Case study
Paper details
Chapter 5 of the Textbook, Questions and Problems #9 (pp. 178-180). In answering Part d, please skim Kim and Verrecchia (1991) and apply its main arguments/results to supporting your response/reasoning. At least 300 words, double-space, 12 pt times roman, at least 1 inch
Trading Volume and Price Reactions to Public Announcements
Author(s): Oliver Kim and Robert E. Verrecchia
Source: Journal of Accounting Research, Vol. 29, No. 2 (Autumn, 1991), pp. 302-321
Published by: Wiley on behalf of Accounting Research Center, Booth School of Business,
University of Chicago
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Journal of Accounting Research
Vol. 29 No. 2 Autumn 1991
Printed in U.S.A.
Trading Volume and Price
Reactions to Public
Announcements
OLIVER KIM* AND ROBERT E. VERRECCHIAt
1. Introduction
The purpose of this study is to investigate theoretically how the price
and volume reactions to a public announcement are related to each other,
to the announcement's characteristics, and to the traders' beliefs at the
time of the announcement. Among many possible sources of (abnormal)
trading volume at the time of a public announcement, our emphasis in
this study is on differences in the quality of preannouncement informa-
tion. The study uses a two-period rational expectations model. Traders
achieve their optimal portfolios prior to the announcement by trading on
what each knows in the preannouncement period. The public announce-
ment changes traders' beliefs and induces them to engage in a new round
of trade. It is assumed that traders are diversely informed and differ in
the precision of their private prior information; they therefore respond
differently to the announcement, and this leads to positive volume.
We obtain three results. First, the price change at the time of an-
nouncement is proportional to both the unexpected portion of the an-
nouncement and its relative importance across the posterior beliefs of
traders. This relative importance is increasing in the precision of the
announcement and decreasing in the precision of the preannouncement
information.
* University of California, Los Angeles; tUniversity of Pennsylvania. We gratefully
acknowledge the comments of Bob Holthausen, Prem Jain, Rich Lambert, Bharat Sarath,
Scott Stickel, and the workshop participants at Berkeley, Columbia, University of Michigan,
University of Minnesota, M.I.T., Northwestern, University of Pittsburgh, University of
Rochester, UCLA, Washington, and Yale. We also thank an anonymous referee for many
helpful suggestions.
302
Copyright ?, Journal of Accounting Research 1991
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TRADING VOLUME AND PRICE REACTIONS 303
The second and main result is that trading volume is proportional to
both the absolute price change and a measure of differential precision
across traders. Price change, as Beaver [1968] points out, reflects the
average change in traders' beliefs due to the announcement, whereas
trading volume reflects traders' idiosyncratic reactions. In this study the
different reactions of traders .are caused by differing precisions of their
private information. The newly announced information is relatively more
important to traders with less precise private information and thus has
a larger impact on their beliefs. Volume reflects the sum of differences
in traders' reactions; the change in price measures only the average
reaction. As a result, volume is proportional both to price change and to
the degree of differential precision. If precision is unobservable, the first
and the second results together suggest that trading volume may be a
noisier indicator of the precision of the announcement, or the precision
of the preannouncement information, than price change. Also, this result
is consistent with the empirical findings that abnormal volume is posi-
tively correlated with absolute abnormal returns.
The third result is a generalization of Holthausen and Verrecchia
[1988], who analyze price changes at public announcements in a two-
period model. In their model investors do not possess private information
and thus have homogeneous beliefs. They show that the price reaction
to an announcement is, on average, increasing in its precision and
decreasing in the amount of preannouncement information.! We show
that the expected volume and the variance of price change are increasing
functions of the precision of the announced information and decreasing
functions of the amount of preannouncement public and private infor-
mation. Therefore, the intuition and results of Holthausen and Verrec-
chia [1988] concerning price reaction extend to volume even when
investors are informed diversely and with different precisions.
In related research, Pfleiderer [1984] and Holthausen and Verrecchia
[1990] consider volume that arises due to differences in interpreting the
announcement across traders.2 Grundy and McNichols [1989] analyze
volume arising from the correction of idiosyncratic errors induced by the
revelation of information through prices.3 Varian [1985] considers volume
due to differences in prior beliefs.4
Our model should not be interpreted too broadly, although it provides
'Since traders have homogeneous beliefs, no trade occurs.
