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.
[email protected]
T
he 2012 presidential election was perhaps the most important election 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 challenger 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 Congress 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 outcome. (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 portfolios. This study seeks to determine whether market reactions to presidential elections, such as those following the 2012 election, are valuable 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
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(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; current prices then adjust according to the aggregate market's required return. To illustrate, consider Exhibit 1, which illustrates the wellknown efficient market discounting process. Assuming a 12% required return over a t w o 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 election'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 violations 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.
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EXHIBIT 1 The Market Vote Model: Perfect Efficiency $140.00 $137.98
$125.44
$120.00
$112.90
$100.00
$80.00
1 Approval
Disapproval
Normal
are especially plausible with presidential elections due to the difference between quantitative and qualitative news. Intuition declares that some information 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 information introduced into the market is nonnumeric. Consequently, the discounting process after an election reflects muchless-certain mathematical calculations based on a qualitative news event.
Therefore, the market's discounting process can be viewed from two perspectives. One perspective is that the process is essentially a binary vote in which the aggregate market is forecasting future economic conditions based on political campaigning, and in the case of the 2012 election, the past job performance of the President. The second perspective is that the process is a precise forecast of the present
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 EXHIBIT 2 result in abnormally lower returns and The Market Vote Model: Overreaction vice versa. Even if the market expects future prices to differ from $125.44, the $140.00 net result would not change. The justification for overreaction is well documented in the literature. The second alternative hypothesis $120.00 of the efficient market discounting process illustrated in Exhibit 1 is that the market correctly, but not completely, discounts the president's economic $100.00 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 $80.00 result will be abnormally positive (negative) returns for market approvals (disapDisapproval • Approval provals) . The two alternative hypotheses
56
DOES THE MARKET'S VOTE COUNT? THE INFOR.MATIONAL CONTENT OF POST-PRESIDENTIAL ELECTION
RETURNS
;5.44
Normal
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EXHIBIT 3 The Market Vote Model: Information Not Fully Reflected $140.00
$120.00
$100.00
$80.00
' Approval
Disapproval
Normal
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 evidence 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 subsequent 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.
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Since data for the Dow Jones Industrial index are available from 1896, and following Jones and Banning [2009], the Dow Jones Industrial index (without div$137.98 idends) covering the period 1896-2011 is examined. The advantage of this relatively long time series is that it captures $125.44 the maximum number of elections (29). The disadvantage is that it predates most of the business cycle variables that have $112.90 been shown to explain stock returns. For example, Aaa bond rates are available 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 important 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 matbematical 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 straightforward 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 market's approval (positive returns) or disapproval (negative returns) ofthe election's outcome. These returns, collectively referred to as "post-election returns," capture the market activity for the remainder of the election week and are calculated as follows:
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Ret, =£(Ln(P„/P„.,))
(1)
where returns (Ret^) refer to the cumulative daily logchange 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 exception 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 examined (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 President'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.
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Wheti the market votes on the economic value of the country's vote for President, there are two forecasts 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 contains 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 negative 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. Accordingly, (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 magnitude of futtire prices, and therefore, returns as follows:
where R^ and R^ are the average daily returtis of stibsequent returns following the market's approval or disapproval respectively, G_ and G^ are the variances oíR^ and R. respectively, and n^ and n^ are the number of observations 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 subsequent returtis following market approvals during the post-election period (i.e., positive returns) will be cotiipared to the average daily subsequent returns followitig
DOES THE MARKET'S VOTE COUNT? THE INFOR.MATIONAL CONTENT OF POST-PRESIDENTIAL
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market disapprovals during the post-election period (i.e., negative returns). As illustrated in Exhibit 1, market efficiency predicts 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 positive stock market returns via hisfiscalpolicy. (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 expectations. 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 difference in returns subsequent to presidential elections and, therefore, the predictive 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 positive 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 proportion 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 proportion of successes (p) following market disapprovals, which in the case of disap-
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of testing the
EXHIBIT
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 Equation (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 probabilities. 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 (descriptive statistics are not reported). Following market disapprovals 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-
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
Year E4
Yearl
Year 2
Year 3
Year 4E
% Pos. t % Neg. t
57.2 1.43 49.0 1.38
52.3 0.53 48.6 0.51
52.6 0.63 48.5 0.60
52.4 -1.34 45.4 -1.29
52.6 0.17 47.7 0.17
% Pos. t % Neg. t
55.2 0.62 48.0 0.78
51.2 -0.83 47.1 -1.06
51.6 -0.53 47.3 -0.67
53.3 -0.27 46.1 -0.35
52.8 0.35 48.0 0.47
% Pos. t % Neg. t
53.3 0.68 48.8 0.99
51.7 -0.13 48.0 -0.19
51.1 -1.30 46.0 -1.91*
53.2 -0.49 45.7 -0.73
52.8 0.35 48.2 0.55
*indicates sigtiificattcc at tite 0.Í0 level.
