Contemporary Journal of Economics and Finance
Volume 1, Issue 1, December 2022, pages 34-42
The Impact of the U.S. Presidential Elections on the Stock Markets
Shab Hundal1, Tatyana Kauppinen1
1 JAMK University of Applied Sciences, Finland
Abstract: The US presidential elections have a history of making financial markets volatile, and unpredictable before and after the elections in comparison to other times. The current study investigates if any systematic association exists between risk and return of corporate sector during the U.S. presidential elections. The secondary data have been collected from 50 U.S. publicly listed companies for the four election periods: 2004, 2008, 2012 and 2016. The empirical findings show that higher returns are accompanied by higher risks and the US presidential elections do make significant impact on stock markets’ risk – return dynamics.
Keywords: Financial risks, risk – return, stock market dynamics, stock bubble, systematic risk, unsystematic risk
1. Introduction
The U.S. presidential elections are reckoned as significant event not only for the U.S. but also for the entire world as the U.S. is the world’s largest economy and the U.S. presidential elections can change the direction of the global social-politico-economic developments. The current study is based on the premise that the stock markets cannot remain unaffected by the political developments and the U.S. presidential elections can have a significant impact on the U.S. and global stock exchanges [1, 2]. The principal research problem of the current study is if there are any associations between the U.S. presidential elections and the risk and return dynamics of the companies. The U.S elections are often accompanied by controversies on the political, economic, and business frontiers in U.S. and elsewhere. Political mudslinging in the media including allegations and counter-allegations made by politicians against each other, before the presidential election, during and even after can have a stronger influence on stock prices. “Every time Presidential-elect Donald Trump tweets, the markets listen. Since his election victory he has sent shares in companies such as Boeing, Lockheed Martin, Toyota and Pfizer reeling into the red, shaving off billions of dollars from their market value in minutes”.
The principal this research objective is to find out any connection, association between U.S. presidential elections and the type of political ideology of the party which comes in power. The study addresses the following research questions: (i) does the risk-return dynamics of the U.S. firms experience any change during the US presidential elections? (iii) does the risk-return dynamics of the U.S. firms experience any specific change when a certain political party comes into power?
To answer the research questions four U.S. presidential election periods have been selected-2004, 2008, 2012 and 2016. Each period includes pre, during and post-elections years. The quantitative data analyses are based on the fifty biggest publicly listed U.S. companies, belonging to different sectors, taken from the S&P databases. The empirical findings show that there is a strong relationship between the U.S. presidential election and sock return fluctuations. Interestingly, the unsystematic risk has affected the sample companies’ risk adjusted return inversely, whereas the systematic risk has been found to be positively associated with both annualized return and risk adjusted annualized return. Overall, the current study concludes that higher returns are accompanied by higher risks and the US presidential elections do make significant impact on stock markets’ risk – return dynamics.
Section two is the literature review of core theoretical concepts and empirical studies. Section three includes research design, data, and methods. Section four highlights the findings of the study. The last section focuses on the discussion, conclusions, and implications of the study.
2. Literature Review
Wisniewski et al. [4] underline the importance of political events, such as the U.S. presidential elections, and their impact on financial markets, however, there is a paucity of empirical research in this filed. There are several studies which have attempted to explore the association between the U.S. presidential election and stock market fluctuation, however, there is a lack of consensus in terms of findings. Blanchard et al. [5] apply the Gordon Growth Model (GGM) and find that the dividend ratio decreased from the time of the election until the end of 2017 implying that either the expected dividends growth increased and / or that the stock premium decreased during the abovementioned time. The study further finds that tax concessions announced by political parties during election years can raise expectations for future dividends and as a result stock prices start increasing.
