Elections, Political Control and Duration of Stock Market ...kuwpaper/2018Papers/201810.pdf · presidential elections can affect the timing of turning points of the U.S. stock market

Elections, Political Control and Duration of Stock Market Cycles

Fan Wang

Abstract

This study uses duration analysis to investigate whether the occurrence and the outcome of

presidential elections can affect the timing of turning points of the U.S. stock market cycle.

Results suggest that political alignment between the White House and the Congress (political

control) plays an important role in the timing of turning points relative to the elections.

Specifically, our estimates show that the increased hazard for a bear market prior to an election

predicted by our Hypothesis One is only found to be significant when political control is absent

or when the incumbent is a Republican. However, the predicted rise in the hazard for a bull

market in the period immediately after an election is not found in our data. In fact, the estimates

reveal a smaller probability for a market peak to occur in the post-election period than at other

times if the party of president elected did not control the Congress. A further examination of the

post-election effects provides evidence that is consistent with our Hypothesis Two that there is

no difference in the likelihood of a peak or trough after the election of a Democratic president as

compared to other times. Furthermore, the estimates show that market troughs are less likely to

occur in the wake of a Republican presidential victory than at other times and political control

attenuates this post-Republican effect. Finally, although the implied post-Republican surge in the

hazard for a bull market is not found in our data, political control does seem to boost the hazard

for a bull market after an election of a Republican.

1. Introduction

"By the Law of Periodical Repetition, everything which has happened once must happen again, and again, and

again -- and not capriciously, but at regular periods, and each thing in its own period, not another’s and each

obeying its own law... The same Nature which delights in periodical repetition in the sky is the Nature which

orders the affairs of the earth. Let us not underrate the value of that hint." -- Mark Twain

Every four years, money and power collide at the intersection of Wall Street and

Pennsylvania Avenue. In fact, some of the most interesting historical patterns in the Stock

Trader’s Almanac relate to the occurrence and the outcome of presidential elections in the United

States. Over the years, academics and market pundits have conducted numerous studies on the

subject of the election cycles in an attempt to make a better prediction of future market trends. It

has been found that the U.S. stock market generally tends to ascend with a coming election and

descend once the election is over. Historically, returns in the U.S. stock market, on average, are

higher during Democratic presidencies than during Republican presidencies. Some suggest that

these periodic patterns in the stock market are the reflection of theories of political business

cycles in the real economy. It is widely accepted that real economy affects stock market as stock

prices reflect investors’ forecasts of the future state of economy and firm. Since a major factor

that affects real economy is the economic policies of an incumbent government, its strategic

decision for reelection and/or partisan preferences could and should affect stock market

movement. Theories of political business cycles predict that the quadrennial election cycle in the

United States could affect the timing of the peaks and troughs of the U.S. business cycles. For

instance, opportunistic political business cycle theories suggest that, compared to other times, a

business trough is more likely in the period before an election as an incumbent attempt to

maximize the chance of reelection, and a business peak follows soon after an election as pre-

election stimulus is reversed. Alternatively, partisan political business cycle theories suggest that

the likelihood of a peak or a trough following a presidential election depends upon which party

was victorious in an election. For example, rational partisan theory (Alesina 1987) suggests that

a business peak is more likely to occur in the wake of a Republican presidential victory, while a

business trough is less likely to occur after a Republican has won a presidential election than at

other times.

One critical task for all investors is to predict the future market direction and then decide

when to enter or exit the market. It is impossible for one to predict future market movement

correctly all the time, but that doesn’t mean the stock market doesn’t have patterns that could

meaningfully add to investors’ profits. That said history can be a good guide and a helpful tool in

considering entry and exit points in the stock market. The importance of the presidential

elections in the U.S. financial markets has long been recognized by financial intuitions. In a

client note, Goldman Sachs offers “3 Reasons Why US Investors Should Take Election Cycles

Very Seriously.” First, the political stakes in presidential, parliamentary, or legislative elections

often translate into changes in policies that can reshape the economic environment. Second, the

regularity with which elections take place in most countries may give place to cyclical patterns in

government and investment behavior. And third, elections can markedly increase political and

social uncertainty. These three factors have the potential to affect all asset classes, especially

equities, given their strong sensitivity to changes in the economic outlook. (Business Insider,

February 2012)

Given the close tie between real economy and stock market, it is natural to wonder will

the quadrennial elections can affect the timing of peaks and troughs of stock market cycles in the

United States as suggested by the PBC theories? Specifically, we are trying to answer the

following questions: Whether the U.S. stock market is more likely to reach a trough (the

beginning of a bull market) in period leading up to an election and the market is more likely to

reach a market peak (the beginning of a bear market) in period shortly after an election? Whether

there is any party difference in the hazards?

