ArticlePDF Available

Does the Market’s Vote Count? The Informational Content of Post-Presidential Election Returns

Authors:

Abstract

One of the most important news events for the U.S. stock markets is certainly the election of the president. This study seeks to determine whether market reactions to elections are a valuable source of information for investors. Using data for the years 1896-2001, a momentum effect appears during the remainder of the election year, a slight reversal effect appears across the president’s term and a strong reversal effect appears during the president’s second year in office. The difference in campaign information during the election and actual subsequent economic policy implementations may explain why the market’s vote does count.
Does the Market's Vote
Count?
The
Informational
Content of Post-Presidential
Election Returns
RAY R. STURM
RAY R. STURM
is an
associate
lecturer
of
fmance
in the
Department
ot
Finance
at
College
of
Business
Administration,
University
of
Central
Florida
in Orlando, FL.
rsturm@ucf.edu
T
he 2012 presidential election was
perhaps the most important elec-
tion in the modern history of the
United States. The country was
trying to recover from the worst economy
since The Great Depression, President Obama's
leadership based on his first term in office
was questioned, and a victory by GOP chal-
lenger Mitt Romney was ripe for the picking.
Yet, on Election Day (November 6, 2012),
the GOP was shell-shocked by a resounding
defeat not only in the presidential election
but in most congressional elections as well.
Despite the argued lack of economic growth
over the prior four years, the President was
reelected and the balance of power in Con-
gress remained unchanged. In response, the
S&P 500 fell 2.37% (close-to-close) the day
following the election as the market apparently
expressed disapproval of the election's out-
come.
(In addition, media speculated that the
market was turning its attention to the Greek
economic crises.) Then the following day, it
fell another 1.22% as investors apparently more
fully considered the implications for their port-
folios.
This study seeks to determine whether
market reactions to presidential elections, such
as those following the 2012 election, are valu-
able information for investors.
The market efficiency model posits that
the adjustment of prices following a news
event such as the presidential election reflects
all available information about the market
(Fama [1965]). After an election, the market in
aggregate will therefore predict the incoming
President's ability to stimulate the economy
and the resulting future stock price levels; cur-
rent prices then adjust according to the aggre-
gate market's required return. To illustrate,
consider Exhibit 1, which illustrates the well-
known efficient market discounting process.
Assuming a 12% required return over a two-
period time horizon and in the absence of an
election, prices would adjust in an efficient
market from an assumed $100 starting level
to $U2 at Time 0 and finally to $125.44 at
Time 1. Inserting an election at Time 0, if
the market approves (disapproves) of the elec-
tion's outcome, believing that the incoming
President's fiscal policies will result in 10%
higher (lower) future stock prices ($137.98 and
$112.90,
respectively), then prices immediately
following the election would adjust to $123.20
($100.80). This illustration forms the null
hypothesis for this study: that market returns
after the discounting process are not reliably
different regardless of the market's vote.
But there are at least two possible viola-
tions of this process. The first is the possibility
that the market overreacts to the election's
outcome. Consistent with the seminal paper
by De Bondt and Thaler [1985] and many
others that followed, the test characteristic
of overreaction is a reversal in prices. With
respect to the current example, overreaction
could manifest itself in infinite combinations.
SPRING 2014THE JOURNAL OE WEALTH MANAGEMENT 55
EXHIBIT
1
The Market Vote Model: Perfect Efficiency
$140.00
$120.00
$100.00
$80.00
$137.98
$125.44
$112.90
ApprovalDisapprovalNormal
This study is concerned with the value of the market's
vote,
so Exhibit 2 illustrates one alternative hypothesis
for this study. Specifically, the market's overreaction to
an election would be indicative of the market's inability
to predict the President's effectiveness. In this example,
regardless of the market's approval or disapproval, future
prices would be $125.44. Hence from
Exhibit 2, the market's approval would
result in abnormally lower returns and
vice versa. Even if the market expects
future prices to differ from $125.44, the
net result would not change. The justi-
fication for overreaction is well docu-
mented in the literature.
The second alternative hypothesis
of the efficient market discounting pro-
cess illustrated in Exhibit 1 is that the
market correctly, but not completely,
discounts the president's economic
ability as reflected in future prices. From
Exhibit 3, if prices adjust only 5% instead
of
10%
($117.60 and $106.40 for approvals
and disapprovals, respectively), then the
result will be abnormally positive (nega-
tive) returns for market approvals (disap-
provals)
.
The two alternative hypotheses
are especially plausible with presidential
elections due to the difference between
quantitative and qualitative news.
Intuition declares that some infor-
mation is more easily, and thus more
quickly, discounted into prices than other
information, because the estimated effects
of quantitative news (e.g., earnings releases
by companies) on future price levels can
be calculated relatively easily using the
many mathematical models available.
These models provide investors with a
relatively objective new trading price
level. But presidential elections reflect less
tangible information because the infor-
mation introduced into the market
is
non-
numeric. Consequently, the discounting
process after an election reflects much-
1 less-certain mathematical calculations
based on a qualitative news event.
Therefore, the market's discounting
process can be viewed from two perspec-
tives.