2 See Indjejikian [1991] for an extension of this idea.
'Other rational expectations models that employ a two-period trading structure include
Brown and Jennings [1987] and Krishnan [1987].
'We mentioned only those studies using Grossman-type rational expectations models.
Studies which assume different market structures include Kyle [1985], Glosten and Milgrom
[1985], Karpoff [1986], and Admati and Pfleiderer [1988]. Also, see Tauchen and Pitts
[1983] and Karpoff [1987] for the relation between volume and price change not explicitly
related to the arrival of new information and its properties, and Verrecchia [1981] for a
discussion of what inferences can be drawn from volume.
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304 JOURNAL OF ACCOUNTING RESEARCH, AUTUMN 1991
insights into how public announcements affect price changes and volume
through differing precisions in private prior information. For example,
we abstract from trading based on liquidity considerations, portfolio
rebalancing, tax effects, etc. We also assume that firms are cross-section-
ally independent. In the empirical domain, it is necessary to control for
these phenomena in assessing the effect of a public announcement on
price changes and volume.
Section 2 describes the model and obtains market equilibrium. Section
3 contains the main results of the paper concerning the market reaction
to public announcements. Section 4 summarizes our work with conclud-
ing remarks.
2. The Model and Market Equilibrium
The securities market model we suggest is one of pure exchange, a
continuum of traders, and three time periods, referred to as periods 1, 2,
and 3. Trading occurs in periods 1 and 2 and consumption in period 3.
There are two assets in the economy, a risky asset and a riskless bond.
One unit of riskless bond pays off one unit of consumption good in period
3. The return of the risky asset is a random variable, denoted by it, and
is realized in period 3. It is assumed that Ct is normally distributed with
mean d and precision (inverse of variance) h.
Four events occur in period 1. First, trader i, i E [0, 1], is endowed
with Ei riskless bond and xi risky asset.5 The aggregate risky endowment,
denoted by x - J xi di, is not known to individual traders and is normally
distributed with mean 0 and precision t.6 The randomness of the risky
asset supply captures the fact that securities markets are generally subject
to random demand and supply fluctuations arising from changing liquid-
ity needs, weather, political situations, etc. In noisy rational expectations
models this randomness serves as an additional source of uncertainty
that prevents securities prices from revealing fully all private informa-
tion; this, in turn, supports incentives to acquire costly private informa-
tion.7
Second, all traders observe a public signal Ct = i + 7j, where j is
normally distributed with mean 0 and precision m. Third, trader i
observes a private signal zi = ii + si where si is independently and normally
distributed with mean 0 and precision si. It is assumed that the set IsiI
is uniformly bounded. Together with prior beliefs of Ct, the signals 5, and
zi represent the preannouncement public and private information, re-
spectively, possessed by traders. The final event in period 1 is that the
5'Assuming a [0, 1] continuum of traders is convenient because sums over traders are
averages as well. The results of the paper are not affected by assuming a countably infinite
number of traders, i.e., i = 1, 2, *- .
6Assuming a nonzero mean of x does not affect the results.
'See Grossman and Stiglitz [1980] and Diamond and Verrecchia [1981] for detailed
discussions of the role of noise.
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TRADING VOLUME AND PRICE REACTIONS 305
market opens and traders buy and sell securities at the competitive
market prices.
In period 2 there is a public announcement of a signal h2 = C + v,
where v is normally distributed with mean 0 and precision n. It is assumed
that all random variables are mutually independent.8 We study the
market reaction to the announcement of 52 in period 2. The market
opens again in period 2 and there is another round of trading. In period
3 the return of the risky asset is realized and consumption occurs.
Traders are risk averse and their preferences can be represented
by negative exponential utility functions with risk tolerance ri, i.e.,
Ui(WL) = -exp(- (Wi/ri). Trader i's final wealth Wi can be written as
Wi = Ei + P1xi + (P2 - P,)Dli + (CZ - P2)D2i, where P1 and P2 are the
prices of the risky asset in periods 1 and 2, and D1i and D2, are trader i's
holding of the risky asset at the end of periods 1 and 2, respectively. It
is assumed that the set Ir- } is uniformly bounded.9
Traders are heterogeneous in terms of risk tolerances (ri) and they
differ in terms of their private information in period 1 (i,) and its
precision (se). Thus, we model the simple observation that some traders
are better informed than others and hold different expectations. This
difference in information quality plays a central role in the trading
volume reaction to public announcements analyzed later in the paper.