Previous studies on the subject of election cycles in the U.S. stock market only address

the timing issue indirectly by focusing on the amplitude of returns and volatilities before and

after the elections or across the tenure of different parties. In this paper, we provide a more direct

test of the temporal links between the political event and turning points in the U.S. stock market.

Duration analysis is used to test whether the likelihood of the occurrence of a turning point in the

U.S. stock market (that is, either the end of a bear market or the end of a bull market) can be

significantly affected by the occurrence and the outcome of a primary election.

Duration analysis is well suited for analyzing the temporal links between elections and

stock market turning points. It allows for directly testing the determinants of the likelihood of the

http://www.businessinsider.com/goldman-sachs-3-reasons-investors-us-election-cycle-2012-2

http://www.businessinsider.com/goldman-sachs-3-reasons-investors-us-election-cycle-2012-2

end of a market cycle phase in any period conditional upon the phase lasting up until that period.

The determinants of the timing of peaks and troughs that we focus on in this study are the

occurrence and the outcome of elections. Duration analysis enables us to estimate the effect of

elections on the likelihood of the end of a stock market cycle phase holding constant other

factors. In particular, duration analysis controls for duration dependence that arises when there is

a changing probability of the end of a stock market cycle as the cycle itself progresses.1

Results presented in the study suggest that political control for the Congress has an

important role in the timing of turning points relative to the elections. The pre-election surge in

the hazard for a bear market predicted by Hypothesis One is found to be significant only when

political control is absent for the incumbent. We do find, however, a significant increase in the

likelihood of the end of a bear market in the 24-month period and the 16-month period before an

election when the incumbent is a Republican, even without controlling for political control. On

the other hand, the predicted post-election surge in the hazard for a bull market in the period

immediately after an election is not found in our data. In fact, after controlling for political

control, the estimates indicate a smaller hazard for a bull market in the period immediately after

an election if the party if the new president did not have the complete control of the Congress.

A further examination of the post-election effects by disaggregating post-election periods

according to the come out of the elections provides evidence that is consistent with Hypothesis

Two. The statistically insignificant coefficients on the Democratic covariates indicate that there

is no difference in the likelihood of a peak or trough after the election of a Democratic president

as compared to other times. However, estimates on the coefficients on the Republican covariates

indicate that a market trough is significantly less likely to occur in the wake of a Republican

presidential victory than at other times. Meanwhile, political control is found to attenuate this

post-Republican effect. Alternatively, the implied post-Republican surge in the hazard for a bull

market is not found in our data even though control of the Congress seems to exacerbate the

hazard for a bull market after an election of a Republican.

1 Various studies have provided evidence of duration dependence in stock market. For example, Zhou and Ridgon

(2011) find evidence of negative duration dependence in all samples of bull markets and evidence of positive

duration dependence in complete, peacetime and post-World War I sample of bear markets. Using a duration-

dependent Markov-switching model, Maheu and McCurdy (2000) find declining hazard functions (negative duration

dependence) in both the bull and bear market states using monthly data from 1834-1995.

In the next section of the paper, we provide a brief review of related literature and offer our

hypotheses. The empirical approach used to test our hypotheses is discussed in Section 3, which

is followed by the empirical results presented in Section 4. Section 5 presents the results when

political control is considered. Finally, before concluding the study in Section 7, we conduct a

robust analysis of our results in Section 6.