One perspective is that the process is essentially a
binary vote in which the aggregate market
is
forecasting
future economic conditions based on political cam-
paigning, and in the case of the 2012 election, the past
job performance of
the
President. The second perspec-
tive is that the process is a precise forecast of the present
EXHIBIT
2
The Market Vote Model: Overreaction
$140.00
$120.00
$100.00
$80.00
;5.44
Approval
DisapprovalNormal
56 DOES THE MARKET'S VOTE COUNT? THE INFOR.MATIONAL CONTENT OF POST-PRESIDENTIAL ELECTION RETURNS
SPRING
2014
EXHIBIT
3
The Market Vote Model: Information Not Fully Reflected
$140.00
$120.00
$100.00
$80.00
$137.98
$125.44
$112.90
'
Approval
DisapprovalNormal
value of future price levels consistent with Exhibits 1-3.
Both perspectives are explored in this study.
This study is certainly not the first to examine
the relationship between the President and the stock
market. Many studies have examined the relationship
between stock returns and the President's political party
(Santa-Clara and Valkanov [2003] and others), and the
relationship between stock returns and the presidential
election cycle (Allvine and O'Neill [1980] and others).
Others, such as Nippani and Medlin [2002] and Ferri
[2008] have analyzed short-term stock return responses
to presidential elections.
This study adds to the literature by providing evi-
dence about the market's ability to accurately discount
the outcomes of presidential elections. Market efficiency
predicts that the adjustment process (i.e., the market's
vote) to the election's outcome should result in no sub-
sequent abnormal returns. Alternatively, the presence
of abnormal returns indicates that the lnarket's vote is
systematically incorrect and therefore may be a source
of
value
to investors.
DATA AND METHODOLOGY
Since presidential elections are only held once
every four years, the first challenge in testing the value
ofthe market's vote is the unavoidably small sample size.
Since data for the Dow Jones Industrial
index are available from 1896, and fol-
lowing Jones and Banning [2009], the
Dow Jones Industrial index (without div-
idends) covering the period 1896-2011
is examined. The advantage of this rela-
tively long time series is that it captures
the maximum number of elections (29).
The disadvantage is that it predates most
of the business cycle variables that have
been shown to explain stock returns.
For example, Aaa bond rates are avail-
able from tbe Federal Reserve back to
the year 1919, but even this long time
interval would reduce the sample size by
21%,
from 29 to 23 elections. For the
purposes of this study, maximizing the
already-small sample size is more impor-
tant than decreasing the sample size to
accommodate the availability of control
variables, because a smaller sample size
with more control variables is less compelling than a
larger sample size with fewer control variables.
Since the election news is qualitative in nature,
intuition suggests that the markets in aggregate may not
fully agree on the news' value—at least not immediately.
Hence, it stands to reason that the news' information may
not be reflected in prices as quickly as with quantitative
news.
For example, if
a
company releases earnings that
are inconsistent with market expectations, it is relatively
straightforward to drop the new numbers into a matb-
ematical model and buy or sell shares to the new level.
By contrast, if the market following the 2012 election
(for example) is effectively voting that President Obama
will not be successful in strengthening the economy over
his remaining four
years,
how ineffective will he be and
what is the present value ofthat ineffectiveness?
Estimating the present value of "ineffectiveness"
(as opposed to crisp numbers) is much less straightfor-
ward and requires a longer discounting process. For
this reason, cumulative returns for the one, two, and
three days following presidential elections (CRl, CR2,
and CR3) will be employed as a proxy for the mar-
ket's approval (positive returns) or disapproval (negative
returns) ofthe election's outcome. These returns, col-
lectively referred to as "post-election returns," capture
the market activity for the remainder of the election
week and are calculated as follows:
SPRING
2014
THE
JOURNAL OF WEALTH MANAGEMENT 57
Ret, =£(Ln(P„/P„.,))(1)
where returns (Ret^) refer
to the
cumulative daily
log-
change
in
closing prices over time period t. That is,
the
cumulative returns (Ret_) represent the trading days
for
the remainder of the election week. (During the sample
period, presidential elections
are
held
on the
Tuesday
following
the
first Monday
in
November.)
Prior
to
1984,
the day of
the presidential election
was closed
for
trading,
so the
first closing price (P^)
is Monday's (i.e.,
the day
before
the
election) closing
price. After 1980, the day of the presidential election has
been open
for
trading,
so the
first closing price used
is
Tuesday's (i.e., Electioti Day's) closing
price.
The excep-
tion is the 2000 electioti;
it
was held
on
November
7,
but
the witmer was
not
declared tintil Monday, November
13.
For
2000, therefore,
the
closing price
on
Friday,
November 10, serves as
the
first closing price (P,)-
Equation
(1)
serves
as a
proxy
for the
market's
vote.
Once
the
vote is determined, returtis over various
periods during the presidential election cycle (PEC)
up
to and including the next presidential election are exam-
ined (see Allvine and O'Neill [1980], Booth and Booth
[2003],
Sturm [2009 and 2011] and others
for
discussion
of
the
presidential electioti cycle). Such
a
methodology
serves
to not
otily control
for the
PEC,
but
also
to
help
cotitrol
for
business cycle influences.
In
particular, five
titne-ititervals
of
subsequent returns
are
exatnined:
Year
E4:
represents average daily returns
for
the
day
following
the
post-election period
(the
fourth trading day after
the
election) through
the
remainder
of
the election year.
Year 1, Year 2, and Year
3:
represent average daily
returns
for
the years one through three of the Pres-
ident's term.
Year
4E:
represents average daily returns for the next
election year up
to
and including Election Day.