After observing available signals, traders also condition on the market
price of the risky asset when choosing their demand. Each trader realizes
that the prices for risky securities in the two trading periods, P1 and P2,
(potentially) reflect the information held by other traders. In a rational
expectations equilibrium, traders make self-fulfilling conjectures about
the relation between prices and traders information.
Let a linear conjecture of P1 and P2 be written as:
Pi = a, 4 + 0'S, + ,f J i di - 1ix
1~~~~~~~~~~1 = a, d + 0J,1 + 01 (Ct + si) di - ylx(1
= a1&z + OJ, + O3ii - -yix
and, similarly:
P2 = ac2u + 02151 + 0252 + /2a - y2x, (2)
8Assuming correlation between the error in the preannouncement public information,
51, and that of the second-period announcement, 52, does not qualitatively change the
results.
9The uniform boundedness of {sid and {ri} is assumed to have a well-defined integral
f risi di.
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306 0. KIM AND R. E. VERRECCHIA
where (1) follows from the law of large numbers and the independence
of the sis. P1 and P2 are linear functions of the average of the signals
available at the time of trading and of the supply noise. P1 is also an
available signal in period 2; expression (2) implicitly contains P1 because
it contains all the variables of which P1 is a linear function, and because
no restrictions are imposed on the coefficients. The constant terms of
the two equations are written without loss of generality as multiples
of d.
Given the conjectured behavior of prices outlined in (1) and (2), trader
i's problem is to choose the amount of the risky asset to hold at the end
of periods 1 and 2. As in most dynamic programming problems, first the
period 2 problem is analyzed and folded back into the period 1 problem.
In period 2 trader i's information consists of the first-period public signal
5i and his private signal Zi, the second-period public signal 52, and the
two price signals P1 and P2. These signals can be written in normalized
forms as t = u + It, 52 = at + i, ii = Ct + i, and:
q1-: (Pi - aid - J =t u-Bli, (3)
1
42 - P2 - a2d - 02J1 02h) == U- Bx (4)
/2
and the signals have precision (of error terms) m, n, si, t/B12, and t/B22,
respectively, where B1 yi/01 and B2 Y2/32. The information set
Y2h i, 41, l2} is equivalent to IS1, 52, it, P1, P21 because one can be
generated from the other.
There are two possible types of equilibria in this market. In one,
traders expect that the two prices fully reveal all private information and
these expectations are fulfilled. In the other, equilibrium prices are not
fully revealing.
To explain the fully-revealing equilibrium, suppose that traders con-
jecture that B1 $ B2. Then, from (3) and (4), Ci = (B241 - B1,2)/(B2 -
B1). Since q1 and q2 are known in period 2, Ci is also known. Once the
return of the risky asset is perfectly revealed, the equilibrium price, P2,
must equal the return, u.10 At P2 = Ct, traders have no incentive to trade
(or not to trade). In period 1 traders know that the risky return will be
revealed in period 2, and thus the equilibrium in period 1 is the same as
that in the one-period model of Hellwig [1980] and others. As a result,
the market price reacts to the announcement in period 2 and volume is
indeterminate in the sense that any level of trading volume (including
10 Otherwise, traders will either buy if CZ > P2, or sell if Cz < P2, an infinite amount
because there is no risk.