In another study Behl and Sethi [6] aimed to explore the impact of the U.S. presidential elections, that have taken place from 1980 to 2010, on the stock market performance for eight different industries. The study analyzed the stock market abnormal return in reference to the corporate tax policy of the state during election year as well as pre, and post-election years. The study finds that stock market reaction is not homogeneous with respect to the certain political party’s victory in the elections. Democratic party’s victory impacts the stock return negatively but in case of Republican party’s victory the results are inconclusive. The study also finds a positive association between abnormal stock price and firms’ marginal tax rate during the election period. Similarly, the reaction of investors also varies across different industries, for example manufacturing and mining industries has reacted significantly negative to the elections when compared to remaining six industries. Furthermore, there has been a negative reaction of stock market after and before the election, whenever a Democratic candidate of Democratic party wins. However, the same is not true when the wining candidate belongs to the Republican party. Similarly, a change in the government causes stronger effect on the stock market in compression to the situation when the same party is getting a re-elected. A change in the ruling party affects the market sentiments and raises the expectations of the market players in terms of policy reforms which fluctuate the stock market. Similarly, it has been found that abnormality in the stock price returns can be caused by uncertain tax policy, approximated by marginal tax rate.
Niederhoffer et al. [7] have investigated the movements in Dow Jones Industrial Average (DJI) before and after the US presidential elections. In this study, eighteen US presidential periods have been investigated during 1900 – 1968. The study finds that the pattern of stock market performances has not shown any systematic difference whether the US is ruled by Republican or Democratic administrations. Allvine and O’Neil [8] have explored interconnection between politics and stock market. Their study shows that stock markets in the USA generally follow a four-year business cycle that corresponds to the US presidential election cycle. Riley and Luksetich [9] have explored the investors’ preference between Republicans and Demarcates. Huang [10] has found out that there have been higher average returns during Democratic administrations, in contrast of the widely held belief that the Republican Party is preferred by stock markets. In a similar vein, Santa-Clara and Valkanov [11], based on their investigation for the period between 1927 to 1998, conclude that the excess return in the stock markets is higher under Democratic rule than under Republican rule. Similarly, Johnson et al. [12] have found that investors earn higher returns on small-cap stocks during Democratic administrations. Bouman and Jacobsen [13] have given an hypothesis that investors, both individual and institutional, have strong reasons to go short in May and not to take long position until November of the same year. They show significant differences in average monthly returns for May-October vs November-April of the same year. Waggle and Agrrawal [14] find that the sell-in-May adage observed in the US stock market is actually applicable to an election-year effect. There are significant seasonal differences seen in the US stock markets in terms of returns in the given election year. Waggle and Agrrawal [14] find that most of the strongly positive November-April returns occur immediately following an election. However, there is no significant difference between the May-October and November-April returns of non-election years. Therefore, it is not a wise move on the part of investors to follow the sell-in-May adage blindly, especially in non-election years.
Oehler et al. [15] do not find any systematic pattern in industry-wise returns when comparing the effect of election victories Democratic and Republican for the period 1980-2008. However, the extent of the stock market reaction is not homogeneous across industries. For example, stock return of mining and manufacturing industries mainly react adversely to presidential elections, while construction and the financial sectors are less influenced. The victory of a Democratic candidate emits a negative stock market reaction both before and after the election, whereas the results are rather mixed when the winning candidate is Republican. Interestingly, a change in presidency from either the Democratic party to the Republican party or vice-versa causes stronger stock market effects than re-election of a president from the same party. This result indicates that the change of guard contains more relevant information for market participants than the continuation of a political approach and supports the notion that markets actually react to changes in the political landscape as induced by presidential election Similarly, the firms’ marginal tax rate is recognized as an important determinant that affects abnormal stock price returns and both variables are positively correlated around the election day.