For
all the
tests,
the 29
post-election cutiiulative
returns
are
divided into
two
groups, positive returns
and negative returns,
to
proxy
for
the market's approval
or disapproval respectively
of the
election's outcome
(i.e.,
the
tnarket's vote). Then,
the
difference between
average subsequent returns across the five time-intervals
is examined.
Wheti
the
market votes
on the
economic value
of the country's vote
for
President, there
are two
fore-
casts
at
issue:
the
direction of future price levels and
the
magnitude
of
those price levels. Therefore,
two
tests
are conducted. First,
the
nonparametric binomial test
of proportions
is
used
to
examine whether the market's
approval
or
disapproval
of
the election's outcome
con-
tains information about
the
proportion
of
subsequent
winning or losing daily returns over the five subsequent
time periods.
The
test statistic
is
calculated
as
follows:
(= {u-p)/{pq/n)
(2)
where
u is the
proportion
of
daily successes
in the
test group,
p is the
proportioti
of
daily successes over
the subsequent return time interval beitig exatnined,
q
is (1
p),
and n is the
number
of
returns
in the
test
group.
A
"success"
is
defined
as the
condition when
post-election returns correctly predict
the
president's
effectiveness as proxied
for
by subsequent returns.
Thus within
the
test groups,
w
is the proportion
of
positive returns following market approvals (i.e., positive
post-election returns [RetJ) and the proportion of nega-
tive returns following market disapprovals (i.e., negative
post-election returns [RetJ).
For
example, during
the
Year
E4
across
the
entire sample, 54.0%)
of
the daily
returns were positive and 46.0% were negative. Accord-
ingly,
(p) is
54.0% when testing market approvals
for
this group and 46.0% when testing market disapprovals.
When testing Year
1, (p) is
51.8%
for
approvals
and
48.2%
for
disapprovals,
and
so forth.
The second test,
the
difference
of
means test,
is
employed to test the market's ability to discoutit the mag-
nitude of futtire prices,
and
therefore, returns as follows:
where R^ and R^ are
the
average daily returtis
of
stibse-
quent returns following
the
market's approval
or
disap-
proval respectively,
G_
and
G^
are the variances
oíR^
and
R.
respectively, and
n^
and
n^
are the number of observa-
tions of R^ and
R^
respectively. To be clear. Equation
(3)
will
be
calculated
by
first sorting
the
average daily
returns following
the
post-election period
in
order
of
the post-electioti returns. Then,
the
average daily
sub-
sequent returtis following market approvals during
the
post-election period (i.e., positive returns) will be cotii-
pared
to the
average daily subsequent returns followitig
58
DOES
THE
MARKET'S VOTE COUNT?
THE
INFOR.MATIONAL
CONTENT
OF POST-PRESIDENTIAL ELECTION
RETURNS
SPRING
2014
market disapprovals during the post-election period (i.e.,
negative returns).
As illustrated
in
Exhibit
1,
market efficiency pre-
dicts that no relation should exist while intuition, given
the qualitative nature
of
the news, predicts otherwise.
In the case of presidential elections, investors are buying
and selling based
on
their confidence
in the
President's
ability
to
create economic conditions conducive
to
posi-
tive stock market returns via his
fiscal
policy. (See Sturm
[2011]
for
an analysis of fiscal policy and the presidential
election cycle.) After
the
election
and
from
a
market
efficiency perspective, investors will
buy or
sell shares
to
new
levels that eliminate abnormal return expecta-
tions.
Thus, Equations
(2) and
(3) serve
to
test whether
the conditions subsequent to the post-election returns as
illustrated
in
Exhibit
2 or
Exhibit
3
are present.
THE MARKET'S VOTE
Exhibits
4 and 5
present
the
results
of
testing
the
difference
in
returns subsequent to presi-
dential elections and, therefore,
the
pre-
dictive power
of
the market's approval
or disapproval
of
the election. Exhibit
4 presents
the
nonparametric results
of
testing
the
market's direction, while
Exhibit 5 presents
the
parametric results
of testing
the
market's quantification
of
the election results.
Specifically, Exhibit
4
presents
the
results of testing the proportion of
posi-
tive and negative daily returns following
market approvals
and
disapprovals using
cumulative returns from Equation
(I)
over the one, two, and three days
(CRl,
CR2,
and
CR3, respectively) following
each presidential election.
In the
first
row
of
each panel
is the
proportion
of
successes
(p)
following market approvals,
which
in
the case of approvals is the pro-
portion
of
positive daily close-to-close
returns across the five subsequent return
periods.
The
second
row
presents
the
i-stat
for
approvals using Equation
(2).
In
the
third row of each panel is the pro-
portion of successes
(p)
following market
disapprovals, which
in the
case of
disap-
provals is the proportion of negative daily close-to-close
returns across
the
five subsequent return periods.
The
fourth row
in
each panel presents
the
f-stat
from Equa-
tion
(2) for
market disapprovals.
From Exhibit
4,
the results initially seem to indicate
that
the
market fully discounts the presidential election
results efficiently with respect
to
binomial probabili-
ties.
That is, when
the
market approves
of
an election,
there
are not an
abnormal number
of
positive returns,
and when
the
market disapproves
of
an election, there
are
not an
abnormal number of negative returns. Upon
closer examination, however, there does appear
to be a
slight "reversal effect"
in
Year
2 of
the
PEC
following
market disapprovals.