2. Related Literature and Our Hypothesis

2.1 Related Literature

Based on their assumptions across different dimensions, theories of political cycles can be

classified into a two by two matrix. One of the dimensions concerns the nature of the economy

itself. For example, the traditional models in the early literature, such as that by Nordhaus

(1975), Lindbeck (1976) and Hibbs (1977), assume that the economy is characterized by a stable

inflation-output tradeoff, policy-makers have a direct control over inflation, and inflation

expectations are adaptive. More recent work expands the early studies by incorporating rational

expectations into their models. The principal assumptions of Persson and Tabellini (1990),

Rogoff and Sibert (1988), Rogoff (1990) and Alesina (1987), for example, are that economic

agents are forward-looking and make decisions based upon all information available to them at

the time. The connection between policy and outcome becomes more tenuous under these

rational expectations assumptions than under the traditional assumption of a stable Phillips

curve. In particular, there is a little scope for pre-election stimulation of the aggregate economy

and the post-election effects are more short-lived when people are rational and forward-looking

than when there is a stable Phillips curve in the traditional models.

The motivation of policy-makers represents another important dimension along which

models of political business cycles can be categorized. Opportunistic political business models,

such as Nordhaus (1975), assume that the goal of all policy-makers is to maximize the chance to

be reelected and policy is used towards this end. In the rational opportunistic political business

model of Persson and Tabellini (1990), the forwarding-looking behavior of economic agents

mitigates the extent to which the economy can be manipulated by policy and makes the voters’

goal to elect the most “competent” candidate regardless of ideology.

Instead of trying to be reelected, the goal pursued by policy-makers in partisan political

business cycle models is to pursue their political ideology. In the work of Hibbs (1977, 1987), in

which politicians can exploit a stable output-inflation tradeoff, this leads to differences across the

tenure of left-wing (Democratic) and right-wing (Republican) governments. The rational partisan

theory of Alesian (1987) preserves the assumption of policy-makers pursuing ideological

motives but tempers their ability to realize their goals by modeling an economy characterized by

rational wage-setters who are temporarily bound by nominal contracts. In the model, wages are

set equal to expected inflation. In the period before an election, the expected inflation is a

weighted average of the likelihood of the election of the party more sensitive to costs of inflation

(the Republicans) and the party less sensitive to inflation’s costs (the Democrats). The election

outcome determines the actual inflation rate and therefore whether real wages are unexpectedly

high (due to a Republican victory) and there is a contraction or whether real wage is

unexpectedly low (due to a Democratic victory) and there is an expansion. The length of the

deviation of output from its natural rate in the model is the length of the wage contract, not the

entire tenure of the administration as the Hibbs’ model suggests.

These theories present different implications regarding the temporal relationship between the

elections and the timing of turning points in business cycles. The opportunistic political business

cycle theory predicts an increased likelihood of a business trough (i.e. the end of a contraction)

with the coming of an election. It also predicts that the onset of contraction (i.e. a business cycle

peak) to offset the pre-election simulative policy is more likely following an election than at

other times. These predictions stand regardless of presidents’ partisanship. Alternatively, the

party in power is the key to the timing of stock market cycle turning points drawn from the

insights of the partisan theory. Rational partisan predicts that the likelihood of a business cycle

peak (trough) marking the end of a stock market expansion (contraction) is higher after the

election of a Republican president than at other times and there is no difference in the likelihoods

after the election of a Democratic president as compared to other times.

Klein (1996) first study the predictions from the political business cycle theories by using

the dates of turning points of the United States business cycles identified by the National Burau

of Economic Research. His results show a strong support for the post-election downturn

predicted by opportunistic political business cycle theories and there is evidence supporting an

increased likelihood of the end of a contraction in the two-year period before an election only

when the president is a Democrat. A closer examination of the post-election effect in his study

shows that consistent with rational partisan theory, there is a greater (smaller) likelihood of the

end of an expansion (a contraction) occurring in any given month in periods following

Republican presidential victories than at other times.

Alongside with the study on politic business cycles, there are increasing researches focusing

on the elections and the stock market. On one hand, more and more studies find that stock

market performance has an important role in predicting the outcome of presidential elections.

Chan and Jordan (2004) find that the equity market’s performance for ten months prior to an

election is a better predictor than GDP growth of the incumbents’ election results in recent years.

Prechter et al (2012) find that compared to GDP, inflation and unemployment rate, stock market

performance is a more powerful predictor for the incumbent’s reelection bids. D�̈�pke and

Pierdzioch (2006) find that stock market returns affect the popularity of the German government.