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TRADING VOLUME AND PRICE REACTIONS 307
zero) supports the equilibrium." The fact that prices fully reveal all
private information in this equilibrium (and, as a result, traders' beliefs
become homogeneous) lacks institutional appeal given what we observe
about how markets work. For this reason the rest of the analysis in this
paper is based on the second equilibrium in which prices only partially
reveal traders' private information.'2
Suppose that traders conjecture that B, = B2. This implies 41 = q2,
and the two price signals are perfect substitutes. At the end of this section
it will be verified that there is a unique equilibrium in which the condition,
B, = B2, is satisfied. Let B B, = B2 and q-q1 = q2. The error terms
of the signals 51, 5h, ii, and q are mutually independent and therefore it
is straightforward to calculate:
K2i Var-'(a I 51, 5h, zj, P,, P2)
= Var-10(i| I, 52, hi, ii)
= h + m + n + si +
i2i--E(a | 1, Y, Zi6 PI) P2)
= E(u |IY,, 52, Zi, q)
ha + Mil + n52 + siji + (t/B2)4
h + m + n + s- + (t/B2) * )
By convenient properties of the normal distribution, the precision of
trader i's total information at the end of period 2, denoted by K2i, is
simply the sum of the precisions of his prior and observed signals. His
posterior expectation of a at the end of period 2, denoted by g26, is the
" Prior work that is similar in part to ours is Grundy and McNichols [1989]. Both use
two-period noisy rational expectations models in order to capture the price and volume
reactions to the second-period public announcement and both obtain a fully revealing and
a partially revealing equilibrium. The major difference in the two models is in the
preannouncement information structure. In Grundy and McNichols [1989], traders' prean-
nouncement information consists of a common prior and private signals with a common
error as well as idiosyncratic errors. The idiosyncratic errors have the same precision. As a
result, there is no volume in the partially-revealing equilibrium. In the fully-revealing
equilibrium traders observe the market price and correct their idiosyncratic errors which
results in positive volume.
12 It is difficult to suggest which equilibrium is more interesting on purely theoretical
grounds. One possible approach is to consider a sequence of finite economies of which the
present economy is the limit and to see which equilibrium is the limit of the equilibria of
the sequence of economies. Another is to consider a sequence of economies in which the
correlation between the supplies in the two trading periods converges to one as in the
present model. Both approaches are difficult to implement, however, because they do not
appear to yield linear equilibria.
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308 0. KIM AND R. E. VERRECCHIA
average of his prior expectation and observed signals weighted by the
precision.
Let D2i be trader i's desired holding (gross demand) of the risky asset
in period 2. It is well known that the normality of distributions in
conjunction with the exponential utility function allows for a simple
expression for 2i . fot13
Ai= riK2i2i - P2)
- ri(hU + m5l + nh2 + sizi + (t/B2)4 - K2iP2). (6)
Trader i's demand decision is based on his market opportunity, which is
the difference between his assessment of the risky return, A2i, and the
market price, P2. The degree of aggressiveness with which he exploits
his market opportunity is determined by his risk tolerance, ri, and the
precision of his information, K2i.
Equating the aggregate supply to the aggregate gross demand of the
risky asset:
D2i di
f ri[hUi + m5l + n52 + si(C + i) + (t/B2)4 - K2iP2] di
r[ha + myl + n52 + si + (t/B2) 4 -KAL
where r f ri di, s (1/r) f risi di, and K2 (1/r) f riK2i di. s and
K2 = h + m + n + s + (t/B2) are, respectively, the averages of si and K2i
weighted by r1. The term f ris- ei di vanishes by the law of large numbers.
Rewriting the above using the definition of 4:
M1 + m~ l + n/ + S + t2 P2 a - +- i . ~~~~~~~~~~~~(7)
The equilibrium condition that the linear price conjecture is self-
fulfilling dictates that (2) and (7) are identical. Therefore:
h m n S + (t/B2) r-1 + (t/B)
a2 = KS 021 = . K 02 1?2 1 ?2 02 = = 1
From B _Y2/32 = [r' + (tIB )]/[s + (t/B2)], B = 1/rs. The total precision
of trader i in period 2, K2i, and the average total precision in period 2,
13 Maximizing utility with respect to D2i conditional on 51, Y2, 4i, and q generates the
result.
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TRADING VOLUME AND PRICE REACTIONS 309
K2, can now be written as:
K2i = h + m + n + si + r2s2t,
K2 = h + m + n + s + r 2s2t
where r2s2t is the precision of the price signal which is common across
traders.
Trader i's problem in period 1 is to choose his demand given signals
Y1, zi, and P1. He also knows (6) and (7). That is, he knows the exact
future relations among his demand, the price, and the available signals
in period 2. Formally, his problem is to:
max =E[Ui(Wi) I ,1iiPI]
Dhi
= E Ui (Wi) I ~1, i, 4]
= E[-exp{ r [Ei + Pixj + (P2 - P )Dbi + ( -P2)D2i]} |I, iq
=4 exp [Ei + Pi + (P2 P)D
- K2i(a - P2)(ji2i - P2)} |,1 4 q
subject to (7).