During Year 2, 48.0% of the daily returns over the
entire 1896-2011 sample period
are
negative (descrip-
tive statistics are not reported). Following market disap-
provals as proxied
for
by
CRl
(Panel A), 48.5% of daily
returns
in
Year
2 are
negative, which
is not
statistically
different from 48.0% (f
=
0.60). Following market disap-
EXHIBIT
4
Binary
Vote
This
exhibit presents
the
results
of
Equation
(2)
as follows:
i={tt-p)/{pq/ri)"'
where
» is the
proportion
of
successes
in the
test group,
p is the
proportion
of
successes
over
the subsequent return time interval being examined,
q\s{'\
-p),
and
/;
is the number
of returns
in the
test group.
A
"success"
is
defined as the post-election returns correctly
predicting
the president's effectiveness as proxied
for
by subsequent returns. Panels A,
B,
and
C
employ post-election returns
CRl,
CR2,
and
CR3 (respectively)
as a
proxy
for
the
market's approval/disapproval
of an
election.
Panel
A:
CRl
Approved
Disapproved
Panel
B:
CR2
Approved
Disapproved
Panel
C:
CR3
Approved
Disapproved
%
Pos.
t
%
Neg.
t
%
Pos.
t
%
Neg.
t
%
Pos.
t
%
Neg.
t
Year
E4
57.2
1.43
49.0
1.38
55.2
0.62
48.0
0.78
53.3
0.68
48.8
0.99
Yearl
52.3
0.53
48.6
0.51
51.2
-0.83
47.1
-1.06
51.7
-0.13
48.0
-0.19
Year
2
52.6
0.63
48.5
0.60
51.6
-0.53
47.3
-0.67
51.1
-1.30
46.0
-1.91*
Year
3
52.4
-1.34
45.4
-1.29
53.3
-0.27
46.1
-0.35
53.2
-0.49
45.7
-0.73
Year
4E
52.6
0.17
47.7
0.17
52.8
0.35
48.0
0.47
52.8
0.35
48.2
0.55
*indicates sigtiificattcc
at
tite
0.Í0
level.
SPRING
2014
THE
JOURNAL
OF
WEALTH MANAGEMENT
59
provals as proxied for by CR2 (Panel B),
47.3%
of daily
returns are negative, which is still not reliable
{t
=
—0.67),
but (i) has turned negative and moved slightly further
away from zero. Finally, following market disapprovals
as proxied for by CR3 (Panel C), only 46.0% of daily
returns are negative—reliable at the 0.10 level
(f =
-1.91).
While modest, this pattern does hint at a bias that will
be confirmed in Exhibit 5. (There is also a slight pat-
tern in Year 4E disapprovals, but nothing close to being
reliable at the 0.10 level.)
Exhibit 5 employs Equation (3) and presents the
main results of testing whether the market's vote counts.
The first row (second row) presents the average per-
centage daily returns for the various periods following
the market's approval (disapproval) during the post-elec-
tion period; the third row presents the difference and the
fourth row presents the z-statistic of
the
difference.
EXHIBIT
5
Difference of Means
This
exhibit presents the results
of
Equation
(3) as follows:
where
R^
and
R^
are the average daily returns
of
subsequent
returns following the market's
approval
or disapproval respectively,
C^
and
CJ^
are the variances
of
R^ and
R^
respectively,
and
n^
and »j are the number
of
observations
of
R^ and R^ respectively. Panels A, B, and
C
employ post-election returns CRl, CR2, and CR3 (respectively) as a proxy for the
market's
approval/disapproval
of an
election.
Panel
A: CRl
Ave.
%Ret. following:
Approval
Disapproval
Differenee
Z
Panel
B:
CR2
Ave.
%Ret. following:
Approval
Disapproval
Difference
Z
Panel
C: CR3
Ave.
%Ret. following:
Approval
Disapproval
Difference
Z
Year
E4
0.09
-0.05
0.13
2.07**
0.02
0.01
0.Ö1
0.13
0.02
0.01
0.01
0.21
Yearl
0.01
0.02
-0.02
-0.59
0.00
0.03
-0.03
-1.12
0.01
0.03
-0.02
-0.59
Year
2
0.00
0.01
-0.01
-0.27
-0.01
0.03
-0.04
-1.37
-0.01
0.05
-0.06
-2.52**
Year
3
0.01
0.06
-0.05
-1.47
0.03
0.04
-0.01
-0.42
0.03
0.05
-0.01
-0.52
Year
4E
0.02
0.02
0.00
-0.06
0.02
0.02
0.00
-0.11
0.02
0.02
0.00
-0.07
^indicates
significance at the 0.05 level.
The first result to be discussed in Exhibit 5 is the
relation between CRl and average daily returns for
the remainder of the election year (Year E4). When the
market approves of an election as proxied for by the next
day's return (CRl), the average daily returns for the
remainder of
the
election year have been about 0.09%.
By contrast, when the market disapproves of an election,
the average daily losses for the remainder of the elec-
tion year have been about 0.05%—a difference of about
0.13%
(0.05 level). Hence, it appears that following a
presidential election, the election's information is not
fully reflected after CRl, consistent with the notion
that qualitative information is more difficult to discount
than qualitative information.
The second result to be discussed from Exhibit 5 is
that over the president's subsequent term, all the differ-
ences in means are negative, consistent with Exhibit 2.
That
is,
across all post-election periods (CR1-CR3) and
across Year 1-4E of the PEC, average
daily returns following disapprovals
exceed average daily returns following
approvals. While most of the differences
are not statistically reliable, the pattern is
still intriguing because it exists without
exception. The lack of statistical signifi-
cance may be an artifact of the inherently
small sample size. This pattern suggests a
long-term reversal effect during most of
the subsequent return periods, as illus-
trated in Exhibit 6.