On the other hand, since new information can be reflected quickly in the stock prices, it is easier

for an incumbent to generate a stock market expansion than to change the course of the economy

before an election. Stock returns and return volatility also reflect investors’ perceptions about the

future course of the economy which depends on the ideological composition of the government if

partisan politics is in effect. In view of these arguments, whether electoral cycles or differences

in partisan politics exist in returns and/or volatility has been studied extensively. Allvine and

O’Neill (1980) conclude that stock prices rise relative to trend over the two years prior to a

presidential election. Lobo (1999) finds that stock returns are lower, and volatility is higher in

election years relative to nonelection years. Pantzalis et al. (2000) find positive abnormal returns

during the two-week period prior to the election week of thirty-three countries in their sample.

Herbst and Slinkman (1984), Huang (1985), Gartner and Wellershoff (1995, 1999) all find

evidence in support of a four-year presidential election cycle in the United States.

There are also differences in returns and volatility along the partisan lines. Riley and

Luksetich (1980) and Hobbs and Riley (1984) find that stock returns are higher under

Republican administrations in the United States, whereas Huang (1985) and Gartner and

Wellershoff (1995) are unable to find significant differences. Johnson et al. (1999) fail to find

any differences between Republican and Democratic presidential administrations for an index of

large-capitalization stocks, but they do find that small-capitalization stocks perform significantly

better during Democratic administrations, and the debt market performs significantly better

during Republican administrations. Lobo (1999) confirms the finding for the small-cap stocks

and also finds that the jump risk obtained from the volatility of the stock market is higher during

Democratic administrations. Santa-Clara and Valkanov (2003) discover that excess returns for

the value-weighted and equal-weighted portfolios are 9% and 16% higher, respectively, under

Democratic than Republican administrations. Vuchelen (2003) presents evidence that the

ideological composition of the government has a significant effect on the Belgian stock market.

Fuss and Bechtel (2008) show that small-firm stock returns were positively (negatively) linked to

the probability of a right- (left-) leaning coalition winning the election in Germany. Finally,

Siokis and Kapopoulos (2007) find that different political regimes affect the volatility of the

stock market index in Greece.

2.2 Our Hypotheses

The aforementioned studies point out that the occurrence and the outcome of presidential

elections affect the timing of turning points of the U.S. business cycles, and presidential elections

affect stock market performance. Existing studies, however, fail to investigate the important

potential link between the quadrennial election cycle and the timing of the turning points (peaks

and troughs) in the U.S. stock market. Based on the existing literature, we hypothesize the

following:

Hypothesis One: Compared to at other times, the likelihood of a market trough (the end of a

bear market) is higher in the period leading up to an election; and the likelihood of a market peak

(the end of a bull market) is higher in the period shortly after an election.

Hypothesis Two: The likelihood of the end of a bull market (a bear market) is higher (lower)

in the wake of a Republican election victory than at other times. There is, however, no difference

in the likelihood of a peak or trough after the election of a Democratic president as compared to

other times.

3. Empirical Approach

The timing of turning points of the stock market cycles relative to the quadrennial

presidential elections in the U.S. lends itself to an empirical investigation using duration analysis.

The data used in duration analysis consist of spells. In our data, a spell represents the number of

months in either a bear market or a bull market. The focus of duration analysis is the hazard

function. The hazard function at time 𝑡, ℎ(𝑡, 𝑥(𝑡)), is an estimate of the probability of the

completion of a spell during the time interval (𝑡, 𝑡 + 𝑑𝑡), given that the spell has lasted up until

time 𝑡. We estimate the hazard function for the probability of a peak (trough) in the U.S. stock

market during the next month given that the market has been in a bull (bear) market up until the

beginning of that month. The hazard function allows for duration dependence if its value at any

moment is a function of the time already spent in a spell. The hazard function may shift due to

exogenous factors, represented by the vector 𝑥(𝑡), which are called covariates. In a continuous

time framework, the hazard function is defined as

ℎ(𝑡, 𝑥(𝑡)) = lim𝑑𝑡→0

Pr (𝑡 ≤ 𝑇 < 𝑡 + 𝑑𝑡|𝑇 ≥ 𝑡, 𝑥(𝑡))

𝑑𝑡

The hazard function can be understood as the probability of a turning point in the short

interval 𝑑𝑡 after 𝑡, conditional on the current phase of the business cycle having lasted until

time 𝑡.