The solution to this problem is calculated in Appendix A and can be
written as:
i = - [K2ha + K2m5l + nsii + {K2(s + r2s2t) ns- 4
n
- {n(si - s) + K1K2}Pi], (8)
where:
Kii 3Var-'(d y1, Zi, P1)
= Var-'(a I1, 1i, q)
= h + m + si + r2s2t,
and:
K1 f riK1i di
r
=h + m + S + r 2s2t.
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310 0. KIM AND R. E. VERRECCHIA
Applying the market clearing condition:
f= D1 i
_ rsDi 2Sit
= fs i [i~K2hd + K2myj + nsi(Cz + s) + {K2(s + r2s2t) - ns)
n
* (a-s- -n(si -s) + KlK2PlI di
=- [K2ha + K2m51 + K2(s + r2s2t)u
n
{K2 + rst) - - KK2P1.
The above can be rewritten as:
P, = K-[ha + m5j + (s + r2s2t) -(I + rst) 4 (9)
In equilibrium (1) and (9) are identical and thus:
h m s+r2s2t r-1 +rst
a,1=-, 01 =-, 1 =A1 = K1' K1 K1 K1
For (6), (7), (8), and (9) to be established as an equilibrium, it has
to be verified that the assumption B = B1 = B2 is true. B1 = yi/01 =
(r-1 + rst)/(s + r2s2t) = 1/rs, and it was shown that B2 = 1/rs. Therefore,
(6), (7), (8), and (9) together with B = 1/rs characterize a unique rational
expectations equilibrium in which prices only partially reveal traders'
private information.
3. Price and Volume Reactions to Public Announcements
This section contains the analysis of trading volume and price change
at the time of public announcement. From (7) and (9) the price reaction
to the announcement of Y2 is:
(K- - - [h (a- ) + mi-(rst + r-')i] K2 K2
= [h (u-a )-me + (rst + r1) x + K1] K1K2
[(K1 - mr-s - r2s2t) +Kj- ha- m-
+ (rst + r)]
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TRADING VOLUME AND PRICE REACTIONS 311
-r2s2t(u_ X +]
rs r
n #[ ha+myl+su+r2s2tq x1
K2 2 K, rK, * (10)
Equation (10) is now restated as a proposition.
PROPOSITION 1. The price reaction to a public announcement is
proportional to the importance of the announced information relative to
the average posterior beliefs of traders and the surprise contained in the
announced information plus noise. That is:
P2 - P1 = K (Surprise + Noise),
K2
where:
ha + m5j + sit + r2s2tq . _
Surprise- K1 Noise= rK
The surprise in the announced information as defined in Proposition 1
is the difference between the announced signal, 52, and an average of
traders' expectations of the risky return Ct and, at the same time, of the
announcement 52.14
The relation in Proposition 1 captures the spirit of event studies, which
are conducted typically to examine the information content of particular
announcements. In the case of earnings announcements the change in
price and the surprise in this model correspond to abnormal returns and
unexpected earnings, respectively. The multiple in the relation, n/K2 =
n/(h + m + n + s + r2s2t), is an increasing function of the precision of
the announced information, n, which can be interpreted as the informa-
tion content of the announced information. A greater n implies a more
sensitive price reaction to the announcement. When n is zero, there is
no price change. On the other hand, n/K2 is a decreasing function of the
precision of other information available prior to the announcement. A
greater amount of preannouncement information implies that the price
reacts less sensitively to the surprise in the announcement.
Using (9) equation (10) can be rewritten as:
P2 - PI = K (Y2 - PI). (11)
K2
"4The term, (ha + mn5 + sa + r2s2tq)/KI, is the weighted average of Mi, = (ha +
myi + sAi, + r2s2tq)/K1i, which is trader i's expectation of Cz or 52 conditional on available
information in period 1. The weight is riK1i which measures the degree of traders' aggres-
siveness in exploiting their market opportunities in period 1.