Exhibit 6 provides a means for
observing average price levels (as cal-
culated from returns presented in
Exhibit 5) over the President's subse-
quent term following the elections. For
consistency with Exhibits 1-3, Exhibit 6
begins with an arbitrary $100 price level
one year before the election (Time -1).
At the election date (Time 0), the data
are separated into market approvals and
disapprovals using CR3 as the proxy.
CR3 is chosen because it captures the
largest difference in returns for Year
2.
For comparison, the expected price
levels in the absence of an election are
also shown, calculated from average
returns over the entire sample period.
60 DOES THE MARKET'S VOTE COUNT? THE INFORMATIONAL CONTENT OF POST-PRESIDENTIAL ELECTION RETURNS
SPRING
2014
EXHIBIT
6
Reversal Effect Following CR3
$150.00
$140.00
$130.00
$120.00
$110.00
$100.00
$90.00
Approvals
Disapprovals
Expected
From
a
casual observation of Exhibit
6, it
is clear that
a
reversal effect is present consistent with, but much more
pronounced than
in.
Exhibit
2. The
presence
of
this
reversal effect suggests that the market overreacts
to the
election's outcome.
Recall that
the
purpose
of
employing
CR2 and
CR3 is to consider the possibility that information about
the elections' results
are not
immediately agreed upon
by
the
market,
in
aggregate resulting
in a
slower
dis-
counting
process.
From a market efficiency perspective,
the difference
in
Year E4 results over
the
post-election
period (Exhibit
5,
Panels A,
B, and C)
suggest tbat
the
market requires more than
one day to
fully reflect
the
information provided by the presidential election, as evi-
denced
by the
abnormal difference
of
0.13%
in
returns
(consistent with Exhibit
2)
following CRl.
But by the
end
of
the second
day
following
the
election
(CR2 in
Exhibit
5,
Panel B),
the
market has already discounted
the information fully,
as
evidenced
by the
non-reliable
difference
of
0.01%
(consistent with Exhibit 1).
How-
ever, the opposite effect is present with respect to Year 2
of the PEC.
The Year
2
results suggest that
the
markets
may
slowly overreact to the elections' results, somewhat con-
sistent with Exhibit
2.
Comparing the Year
2
results across
the post-election return period (i.e.. Panels A, B, and C),
the daily returns
in
Year 2 are flat following
CRl approvals
and
0.01% following disap-
provals. Following
CR2
approvals, returns
for Year
2
become slightly negative (-0.01%)
and more positive following disapprovals
(0.02%).
However,
for
market approvals
as
proxied for by the three days after the election
(CR3),
returns
are
still around
-0.01%
but
returns following disapprovals have jumped
to 0.05%. Moreover, the statistical reliability
of the differences across Panels
A, B, and
C increases from
a
very insignificant
-0.27
z-score following CRl,
to
-1.37 following
CR2,
and
then
to a
statistically significant
-2.52 (0.05 level) following CR3.
The Year
2
results
are the
most
intriguing
for
three reasons. First, they
are
consistent with
the
pattern identified
in the
binomial tests of Exhibit
4.
Second, the Year
2 returns
in
Panel
C
present the greatest sta-
tistical reliability of all the results. And third,
they are
not
consistent with
the
results
for
Year E4
fol-
lowing
CRl
(Exhibit
5,
Panel A). Hence,
the
returns
for
the
President's second year
in
office merit further
investigation.
RETURNS EOR THE PRESIDENT'S SECOND
YEAR IN OFFICE
The contradictory evidence between Year
E4
and Year
2 is
difficult
to
reconcile within
the
efficient
market hypothesis. While
it
is straightforward
to
accept
that prices
may not
fully reflect information immedi-
ately (hence the use of CR2 and CR3), once the infor-
mation
is
fully reflected, abnormal returns should
not
be observed, consistent with Exhibit
1.
Even if abnormal
returns
are
observed, tbey would
be
expected
to be
eventually arbitraged away, resulting
in
normal returns
thereafter.
(See
Black [1971]
and
many others
for an
explanation
of
the arbitrage process.)
It
appears that
this arbitrage process
is
observed
in
Exhibit 5, Panel
A.
Abnormal returns
for
Year E4 are observed, suggesting
that prices do not fully and immediately reflect all infor-
mation about
the
elections.
Yet no
abnormal returns
are observed after
tbe
Year E4 time period, suggesting
that
the
information
is
fully reflected
by tbe end of
Year E4.
SPRING
2014
THEJOURNAL
OF WEALTH MANAGEMENT
61
By contrast, the returns during Year 2 do not pro-
vide evidence of
a
clean discounting process. To inves-
tigate the Year 2 conundrum further. Exhibit 7 presents
the results of expanding the
tests.
In particular. Exhibit 1,
Panel
A
presents Year
2
returns following market approvals
and disapprovals as in Exhibit 5, except the post-election
period is extended through eight trading days following
the election. That
is,
(n) in Equation (1) is extended from
three to eight to capture returns for the remainder ofthe
election week, as well as the following week. Panel B
in Exhibit 7 replicates the results of Exhibit 5 for Year 2
using CR3 as a proxy for the market's vote, except that
the sample is divided into the sub-periods 2011-1952
and 1952-1896.