There are various potential candidates for the functional form used to implement this

analysis. The focus of attention in this study is the effect of the election covariates on the hazard

rather than the estimation of the duration dependence of expansions or contractions. Therefore,

we estimate the Cox proportional hazard model. Cox model factors the hazard into an arbitrary

and unspecified baseline hazard, ℎ0(𝑡) , and a function that depends upon a vector of explanatory

variables, 𝑥(𝑡), and the associated vector of coefficients, 𝑆, as follows;

ℎ(𝑡, 𝑥(𝑡), 𝛽, ℎ0) = ℎ0(𝑡) exp(𝑥(𝑡)𝛽)

This specification satisfies the requirement of non-negativity of the hazard without

imposing any restrictions on the coefficients 𝛽. The exponent of the coefficient on pre-election

or postelection covariates can be interpreted as the shift of the hazard during the relevant period

as compared to the other times. 2

The focus of this study is a set of covariates representing specified periods before or after

elections. These pre-election and post-election periods are identified by dummy variables that

enter as time-varying covariates, that is, covariates that can change over the course of a spell.3

Each of these covariates represents one of three different time frames and correspondingly is set

equal to one in the eight-month, sixteen-month, or twenty-four-month period either before or

after an election. 4 The use of different time frames for the covariates allows for investigation of

the length of the period of the political effect on the hazard. The coefficients across different

specifications of time frames are directly comparable since the hazard is the estimate of the

likelihood of the completion of a market cycle phase in the next month conditional on its lasting

up until that month.

To shed light on how the hazard rates may depend on the underlying state of the

economy, some specifications also include interest rates as a time-varying covariate.5 Interest

rate levels may be affected by a low-frequency component and therefore might not contain the

same information over a sample as long as ours, whereas interest rates changes are more likely to

track business cycle variation across the full sample. For this reason, we include both levels of

and changes in interest rates. Our analysis of nominal stock prices uses nominal interest rates,

2 The arbitrary baseline hazard of the Cox proportional hazard model can have any shape and it is not estimated. The

proportional hazard specification is well suited for investigating the effect of covariates on the relative risk of ending

a spell, but it does not lead itself to an investigation of duration dependence. 3 It is important to use time-varying covariates rather than simply identify those business cycles in which there was

an election with a dummy variable that serves as a constant covariate because the longer the business cycle the more

likely that there would be an election during it. Therefore, the use of elections as a constant covariate would give

rise to spurious results. 4 In an alternative specification of the postelection covariates begin in the month following the new president’s

inauguration if he represented a different political party from his predecessor and began in the month after the

election otherwise. This alternative is specification is more consistent with the notion that once in power, the

government was able to affect the economy, while the specification based only on election dates is more consistent

with the notion the effect of the election on the stock market was due to the “news” revealed by the outcome of the

election. In any case, the results using either specification were very similar. 5 Interest rates have been widely document to closely track the state of the business cycle and appear to be a key

determinant of stock returns at the monthly horizon (see, e.g., Kandel and STambaugh 1990; Fama and French

1988)

whereas our analysis of real stock prices is based on real interest rates. Both interest rates are

collected from Sheller’s database.6

The coefficients on the pre-election and post-election covariates represent the shift in a

hazard during the specified period before or after an election, respectively, holding constant the

effect of duration dependence and controlling for the underlying economy if interest rates are

included. Pre-election and post-election covariates used in tests of Hypothesis One do not

distinguish between political parties. Hypothesis One predicts positive coefficients on the pre-

election covariates in hazard estimates for bear markets. This implies that bear markets that have

lasted until the period before an election are more likely to end at that time than at other times.

The prediction of a post-election downturn from the hypothesis is consistent with positive

coefficients on post-election covariates in hazard estimates for bull markets.