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312 0. KIM AND R. E. VERRECCHIA
This relation is without noise because P1 itself contains the noise defined
in Proposition 1. Both the left-hand and the right-hand side are in
principle observable.
For an analysis of trading volume, first rewrite trader i's demand of
risky asset in the two trading periods expressed in (8) and (6) using (9)
and (7) as:
- rs r- + K [h1 (-u) - me + rsti] rK1 XI
and:
ri(si - s) + riK2i
D2i= rjj~ [h ((a- Cz) - mi~ - ni+ rsti] +~X
K2 rK2
Therefore:
+ D2i- Di = i(i - ) K2 K, [h (( -C) -7 ]j+rt
ri(si - SW + ri (KlK2i-K &K2)i
K2 rK1K2 (12)
= -ri (si- s) Kn [h (az-a) - m + (r-1 + rst)i + Kv
K1K2
= -ri(si - s)(P2 - P1)
The volume reaction to the announcement of 52 can now be calcu-
lated using (12) and the definition of trading volume, Volume
?2 J |D2i -li I di, as in the following proposition.
PROPOSITION 2. The volume reaction to a public announcement is
proportional both to the absolute price change at the time of the an-
nouncement and to a measure of differential precision across traders.
That is:
Volume = frijsi - sjdi) IP2 - P11
- (2 J' rijsi -sjdi) I Surprise + Noise .
The multiple f ri lS - s I di in the above relation is the weighted average
of the absolute deviations of the precision of traders' private information,
sis, from the average precision, s, weighted by the ris.
Intuitively, when the new public information, 2, is released in period
2, all traders revise their beliefs, and this revision is reflected in the
change in market price. Relatively better informed traders revise their
beliefs less because the new information is relatively less important to
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TRADING VOLUME AND PRICE REACTIONS 313
them than to those who are more poorly informed. The presence of
differential precision thus causes differential belief revision among traders
which, in turn, creates trading volume. When there is no difference in
precision, i.e., when si = s for all i, then traders' belief revisions and the
price movement are parallel and there is no volume. Note that this is
true even when ris differ among traders. Thus differences in risk aversion
alone do not result in a positive trading volume in the present model
(although such differences can affect volume in the presence of differ-
ential precision).15
Proposition 2 can be related to an event study context. In tests of the
information content of particular events, such as earnings announce-
ments, Proposition 2 suggests that volume may be a noisier indicator
than price change of the information content of the announcement, n,
and of the amount of preannouncement information, h, m, and s, which
correspond to the prior, public, and private information held at the time
of announcement.16 If the measure of differential precision, which func-
tions as noise if it is not observable, is uncorrelated with the information
variable of interest, the results of a study using volume will not be biased.
However, if the measure of differential precision is systematically related
to the information variable of interest, then the use of volume may distort
results. For example, if more risk-tolerant traders tend to prefer stocks
of smaller firms, the multiple in the relation in Proposition 2 will be
greater for smaller firms. Consequently, a volume study which tests the
difference in the amount of preannouncement information between large
and small firms will produce results that exaggerate the difference.17
Reversing the above argument, the use of volume and returns together
could potentially generate insights about the multiple, which depends on
traders' risk attitudes and the degree of differential precision among
them. If there are reasons to believe that these variables are different
across firms, industries, or types of announcements, then one could use
volume data to test such conjectures. This line of thinking also offers an
alternative way to understand observed differences in volume relative to
returns. For example, Jain [1988] reports that the announcements of
certain macroeconomic variables such as money supply and consumer
price index induce significant abnormal returns but no abnormal volume.
On the other hand, many studies document that there are both significant
15 The fact that differences in risk aversion alone do not result in volume is an artifact
of the exponential utility function. Differences in risk aversion in conjunction with diverse
information generally lead to volume; see, for example, Verrecchia [1981].
6 Atiase [1985], Bamber [1986; 1987], Freeman [1987], and Grant [1980], among others,
compare the extent of market reactions between large and small firms to test the difference
in the amount of preannouncement information.
17 Our results extend (trivially) to a multiasset model in which asset returns and aggregate
supplies are mutually indpendent. Extending the model to a general correlation structure
is much more complicated; see Admati [1985]. Therefore, our insights are limited to
empirical studies in which cross-sectional differences are investigated and these differences
do not depend on cross-sectional correlations.