EXHIBIT
7
Year
2 Returns
This
exhibit presents the results
of Equation
(3) for Year 2 returns
as
follows:
where
R and
R^
are the average daily returns
of subsequent
retLirns
following
the market's approval or disapproval respectively, a_ and
C5j
are the variances
of
R^ and R^ respectively, and
«^
and
»^
are the
number
of observations of
R_
and R^ respectively. Panel A sorts
returns
over post-election periods from the day after the election
(CRl)
through the following week
(CR8).
Panel B replicates the
results
in Exhibit
5
over the sub-periods 1896-1951 and 1952-2011
using
CR3 as a proxy for the market's
vote.
Returns
Panel
A: Year 2
Ave.
%Ret. following:
Approval
Disapproval
Difference
Z
Ave.
%Ret. following:
Approval
Disapproval
Difference
Z
Panel
B: Subperiods
following
CR3
Ave.
%Ret. following:
Approval
Disapproval
Difference
Z
CRl
0.00
0.01
-0.01
-0.27
CR5
0.00
0.00
0.00
0.02
CR2
-0.01
0.03
-0.04
-1.37
CR6
0.01
0.00
0.01
0.45
2011-1952
-0.03
0.04
-0.07
-2.19**
CR3
CR4
-0.01
0.00
0.05 0.01
-0.06
-0.01
-2.52**
-0.28
CR7
CR8
0.00 0.01
0.02 0.00
-0.02
0.01
-0.66
0.34
1952-1896
-0.01
0.07
-0.08
-2.85***
*indiccite significance
at
the
0.05 and
0.01
levels
respectively.
From Exhibit 7 Panel A, the results for CR1-CR3
reproduce the results in Exhibit 5. For the remainder of
the extended post-election period, the previously dis-
cussed pattern leading up to CR3 does not continue
beyond CR3, implying that with respect to Year 2, the
market requires three days after the election (i.e., the
remainder of the election week) to discount the elec-
tion's news. Afterwards, Year 2 returns are not abnor-
mally different, consistent with Exhibit 1.
With the unavoidably small sample size, statistical
intuition would question the results as simply a small-
sample anomaly. To explore this possibility further. Panel
B of Exhibit 5 employs CR3 as the proxy for the mar-
ket's vote and divides the sample into two sub-periods.
While this procedure obviously reduces the already-
small sample size, the statistical reliability ofthe results
is not affected. In particular, the reversal effect holds up
over both sub-periods, with a difference in means of
-0.07%
for the most recent period and
-0.08%
for the
earlier period, both statistically reliable at the 0.05 and
0.01 levels, respectively. This result serves to not only
mitigate the small-sample concerns, but also speaks per-
suasively to the effect's consistency.
Another possible explanation for the Year
2
results
is that outliers skew the results. Exhibit 8 presents the
average daily returns in Year
2
as a function ofthe CR3
returns. Exhibit
8
identifies four potential outliers in the
data: the returns following the elections of
1912,
1928,
1952,
and 1972. Considering each potential outlier one
at a time and in order of extremity, the returns fol-
lowing the 1912 election appear to be the most obvious
potential outlier. Dropping this data point from the
analysis reduces the z-value from —2.52 (Exhibit 7)
to -2.24, still a reliable result. (Results for the outlier
tests not reported.) If both 1912 and 1928 are dropped,
the z-value drops further to —1.94, also still a reliable
result. Finally, if 1972 is to be considered an outlier, so
too should 1952. Dropping all four of
these
data points
(1912,
1928, 1952, and 1972) results in
a
z-value of-2.14.
Therefore, the results do not appear to be significantly
influenced by outliers. Moreover, taking Exhibits 7 and
8 together strongly suggests that a Year 2 effect exists
that is robust to methodological considerations.
Since a Year 2 effect appears to be clearly present,
what drives the effect? Answering this question is not
easy, especially since a conclusive explanation for the
PEC has not been offered in the literature. (See Sturm
[2011] for
a
literature review and discussion.) The Presi-
62 DOES THE MARKET'S VOTE COUNT? THE INFORM.ATIONAL CONTENT OF POST-PRESIDENTIAL ELECTION RETURNS
SPRING
2014
EXHIBIT 8
Outlier
Effects
on
Average
Daily Year
2
Returns
0.20%
0.15%
£
0.10%
s
K
0.05%
2
0.00%
="
-0.05%
cd
Q
gjo
-0.10%
2
>
-0.15%
-0.20%
-0.25%
M.
X
1972
X
1928
X
1912
-8%
-6%
-4%
-2%
0%
CR3
2%
4%
6%8%
dent's influence over fiscal policy would seetn to be an
obvious driver of the PEC, but Sturm [2011] examines
and finds no relation between fiscal policy and the PEC.
However, he does consider tax legislation as a potential
driver, which tnay also help explain the Year 2 reversal
effect docutnented in this study.
Since the majority of tax legislation is usually
passed within the first half of the President's term
(Sturm [2011]), the Year 2 effect may reveal the dif-
ference between election campaigning and actual eco-
notnic policies. For example, regardless of whether the
market approves or disapproves of ati election's outcome,
the market's vote is based mostly on information dis-
seminated via campaigning at that time. Because it takes
time for the new President to itnplement policies, the
second year of
his
tertii is the most likely time interval
for the full details of his actual economic/tax policies
(as opposed to the policies presented during the election
campaign) to be revealed. Once they are, the market
recalculates the present value of future price levels, con-
sistent with Exhibits 1—3.