The set of post-election covariates used to test Hypothesis Two includes separate

covariates for the period after the election of a Republican president and for the period after the

election of a Democratic president. Hypothesis Two suggests that the post-election effect

depends upon the party won the election. It predicts positive coefficients on the post-election

covariates representing the period following the election of a Republican in hazard estimates of

bull markets and negative coefficients on the post-election covariates in hazard estimates of bear

markets. In addition, the coefficients on the covariates that represent the period following the

election a Democratic president are expected to be indifferent from zero in hazard estimates for

both bull and bear markets.

It is reasonable to expect that the effects of presidential elections on the turning points of the

U.S. stock market may differ across sub-periods of the almost century and a half over which we

have data. Accordingly, we estimate hazard functions for the full set of 40 bears and 39 bulls in

the United States since 1872 as well as for subsamples of the 25 bears and 24 bulls in the period

after World War I and the 19 bears and 18 bulls in the period after World War II.

6 http://www.econ.yale.edu/~shiller/data.htm.

4. Empirical Results

The key data in our analysis of the link between political and financial market events are

the dates of turning points of the U.S. stock market cycle. As the name points out that a turning

point is when the stock market trend turns, i.e. goes from being generalized upward moving to

generalized downward moving or vice versa. The upward trend is commonly called a bull market

and the downward period is known as a bear market. Although bull and bear markets are

common words to investors, there is no academic general definition. For this study, we identify

the market regimes by following the algorithm developed by Pagan and Sossounov (2003). The

turning points are peaks and troughs of the identified stock market cycles.7 Since inflation has

varied considerably over our sample period, and it can be argued that drift in nominal prices does

not have the same interpretation during periods of low and high inflation. To deal with effects

arising from this, in addition to the nominal stock prices, we consider the real prices as a proxy

for the general market for robustness check. Both price series are also collected from Sheller’s

database.

Our sample begins with the peak in May 1872 and ends with the trough in February

2016. There are 39 bull markets (periods from troughs to peaks) and 40 bear markets (periods

from peaks to troughs) covered in our entire sample. The duration of each of these bears and

bulls is presented in Table l. The final two columns in the table report whether an election was

held during that phase of the market cycle. It can be seen from Table 1 that 24 of the 36 elections

held over the entire sample occurred during bull markets. This is broadly consistent with the

prediction of Hypothesis One that incumbents attempt to generate a rising market in the period

leading up to elections to increase the likelihood of being returned to office.

Table 2 provides an initial view of the timing of peaks and troughs relative to presidential

elections. We calculate the number of months since the last election for each of the turning

points by subsamples as well as by the party of the president. Except for the Democratic

administrations in the post-World War II period, the average number of months between the last

election and a market peak (the end of a bull market) is consistently smaller than the average

number of months between the last election and a market trough (the of a bear market) across

7 We account a peak and a trough as the final month of the bull market or bear market, respectively

samples and across political parties. This is consistent with the prediction that bull markets tend

to end soon after a presidential election and bear markets tend to end before presidential

elections. Hypothesis Two predicts differences across Republican and Democratic

administrations. Comparing the second and third panels of Table 1 shows that, for the full

sample and the subsample covers the post-World War I era, troughs occur later, on average, after

the election of a Republican than after the election of a Democrat. Additionally, on average,

peaks occur sooner in Republican administrations than in Democratic administrations for the

subsamples beginning after the World War I and the World War II respectively. The standard

deviations for all these statistics, however, are quite large relative to the averages.

Further information about the distribution of the number of months between market cycle

turning points and elections is provided in the histograms in Figures 1 and 2. Partially confirming

the results in Table 1, the histograms of troughs show that there are more troughs occurred in the

pre-election period than in the post-election period. Interestingly, however, the histograms of

peaks reveal that the mass points occur in the pre-election period rather than in the post-election

period. This pattern seems to be more pronounced with samples that cover only the later periods.

Nevertheless, one of the spikes in the histograms of peaks is within the 8-month period after an

election, which indicates that the period immediately after an election is still one of the periods

when peaks are most likely to occur. Histograms the differentiates across presidential parties are

presented in Figure 2. These histograms show that, compared to Democratic presidents, troughs

are more likely to occur in the pre-election period for Republican presidents. Furthermore,

despite there are more peaks in the pre-election period for Republican presidents, there is a clear

pattern that peaks are more likely to occur in the period immediately after an election of a

Republican than after the election of a Democrat.

