

12

.10X

.08:

.06

.04

.02

.5 bservati

0.4

0.6 0.8

1.0

1.2

_

1.4 1.6

1.

2.0

2

Valueof

U,

FIG. 5.

Documents

Beaver WH - The Information Content of Annual Earnings Annou