Colón-De-Armas et al. [16] examine the relationship between political events and the stock market, particularly shifts in investor sentiment around the seven US presidential elections for the period 1988-2012. The investor sentiment is measured by changes in discounts in the closed-end funds. The study shows that discounts significantly diminish starting from two weeks before the election to a week before the election, and persist until the week after the election, suggesting an increase in investors’ optimism during that period. The study shows that the sentiment of individual investors is a function of political uncertainty. Investors’ optimism increases when the level of uncertainty regarding the election’s outcome is resolved the week before the election. It can be so as investors realize which presidential candidate is the clear favorite to win. The increase in investor’s optimism is stronger before and after a Democrat is elected president, which is consistent with the extensive literature documenting higher stock market returns during Democratic as opposed to Republican US presidencies. When a Republican is elected, an initial increase in optimism also is observed two weeks before the election. That optimism, however, begins to disappear perhaps when it becomes more likely that a Republican will be elected, and is completely reversed when that election is confirmed. Goodell and Vähämaa [17] find similar results too. Similarly, more than a particular party prevailing, investors are more interested in avoiding the entrenchment of power since the results suggest that they become optimistic when a change in the ruling party takes place but become pessimistic when there is power continuity in the White House.
Ajjoub et al. [18] discuss the impact of social media activities of political leaders that can cause stir in the stock market. Precisely, the study explores the influence of US President Donald Trump’s tweets on stock prices. The findings underline that the positive tweets about media firms positively influence abnormal returns, and such tweets are more impactful on investors’ mind than negative and neutral tweets. Moreover, the influence of positive tweets on the stock prices of media firms appears to significantly stronger after President Trump’s election than the similar impact before his election as the US president. Notably for non-media firms, the study underpins even more pronounced impact of tweets on stock prices, particularly when a tweet has a negative connotation and investors sentiment is adverse. Specifically, negative tweets cause negative abnormal returns which are more influential on the first day than neutral and positive tweets, however, this effect partially reverses the next day, possibly due to the self-correcting mechanism of the stock market for an initial overreaction. Furthermore, whenever the President posts a tweet carrying a negative sentiment about a non-media firm in which he reiterates news about the firm that was previously made public, the negative abnormal return appears to be ignited not only by the content of information contained in the news release, but also by the President’s attitude towards the issue or hatred towards the firm.
Goodell and Bodey [19] underline that as the likely winning candidate in the US elections becomes obvious, the uncertainty diminishes. However, markets react unfavourably, and stocks become undervalued (lower P/E ratio). In another study, Goodell and Vähämaa [17] have identified developing of certain patterns of investors’ expectations amidst market uncertainties regarding future macroeconomic policy under the new US government.
Based on the above review of literature, the following two hypotheses have been formed:
H1: The victory of Republicans in the US presidential elections impact on stock market risk – return dynamics.
H2: The victory of Democrats in the US presidential elections impact on stock market risk – return dynamics.
3. Research Design
The current study research is based on the secondary data analysis. The historical data of changes in companies stock prices and the dynamics of the market index has been taken from S&P 500 database and annual reports of top fifty biggest U.S. companies belonging to different industrial sectors of economy. All secondary data was taken for four previous periods of presidential election in U.S. The time scale of collected data is starting from 2003 till 2017 having an interval of one year between each of the four election periods. Therefore, each one of those four periods have been divided as: the year of pre-election campaign; the election year; and the post-election year period.
This data four periods are: First period (2003, 2004, 2005); Second period (2007, 2008, 2009); Third period (2011, 2012, 2013); and Fourth period (2015, 2016, 2017).
Multivariate ordinary least square regression analysis models have been applied for the analysis purpose.
Yit = αit + βitΣXit + €it
Y = Predicted variable, X=predicting variable, α = Intercept term, €= Stochastic error term, t=one year time, and i=sample firm (unit of analysis).