While the above summary statistics are suggestive, more powerful tests of our hypotheses

are provided by duration analysis. Unlike the unconditional estimates in Table 2, duration

analysis allows us to test the effects of elections on stock market cycles holding constant the

effects of the underlying economy and the time on the market cycle itself. The estimates of the

Cox proportional hazard models for bear markets with the various pre-election periods serving as

time-varying covariates are presented in Table 3. Although all the coefficients on the pre-election

dummy variables are of the expected positive sign, the only instance of a coefficient that

significantly differs from zero is the 16-month covariate for the post-World War II subsample.

The robust p-value on this coefficient rises to above 0.10, however, when interest rates are

included.8 Therefore, the results provide weak evidence, at best, for the prediction of Hypothesis

One that there is an increased likelihood of a bear market ending in the period before an election

than in other periods (conditional upon its having lasted until that period). Kelvin (1996) also

finds that there is no evidence to suggest that the likelihood of an end of contraction in the

business cycle in the period before an election is significantly higher than in other periods.

Hypothesis One does not suggest that there should be a difference across political parties

in attempts to engineer a market expansion in the period before an election. It may be, however,

that the likelihood of bear market ending in the period before an election depends upon the

administration holding power at the time. This possibility is investigated in Table 4. In that table,

the covariates representing the period before an election distinguish between those times when a

Republican holds the presidency and those times when a Democrat sits in the White House. As

above, positive and significant values of the estimated coefficients would demonstrate a greater

likelihood of the end of a bear market in the period leading up to an election than at other times.

As seen in Table 4, there is no evidence that a bear market is more likely to end in the

period before an election than at other times when the incumbent is a Democrat. Interestingly,

however, the coefficients on the covariates representing the pre-election period with a

Republican incumbent are not only all of a positive sign but also those for the 16-month and 24-

month covariates are significant at the 10 percent and 5 percent levels of significance for the

subsamples. The estimates suggest that, compared to other times, an ongoing bear market is

2.20 (𝑒𝑥𝑝 (0.79)) [2.41 (exp (0.88))] times more likely to end in any given month during the 24-

month period [the 16-month period] before an election when the incumbent is a Republican for

the subsample beginning after World War I. This likelihood of the end of a market contraction in

the next month by virtue of a proximate election and a Republican president rises to

2.92(𝑒𝑥𝑝 (1.07)) [2.83(𝑒𝑥𝑝 (1.04)) ] times when the sample is constrained to the post-World

War II era. A similar finding has also been reported by Wong and McAleer (2009) that,

8 The negative coefficients on the interest rate changes indicate that the probability of a bear market to end decreases

when the interest rate changes increase. And the coefficients are significant at the 5 percent level and the 1 percent

level in the full sample and the post-World War I subsample respectively.

compared to their Democrat counterpart, Republican party tends to have greater cause to engage

in active manipulation in the equity market to win.

In addition to the prediction of a greater likelihood of a bear market ending in the period

before an election, Hypothesis One also predicts a higher likelihood of a bull market ending in

the period immediately after an election than in other periods conditional on its having lasted

until that period. This would be reflected in positive coefficients on the post-election covariates.

Table 5 presents the estimates for bull markets with the post-election periods serving as time-

varying covariates.9 Despite results demonstrate some effect consistent with the prediction, such

as the estimated coefficients on the post-election time period dummy variables representing the

8-month and 16-month periods following an election are of the expected positive sign for the

post-World War I and post-World War II subsamples and the point estimates are largest on the 8-

month covariate, none of the coefficients are statistically significant. Thus, these results provide

no strong evidence for the prediction that there is a greater likelihood of a market expansion

ending in the period immediately after an election than in other periods (conditional upon its

having lasted until period).

A change in the likelihood of a stock market cycle turning point in the period following

an election may depend on the outcome of an election. As discussed above, to test Hypothesis

Two, we use a specification that has separate time-varying covariates for the months since the

election of a Republican and the months since the election of a Democrat. Hypothesis Two

suggests that, compared to other times, there is an increased likelihood of the end of a bull

market and a decreased likelihood of the end of a bear market after the election of a Republican.