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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 election 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 differences 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 EXHIBIT 5 approvals. While most of the differences Difference of Means are not statistically reliable, the pattern is This exhibit presents the results of Equation (3) as follows: still intriguing because it exists without exception. The lack of statistical significance may be an artifact of the inherently where R^ and R^ are the average daily returns of subsequent returns following the market's small sample size. This pattern suggests a approval or disapproval respectively, C^ and CJ^ are the variances of R^ and R^ respectively, long-term reversal effect during most of 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 the subsequent return periods, as illusmarket's approval/disapproval of an election. trated in Exhibit 6. Exhibit 6 provides a means for Year 4E Year E4 Year 2 Year 3 Yearl observing average price levels (as calPanel A: CRl culated from returns presented in Ave. %Ret. following: 0.00 0.01 0.02 Approval 0.09 0.01 Exhibit 5) over the President's subse0.06 0.02 0.02 0.01 Disapproval -0.05 quent term following the elections. For -0.01 -0.05 0.00 Differenee 0.13 -0.02 consistency with Exhibits 1-3, Exhibit 6 -1.47 -0.06 -0.59 -0.27 Z 2.07** begins with an arbitrary $100 price level Panel B: CR2 Ave. %Ret. following: one year before the election (Time -1). 0.02 -0.01 0.03 Approval 0.02 0.00 At the election date (Time 0), the data 0.02 0.03 0.04 0.03 Disapproval 0.01 are separated into market approvals and -0.04 -0.01 0.00 -0.03 Difference 0.Ö1 -0.11 -1.12 -1.37 -0.42 Z 0.13 disapprovals using CR3 as the proxy. Panel C: CR3 CR3 is chosen because it captures the Ave. %Ret. following: largest difference in returns for Year 0.03 0.02 0.02 0.01 -0.01 Approval 2. For comparison, the expected price 0.02 0.05 0.05 Disapproval 0.01 0.03 -0.01 0.00 -0.02 -0.06 Difference 0.01 levels in the absence of an election are -2.52** -0.52 -0.07 0.21 Z -0.59 also shown, calculated from average returns over the entire sample period. ^indicates significance at the 0.05 level.
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 pattern 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 percentage daily returns for the various periods following the market's approval (disapproval) during the post-election period; the third row presents the difference and the fourth row presents the z-statistic of the difference.
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DOES THE MARKET'S VOTE COUNT? THE INFORMATIONAL CONTENT OF POST-PRESIDENTIAL ELECTION
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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 discounting 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 evidenced 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). However, 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 consistent with Exhibit 2. Comparing the Year 2 results across the post-election return period (i.e.. Panels A, B, and C),
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the daily returns in Year 2 are flat following CRl approvals and 0.01% following disapprovals. 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 statistical reliability of all the results. And third, they are not consistent with the results for Year E4 following 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 immediately (hence the use of CR2 and CR3), once the information 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 information 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.
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By contrast, the returns during Year 2 do not provide evidence of a clean discounting process. To investigate 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
CR2
CR3
CR4
0.00 0.01 -0.01 -0.27
-0.01 0.03 -0.04 -1.37
-0.01 0.05 -0.06 -2.52**
0.00 0.01 -0.01 -0.28
CR5
CR6
CR7
CR8
0.00 0.00 0.00 0.02
0.01 0.00 0.01 0.45
0.00 0.02 -0.02 -0.66
0.01 0.00 0.01 0.34
2011-1952 -0.03 0.04 -0.07 -2.19**
1952-1896 -0.01 0.07 -0.08 -2.85***
*indiccite significance at the 0.05 and 0.01 levels respectively.
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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 discussed 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 election's news. Afterwards, Year 2 returns are not abnormally different, consistent with Exhibit 1. With the unavoidably small sample size, statistical intuition would question the results as simply a smallsample anomaly. To explore this possibility further. Panel B of Exhibit 5 employs CR3 as the proxy for the market's vote and divides the sample into two sub-periods. While this procedure obviously reduces the alreadysmall 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 persuasively 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 following 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-
DOES THE MARKET'S VOTE COUNT? THE INFORM.ATIONAL CONTENT OF POST-PRESIDENTIAL ELECTION
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EXHIBIT 8 Outlier Effects on Average Daily Year 2 Returns 0.20% 0.15%
s
£
0.10%
K
0.05%
2
0.00%
M.
=" -0.05% cd
Q
X 1972 X 1928
gjo -0.10%
2 > -0.15%
X 1912 -0.20% -8%
-6%
-4%
-2%
0%
-0.25%
2%
4%
6%
8%
CR3
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 difference between election campaigning and actual econotnic 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 disseminated 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, consistent 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,
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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
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efficiently the market discounts the results of presidential elections. Returns for the three days following the election 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 following 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 unavoidably small sample size or a pattern of market inefficiency is hard to say. But the most intriguing result is the statistically 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.
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REFERENCES Allvine, F.C., and D.E. O'Neill. "Stock Market Returns and the Presidential Election Cycle/Implications for Market Efficiency." Financial Analysts Journal, Vol. 36, No. 5 (Sept./Oct. 1980), pp. 49-56.
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DOES THE MARKET'S VOTE COUNT? THE INFORMATIONAL CONTE.\'T OF POST-PRESIDENTIAL
ELECTION
RETURNS
SPRING 2014
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