Table 1: Description of Variables description
| Variable | Label | Formula/Definition | Variable | Label | Formula/Definition |
| Annualized Firm Stock Return | AnnulRetFirm | (1+Daily Stock Return)365 -1
|
Annualized Market Return | MarktAnnualRET | (1+Daily Market Return)365 -1
|
| Systematic Risk | ToTSysRisk | Beta times annualized market risk | Annualized Market Risk | TOTRISKMark | Daily market risk times square root of 365 days |
| Unsystematic Risk | ToTUnsysRisk | Total annualized risk minus total systematic risk
|
Jensen’s Alpha | JenAlpha | Relative performance of firm stock return in comparison to the minimum expected return. |
| Risk Adjusted Annualized Return | RETToRISKFirm | Return on investment earned per unit of risk taken. | Market Return to Risk Rate | RETtoRISKMark | Return on index per unit of risk taken. |
| Effective Corporate Tax | ETR | The ratio of actual amount of corporate tax paid by a company by the profit before tax, each year. | Debt Tax Shield | NLDTS | Potential addition to the firm value by leverage. |
| Unlevered Return | UnleverRet | Implied rate of return a company expects to earn on its assets, without the effect of debt. | Total Debt | NLofDebt | Natural logarithm of total debt |
| Return on Capital Employed | ROCE | Financial ratio measuring profitability and efficiency of capital employed. | Return on Equity | ROE | Financial ratio measuring profitability and efficiency of capital employed. |
| Total Asset | NLASSETS | Natural logarithm of total assets |
4. Research Findings
Table 2 highlights First period (2003, 2004, 2005) of elections won by the Republicans. As the Market Annualized Return increases, the Annualized Return (AnnulRetFirm) of firms rises too, however, Risk Adjusted Annualized Return (RETToRISKFirm) is affected negatively. Similarly, Jensen’s Alpha (JenAlpha), measuring over/under-performance in comparison to the minimum expected return, affects both predicted variables- AnnulRetFirm and RETToRISKFirm positively. RETtoRISKMark, measuring risk adjusted market return, positively impacts both predicted variables. Interestingly, TOTRISKMark and ToTSysRisk affects both dependent variables positively, whereas ToTUnsysRisk and UnleverRet have the negative impact on the same variables. Firms having higher level of leverage (NLofDebt) negatively impacts AnnulRetFirm.
Table 2: Effect of Predicting variables on ‘Annualized Return’ and ‘Risk Adjusted Annualized Return’ for the ‘First period’ (2003, 2004, 2005) of US Presidential election won by the Republican Party
| Dependent Variable | Annualized Return
(AnnulRetFirm) |
Risk Adjusted Annualized Return (RETToRISKFirm) |
| (Constant) | -0.248 (-0.328) | -0.247 (-0.266) |
| MarktAnnualRET | 4.931 ** (2.179) | -4.018* (-1.489) |
| CJenAlpha | 2.533 *** (36.572) | 2.565 *** (32.656) |
| RETtoRISKMark | 1.361 *** (3.385) | 1.173 ** (2.377) |
| TOTRISKMark | 9.286 ** (2.122) | 8.911 * (1.534) |
| ToTSysRisk | 3.836 ** (2.117) | 3.586 * (1.467) |
| ToTUnsysRisk | -5.792 *** (-6.674) | -5.701 *** (-5.422) |
| UnleverRet | -1.962 ** (-2.045) | -1.758 *(-1.557) |
| D2E | -0.001 (-0.782) | -0.005 * (-1.464) |
| NLofDebt | -0.068 ** (-2.231) | -0.021 (-0.204) |
| ROE | 0.023 (0.627) | 0.426 *(1.373) |
| ROCE | 1.09 (1.194) | 0.270 (0.232) |
| ETR | -0.019 (-0.234) | 0.028 (0.198) |
| NLDTS | -0.061 * (-1.87) | 0.000 (0.656) |
| NLAssets | 0.000 (0.916) | -0.045 (-0.435) |
| R-Square | 0.939 | 0.928 |
| Durbin-Watson Test | 1.863 | 1.714 |
| Number of Observations | 150 | 150 |
Significance level *** p<0.01; ** p<0.05; p* <0.10.