From the evidence in Exhibits 4, 5, and
7,
it appears
tbat the tnarket is usually disappointed in Presidents of
whom it approved and relieved by Presidents of whom it
disapproved. That
is,
the market overreacts. Admittedly,
this explatiation
is
conjecture, but it
is
plausible iti light of
a belief that presidential candidates either have a hidden
economic agenda during their campaign, do not (or are
not able to) follow through on campaign promises, or do
not truly understand the consequences of their planned
economic policies. In the absence of such a
belief,
other
explanations would need to be considered.
CONCLUDING REMARKS
The model of market efficiency predicts that
market prices will adjust completely and immediately
following the release of
a
news event. One of the most
important news events for the markets certainly must be
the election of the Presidetit of the Utiited
States.
So frotn
an efficient market perspective, the stock tnarket will
effectively "vote" on the newly elected President's ability
to create future value in the markets after the election's
results are determined. This study seeks to determine
whether this vote contains value for investors.
The key piece of evidence determining whether
prices fully reflect infortnation
is
the presence or absence
of a difference in returns subsequent to the news release.
Using daily data for the Dow Jones Industrial Average
over the period 1896-2011, this study examines how
SPRING
2014
THE
JOURNAL OF WEALTH MANAGEMENT 63
efficiently the market discounts the results of presidential
elections. Returns for the three days following the elec-
tion are employed as a proxy for the market's approval
or disapproval of the elections' results. Positive returns
indicate the market voting in favor of the incoming
President and vice versa. Then, returns following this
post-election period are examined from the perspective
of the presidential election cycle for the presence of
a
difference.
The results expose three abnormalities that may be
a source of information to investors. First,
a
momentum
effect appears to be present over the remainder of the
election
year,
implying that the market reacts "correctly"
but not fully to the election's outcome. Second, a slight
reversal effect appears to be present across the President's
term. Finally,
a
persuasive "Year
2
reversal effect" appears
in both the direction and the magnitude of average daily
returns during the President's second year in office. The
market experiences an abnormal number of negative
days during the President's second year in office fol-
lowing market approvals, and an abnormal number
of positive days during the President's second year in
office following market disapprovals. Moreover, daily
average returns are
—0.01%
following market approvals
and 0.05% following market disapprovals—a statistically
reliable difference of about 0.06% that is robust across
sub-periods.
Whether the results are an artifact of the unavoid-
ably small sample size or
a
pattern of market inefficiency
is hard to say. But the most intriguing result is the statis-
tically reliable Year 2 reversal, which may be driven by
the difference between the political rhetoric with respect
to economic policy during the election and the actual
facts as revealed during the President's first two years
in office. Given the robustness of this result combined
with the other results, the market's vote may indeed be
a source of value to investors. Therefore, the market's
vote does appear to count.
Black,
F.
"Implications of the Random Walk Hypothesis for
Portfolio Management."
Finatuial
Analysts
Journal
(1971), pp.
16-22.
Booth,
J.R., and
L.C.
Booth. "Is Presidential Cycle in Secu-
rity Returns Merely a Reflection of
Business
Conditions?"
Review
of
Financial
Economics,
12 (2003), pp. 131-159.
De Bondt, W.F.M., and R.H. Thaler. "Does the Stock Market
Overrezctl"
Journal
of
Finance,
40 Quly 1985), pp. 793-805.
Fama, E.F. "The Behavior of Stock-Market Prices." The
Journal
of
Business,
Vol. 38, No. 1 (1965), pp. 34-105.
Ferri, M.G. "The Response of
U.S.
Equity Values to the 2004
Presidential Election." JoMrna/ of
Applied
Finance,
Vol. 18, No.
1 (2008), pp. 29-37.
Jones,
S.T., and K. Banning. "U.S. Elections and Monthly
Stock Market Returns." The
Journal
of
Economics and
Finance,
22 (2009), pp. 273-287.
Nippani, S., and W.B. Medlin. "The 2000 Presidential Elec-
tion and the Stock
Market."
JoMn/a/
of
Economics and
Finance,
Vol. 26, No. 2 (2002), pp. 162-169.
Santa-Clara, P., and R. Valkanov. "The Presidential Puzzle:
Political Cycles and the Stock Market." The
Journal oj
Finance,
Vol. 58, No. 5 (2003), pp. 1841-1872.
Sturm, R.R. "The 'Other'January Effect and the Presidential
Election Cycle."
Applied Financial
Economics,
Vol. 19, No. 17
(August-September, 2009), pp. 1355-1364.
Sturm, R.R. "Economic Policy and the Presidential Elec-
tion Cycle in Stock Returns."JoMmal of
Economics and Finance
(2Gll),DOI:10.1007/sl2197-011-0179-6.
To
order reprints
of
this
article,
please contact
Dewey
Palmieri
at
dpalmieri@iijournals.com or
212-224-3675.
REFERENCES
Allvine, F.C., and D.E. O'Neill. "Stock Market Returns and
the Presidential Election Cycle/Implications for Market Effi-
ciency."
Financial
Analysts
Journal,
Vol. 36, No. 5 (Sept./Oct.
1980),
pp. 49-56.