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314 0. KIM AND R. E. VERRECCHIA
price and volume reactions to earnings announcements.18 Jain [1988]
interprets the difference in volume relative to the absolute price change
between the two types of announcements as caused by differences in the
degree of differential interpretation among traders. However, even with-
out differential interpretations, we show that volume is influenced by the
level of differential precision. Consequently, one must be careful to
consider the roles of both differential interpretations and differential
precision in making inferences about volume.
Finally, the second equation of Proposition 2 implies that the volume
reaction to a public announcement is proportional both to the relative
importance of the announced information and to the absolute value of
the surprise (plus noise) as defined in Proposition 1. This relation is
intuitive and consistent with Bamber's [1987] result that volume is
positively associated with the absolute value of unexpected earnings. If
size is positively associated with the amount of preannouncement infor-
mation (which is in turn negatively related to the relative importance of
the announcement), volume will be negatively associated with size. Such
a relation is reported by Bamber [1987].
The average magnitude of market reaction is often compared among
different firms or different types of announcements without considering
whether the announced news is good or bad. Comparable theoretical
measures are variance of price change and expected volume. The follow-
ing lemma calculates the variance of price change from (10).
LEMMA 1. The variance of price change at the time of public an-
nouncement is:
A Var(P2 - P1)
K22 K12K22
= K2 (1 + nLD ,
where:
L, Var(Cz - P1) = (K1 + s + r2t1)/K12.
The expected volume is calculated in the following lemma using Prop-
osition 2, Lemma 1, and the fact that the expectation of the absolute
value of a normally distributed random variable with zero mean is V271
times its standard deviation.
LEMMA 2. The expected volume at the time of public announcement
is:
V E[Volume]
-=~4,/ J' ri I8 - s I di.
18 These include Beaver [1968], Morse [1981], Pincus [1983], and Bamber [1986; 1987].
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TRADING VOLUME AND PRICE REACTIONS 315
The following proposition is an immediate result of Lemmas 1 and 2
and shows how the magnitude of market reaction is associated with the
precisions of the announced and preannouncement information.
PROPOSITION 3. The magnitudes of both volume and price change at
the time of public announcement are on average associated positively
with the precision of the announced information and negatively with the
precision of the preannouncement prior, public, and private information.
That is:
1. 0 > O. 0 > 0;
~ah 'oh anan
3.-< 0 -< 0;
am 'di
4.A< 0,-v < 0.
as as fL I si-s I di constant
The proof is provided in Appendix A. The results of Proposition 3 are
intuitive. On the one hand, as the quality of an announcement increases,
traders react to the announcement with greater conviction. On the other
hand, as the quality of preannouncement information increases, the
relative importance of the announcement to traders decreases, so they
respond less strongly to the announcement. Holthausen and Verrecchia
[1988] formalize this intuition for price changes in a two-period rational
expectations model and show that this intuition is valid for homogeneous
expectations. Proposition 3 shows that the intuition concerning price
changes remains valid and also applies to volume even when traders are
diversely informed and have different precisions. Furthermore, the results
are also consistent with the intuition and empirical results of Atiase
[1985] and others.
4. Conclusion
We have examined Beaver's [1968] intuition that the change in price
reflects the average change in traders' beliefs, while volume reflects the
sum of the differences in traders' reactions to an announcement, using a
highly stylized model with strong assumptions. The relatively clean and
specific results obtained in this study should thus be interpreted with
care, although the general intuition in most of the results is clear and
does not seem to depend critically on the simplifying assumptions made.
They are also largely consistent with existing empirical findings.