Table 3 highlights Second period (2007, 2008, 2009) of elections won by the Democrats. Similarly, Jensen’s Alpha (JenAlpha), measuring over/under-performance in comparison to the minimum expected return, affects both predicted variables- AnnulRetFirm and RETToRISKFirm positively. ToTUnsysRisk and NLAssets affect RETToRISKFirm negatively and positively, respectively.
Table 3: Effect of Predicting variables on ‘Annualized Return’ and ‘Risk Adjusted Annualized Return’ for the ‘Second period’ (2007, 2008, 2009) of US Presidential election won by the Democratic Party
| Dependent Variable | Annualized Return
(AnnulRetFirm) |
Risk Adjusted Annualized Return (RETToRISKFirm) |
| (Constant) | 0.006(0.025) | 0.409(0.687) |
| MarktAnnualRET | 0.001(0.013) | 1.822(1.373) |
| JenAlpha | 0.247*** (32.781) | 1.693*** (23.685) |
| RETtoRISKMark | 0.001(0.031) | -0.323(-0.643) |
| TOTRISKMark | 0.001(0.016) | -0.798(-1.267) |
| ToTSysRisk | 0.000(0.001) | -0.231(-0.511) |
| ToTUnsysRisk | -0.000(-0.016) | -1.221*(-1.598) |
| UnleverRet | -0.002(-0.085) | -0.291(-0.707) |
| D2E | 0.013(0.234) | -0.002(-0.242) |
| NLofDebt | 0.002(0.119) | -0.233(-0.779) |
| ROE | -0.013(-0.113) | 0.070(0.309) |
| ROCE | 0.006(0.213) | -0.795(-0.731) |
| ETR | -0.004(-0.113) | 0.250(0.319) |
| NLAssets | -0.00(-0.026) | 0.318*(1.616) |
| NLDTS | -0.000(-0.011) | -0.071(-0.341) |
| R-Square | 0.756 | 0.894 |
| Durbin-Watson Test | 1.821 | 1.846 |
| Number of Observations | 150 | 150 |
Significance level *** p<0.01; ** p<0.05; p* <0.10.
Table 4 highlights Third period’ (2011, 2012, 2013) of elections won by the Democrats. As the MarktAnnualRET, JenAlpha and RETtoRISKMark increase, the Annualized Return (AnnulRetFirm) and Risk Adjusted Annualized Return (RETToRISKFirm) of firms rise too. Similarly, TOTRISKMark affect both predicted variables positively. ToTSysRisk and ToTUnsysRisk affect AnnulRetFirm positively. However, ToTUnsysRisk affects RETToRISKFirm negatively.
Table 4: Effect of Predicting variables on ‘Annualized Return’ and ‘Risk Adjusted Annualized Return’ for the ‘Third period’ (2011, 2012, 2013) of US Presidential election won by the Democratic Party
| Dependent Variable | Annualized Return
(AnnulRetFirm) |
Risk Adjusted Annualized Return (RETToRISKFirm) |
| (Constant) | 0.006 (0.011) | 0.328 (0.792) |
| MarktAnnualRET | 2.111*** (2.051) | 1.838** (1.953) |
| JenAlpha | 2.111*** (34.123) | 3.175*** (30.802) |
| RETtoRISKMark | 0.983*** (6.195) | 0.158** (0.805) |
| TOTRISKMark | 0.451** (2.071) | 1.77** (2.215) |
| ToTSysRisk | 0.012** (2.042) | -0.386 (-0.728) |
| ToTUnsysRisk | 0.211*** (8.021) | -5.851*** (-7.037) |
| UnleverRet | 0.021** (2.032) | -0.161* (-1.311) |
| D2E | -0.211*** (-12.025) | -0.121** (-2.277) |
| NLofDebt | 0.001 (0.011) | -0.441* (-1.574) |
| ROE | -0.003 (-0.019) | -0.293 (-1.161) |
| ROCE | -0.005 (-0.058) | 0.684*** (4.628) |
| ETR | 0.000 (0.147) | 0.036* (1.318) |
| NLASSETS | 0.036** (2.021) | 0.307*** (8.474) |
| NLDTS | -0.001 (-0.121) | 0.107* (1.407) |
| R-Square | 0.861 | 0.779 |
| Durbin-Watson Test | 1.981 | 2.021 |
| Number of Observations | 150 | 150 |
Significance level *** p<0.01; ** p<0.05; p* <0.10
Table 5 highlights Fourth period (2015, 2016, 2017) of elections won by the Republicans. The JenAlpha affect the Annualized Return (AnnulRetFirm) and Risk Adjusted Annualized Return (RETToRISKFirm) of firms positively. Similarly, RETtoRISKMark affects RETToRISKFirm positively. ToTUnsysRisk affects RETToRISKFirm negatively. However, TOTRISKMark, ToTSysRisk, UnleverRet, D2E, and NLofDebt affect neither of the predicted variables significantly.