64 DOES THE MARKET'S VOTE COUNT? THE INFORMATIONAL CONTE.\'T OF POST-PRESIDENTIAL ELECTION
RETURNS
SPRING 2014
©EuromoneyInstitutionalInvestorPLC.Thismaterialmustbeusedforthecustomer's
internalbusinessuseonlyandamaximumoften(10)hardcopyprint-outsmaybemade.No
furthercopyingortransmissionofthismaterialisallowedwithouttheexpresspermissionof
EuromoneyInstitutionalInvestorPLC.Source:JournalofWealthManagementand
http://www.iijournals.com/JPPM/Default.asp
Article
Full-text available
Purpose The purpose of this paper is to provide a plausible explanation for the “sell in May” anomaly observed in US stock markets. A heretofore unexplained strategy of selling stock in May and not returning to the market until November has been shown to outperform a simple strategy of buying and holding stock all year long. Design/methodology/approach The authors compare the seasonal performance of three US size-based portfolios for the May–October and November–April periods considering whether or not they were in years with US congressional elections, which occur every two years. Findings While the sell-in-May effect appears to persist in the long run, the authors find that the anomaly is not present in non-election years. There is no significant difference between the May–October and November–April stock returns in non-election years. The observed sell-in-May effect is driven by poor stock returns in the May–October periods leading up to US presidential or congressional elections and subsequent strong performance in the November–April periods immediately following elections. Originality/value The paper offers an election-year effect as an explanation of the sell-in-May anomaly that has been observed in the US stock market. Other possible explanations of the effect, such as seasonal affective disorder, the weather, and daylight savings time, have not gained widespread acceptance.
Article
Full-text available
Many papers in the academic literature have documented a “Presidential Election” cycle in stock returns. Prior literature also documents that stock returns appear to be influenced by economic policy. The goal of this study is to examine the tools of fiscal and monetary policy to test for the presence of a presidential election cycle. The findings strongly suggest that the presidential election cycle in stock returns and the government’s economic policy influence on stock returns are two separate phenomena. Moreover, it is much more likely that stock returns are influencing economic policy rather than the other way around. However, the findings also suggest that tax legislation may drive the Presidential Election Cycle. KeywordsStock Returns–President–Election Cycle–Economic Policy–Tax Legislation
Article
Full-text available
The 'other' January effect posits that when January's stock returns are positive (negative), the remaining 11 months of the year tend to be positive (negative) as well. While no explanation is currently offered, this departure from market efficiency carries important implications for the portfolio management decision. Other research has shown that stock returns tend to be higher during the second half of the president's term than during the first half as a result of variations in fiscal policy across time. When the 'other' January effect is examined in the presence of the presidential election cycle, it seems clear that January holds greater predictive power during certain years of the president's term in office. Therefore, in portfolio management decisions, investors should not view either in isolation, but consider both together.
Article
We confirm previous findings that both large‐cap and small‐cap stock returns in the US exhibit a presidential cycle pattern, i.e. returns are significantly higher in the last 2 years than in the first 2 years of the presidential term. We attempt to examine if this presidential cycle pattern can be explained away by the traditional business cycle proxies, namely the term spread (TERM), dividend yield (D/P), and default spread (DEF). Our motivation arises from the political business cycle theory that monetary and fiscal measures undertaken by presidents are usually translated into the business cycle. We find that the presidential cycle has explanatory power beyond business conditions proxies shown to be important in explaining stock returns. Tests of slope parameters show that stock returns are less sensitive to only the D/P during the last 2 years of the presidential term. The presidential cycle effect prevails even after controlling for the party in power and the incumbent versus nonincumbent presidents.
Article
The impact of the delay in the declaration of a winner in the U.S. Presidential Election of 2000 on the performance of stock markets is examined in this study. We present evidence indicating that the stock market performance was different from a pre-event comparison period. Conventional t-tests and a dummy variable regression that controls for interest rate movements are used to present evidence indicating that there was a significant initial negative reaction to the delay in the election results.
Article
Using monthly market returns over a period of 104years, we investigate possible relationships between stock market performance and various occurrences in American elections. Unlike most prior studies, we find little relationship between the two. In the relatively few cases where we do find statistically significant relationships, the degree of explanatory power is quite small. Specifically, market returns do not appear to vary based on partisan control of the government, a result that is robust to the inclusion or exclusion of macroeconomic control variables. Further, the often-discussed “second-half” effect, which predicts higher returns during the second half of a given presidential term, turns out to be both weaker and less straightforward than is commonly believed. Overall, neither election results nor the election cycle appears to offer much help in predicting stock market returns.
Article
We confirm previous findings that both large-cap and small-cap stock returns in the US exhibit a presidential cycle pattern, i.e. returns are significantly higher in the last 2 years than in the first 2 years of the presidential term. We attempt to examine if this presidential cycle pattern can be explained away by the traditional business cycle proxies, namely the term spread (TERM), dividend yield (D/P), and default spread (DEF). Our motivation arises from the political business cycle theory that monetary and fiscal measures undertaken by presidents are usually translated into the business cycle. We find that the presidential cycle has explanatory power beyond business conditions proxies shown to be important in explaining stock returns. Tests of slope parameters show that stock returns are less sensitive to only the D/P during the last 2 years of the presidential term. The presidential cycle effect prevails even after controlling for the party in power and the incumbent versus nonincumbent presidents.
Article
Thesis (Ph. D.)--University of Chicago, Graduate School of Business, June, 1964. "Reprinted from the Journal of business of the University of Chicago, XXXVIII, no. 1 (January, 1965), 34-105." Includes bibliographical references. Microfilm. Chicago : Dept. of Photoduplication, University of Chicago Library,