The main result of this paper, that volume may be a noisier indicator
of information variables than the change in price, does not necessarily
imply that volume studies are redundant or inferior. First, volume studies
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316 O. KIM AND R. E. VERRECCHIA
can to a large extent substitute for returns studies. More important, since
volume contains the differences among traders which are averaged out
in the returns data, the use of volume in conjunction with returns could
identify systematic differences in investors' knowledge or other charac-
teristics which result in different reactions to public announcements
across firms or across types of announcements. This paper identifies
differences in precision across traders as a potentially important factor
influencing volume relative to price change. This intuition could shed
light on other interesting issues in accounting and finance related to
differences in the quality of investors' information.19
APPENDIX A
Calculation of Dii
Omitting terms unrelated to Dli, the objective function is written as:
Ep2,i2[-exp~i (P1 - P2)Dli - K2i(- P2)(G2i - P2)} y, zi, q
Using the law of iterated expectations, this becomes:
EpE2,a2{iJ-exPi (P1 -P2)Dli -K2i(u - P2)(L2i -P2)}
* 1 I 6 4l iq P2, A2i] yi, zi, q]
= E32 z2i[-exp-i (P1 - P2)Dli- 2 (q2i-P2)2} | i, qK
because:
E[a I51, 1i q, P2, P t2i] = i26
Var[u l?Y1, Zi, q, P2, /i2i] =K
and thus:
Ea -exp{-K&Wtu - P2)(12i - P2)} |i, Z, q, P2, A2i]
= -exp{-K2i( i22 - P2)(1i2 - + (i22 } L 2 2i P)(W P2) + 2K2i
= -exp{- K2i (12i -P2)2}
using the moment-generating function of a normal random variable.
19 Studies that utilize different properties of volume and returns for analyzing other
issues include Morse [1980], Lakonishok and Vermaelen [1986], and Richardson, Sefcik,
and Thompson [1986].
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TRADING VOLUME AND PRICE REACTIONS 317
(7) and (5) are now written as:
P2 = - [ha + m51 + nO2 + (s + r2s2t) -(rst + r1)x]
K2
1 [ha + m51 + n52 + (s + r2s2t)q],
K2
#2i= K [ha + myi + n52 + sjij + r2s2tq]
Si + s K2
K2i i+ K2 K2i
1
- K [K2P2+ sizi-sq].
K2i
Therefore:
/2i - P2 = K[-(Si - s)P2 + S1 - s4].
Using this relation, the objective function above can be written as:
E[-exp{ (P1 - P2)DAi- [-(Si-S)P2 + SiZi-S2 ylziq
ri ~~2K2, 42 i j
The only random variable in this expression given 51, 4, q, and thus P1
is P2 in a quadratic form.
First, calculate the conditional expectation and variance of P2.
E[P2 i 7 i, 4 = K K [K2i(hU + m5,) + sinzi + (r2s2tK2i + sK1i)q],
Var[P2 I S i, Z =, -K K2
The objective function can now be rewritten as:
E[-exp{- (P1 - P2)DAi - 2K[(- S + Siii-S4I2} 1 Y1, ii, q
xc - (P1 - P2)DAi + K {-(Si - s)P2 + Si, -Sq}2
+ K1K 2 I K K2(haz + m5,)
nK2i [ K+iK2
+ sinii + (r~st~ ~iqlt dP2
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318 0. KIM AND R. E. VERRECCHIA
Oc - Jexp (Si {( ))2 +K1iK2 A 2 - 2p ((si - s)(Sii - s)
L- 2 tK2i nK2i K12
+ K2 {K2i(ha + m51) + sinii + (r2s2tK2, + sK1i)qj- -i)}
nK~~~~~~~~~~~~i~~~ ri )
omitting terms unrelated to D1i or P2. This is simplified to:
1 j_ _ _ K2 -Js exp[-- (Si-s+ ) p22-2P2-(hU + m) + siz
+ (s + r2s2t) -s -Pi)} + Q )] dP2
because:
1{n(si -S)2 + K1iK22} = {n(K2i -K2)2 + KpK22}
nK2i nK2i
- (nK 2 - 2nK2,K2 + K2,K22)
nK2i
= K2i- K2 + K22 - nK2
n
KjK2
= Si - S +
n
and:
(Si - S)(Siii - SO) K22t K2)( , ) +-K2 {K2i(h& + m51) + sini1 + (r2s2tK2i + sKli)qI
K2i snzK__
K2 (hu + my,) + y(K2i-K2+ K2) +K
n K2i nK2i
{K2r2s2tK2i + s(-nK2i + nK2 + K2K1i)1
= K2 (hu + mul,)+ (K2i-K2+ K2) + K
n K2i nK2i
*K2r2s2tK2, + s(-nK2, +K2K2,)I
= K2 K2 2~t = (huz + myl,) + siii + -(S + r st)s iq.
n n