Table 5: Effect of Predicting variables on ‘Annualized Return’ and ‘Risk Adjusted Annualized Return’ for the ‘Fourth period’ (2015, 2016, 2017) of US Presidential election won by the Republican Party
|
Dependent Variable |
Annualized Return (AnnulRetFirm) |
Risk Adjusted Annualized Return (RETToRISKFirm) |
| (Constant) | 0.000(0.001) | 0.902(0.936) |
| MarktAnnualRET | 0.000(0.001) | -0.692(-0.514) |
| JenAlpha | 2.345*** (52.221) | 1.832*** (32.372) |
| RETtoRISKMark | 0.001(0.018) | 0.353**(2.022) |
| TOTRISKMark | 0.000(0.011) | -2.557(-0.556) |
| ToTSysRisk | 0.002(0.071) | 1.028(1.114) |
| ToTUnsysRisk | 0.002(0.083) | -2.194*** (-3.005) |
| UnleverRet | -0.021(-0.116) | 0.03(0.358) |
| D2E | 0.021(0.814) | -0.009(-0.843) |
| NLofDebt | 0.022(1.011) | -0.101(-0.412) |
| ROE | -0.034(-1.221) | 0.122(0.754) |
| ROCE | -0.01(-0.016) | -2.121*(-1.548) |
| ETR | -0.002(-0.029) | -0.349(-0.809) |
| NLAssets | -0.001(-0.018) | 0.039(0.222) |
| NLDTS | 0.000(0.002) | 0.065(0.388) |
| R-Square | 0.871 | 0.823 |
| Durbin-Watson Test | 1.981 | 2.021 |
| Number of Observations | 150 | 150 |
5. Conclusion
The current study aims to investigate if there are any associations between association the U.S. presidential elections and the stock market reactions and if the election of the certain political party affects the risk-return dynamics in the USA. The study finds that there is a strong relationship between the U.S. presidential election and sock return fluctuations, in general. Interestingly, the unsystematic risk has affected the sample companies’ risk adjusted return inversely, whereas the systematic risk has been found to be positively associated with both annualized return and risk adjusted annualized return. Overall, the current study concludes that higher returns are accompanied by higher risks and the US presidential elections do make significant impact on stock markets’ risk – return dynamics.
The study concludes that whenever the Republicans come in power, stock returns, adjusted as well as unadjusted by risk, improve as the firms over-perform in comparison to the minimum expected return and overall risk in the market increases. However, as the market return increases, the unadjusted firm returns increase however the risk adjusted returns decline. Interestingly, both total risk and market risk influence both risk adjusted as well as risk unadjusted returns positively, however, the firm specific risk affect both types of returns negatively.
Similarly, the study concludes that whenever the Democrats come in power, the market return related variables have almost same positive effects on both risk adjusted as well as risk unadjusted returns, however, the unsystematic risk, unlike in the case of Republicans, affects both risk adjusted as well as risk unadjusted returns positively.
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