There is, however, no difference in the likelihoods after the election of a Democrat than at other

times. In other words, this implies positive coefficients on the covariates representing the period

after an election was won by a Republican and those on the covariates representing the periods

after an election that went to the Democratic candidate are insignificantly different from zero in

hazard estimates for bull markets. Alternatively, in hazard estimates of bear markets, it implies

negative coefficients on the covariates representing the period in the wake of a Republican

9 The negative coefficients on the interest rate changes seem to suggest that increase in interest rate changes not only

reduces the probability of a market trough but also the probability of a market peak.

presidential victory and the insignificant coefficients on the covariates representing the period

after a Democratic presidential victory.

Results in Tables 6 and 7 strongly support the predictions of our Hypothesis Two as

regards the effects of Democratic presidential election victories as there are no instances of a

statistically significant coefficient on the Democratic covariate. In the estimates of the hazards

for bull markets presented in Table 6, the coefficients on the covariates representing the 8-month

and 16-month periods after the election of a Republican are positive across specifications (i.e.

with and without interest rates) for both subsamples. Specifically, the coefficients on the

covariates representing the 8-month period after a Republican election victory are significant at

the 10 percent level for the post-World War II sample.10

Compared to the post-election covariates that do not differentiate between the party of the

president, the coefficients on the Republican covariates are significantly larger in size but for the

covariates representing the two-year period after an election of a Republican. As with the results

in Table 5, the coefficients are largest on covariates representing on the 8-month period

following the election of a Republican president, implying that the post-Republican effect is

largest in the period immediately after an election was won by a Republican candidate. The point

estimate suggests that a bull market is twice (𝑒𝑥𝑝 (0.66)) as likely to end within 8 months of a

Republican presidential victory as at other times in the post-World War I period, controlling for

interest rates and for duration dependence. This likelihood of the end of a bull market in the next

month rises to 2.44 (𝑒𝑥𝑝 (0.88)) when the sample is constrained to the post-World War II era.

This suggests that the post-Republican effect has become more noticeable over time.

Results presented in Table 7 for the estimates for hazard functions for bear markets

display effects consistent with our Hypothesis Two.11 The coefficients on the covariates for the

period following the election of a Republican are all of the expected negative sign and those for

the 24-month covariate are significant at the 10 percent level or higher. The coefficients on the

10 There are only two instances of a peak within 8 months of a Democratic presidential victory in the post-World

War II ear implying that the result for the post-World War II period in Table 5 is largely due to periods following a

Republican presidential victory.

11 There are insufficient observations for estimating the coefficient on covariates representing the 8-month period

after the election of a Republican president.

covariate representing the 16-month period after the election of a Republican are also found to be

significant in the full sample. The point estimates suggest that there are substantial differences in

the hazard of a market contraction between the period after an election of a Republican president

and other times. For example, a market trough is about 28 (𝑒𝑥𝑝(−1.28)) percent as likely to

occur in the 24-month period following a Republican presidential victory as at other times for the

post-World War II sample period after controlling for interest rates and for duration dependence.

5. Political Control and Duration of Stock Market Cycles

Political alignment between the White House and the Congress, another important political

factor in the U.S. stock market, is largely overlooked in the existing research when studying the

presidential election cycles in the U.S. stock market. In this section, we investigate whether

political control of the Congress attenuates or exacerbates the election effects on the likelihood

of a market peak or trough presented early in the paper. To investigate the role of political

control, we construct a dummy variable, Congress, which equals to one if the president’s party

has control (holds the majority of seats) of both the house of representatives and the house of

senate simultaneously (i.e. complete control of the legislative branch in the nation) and interact it

with the covariates representing the pre- and post-election periods. We re-estimate the

regressions presented in the early tables by controlling for political alignment between the White

House and the Congress. The new results are presented in Tables 8-12.

As seen in Table 8, after controlling for political control of the Congress, there is a

significant evidence for the prediction that there is a greater probability of an ongoing bear

market ending in the period prior to an election than at other times. Estimates on the coefficients

on the pre-election time period dummies now are not only all of the expected positive sign but

also are highly significant for covariates representing the 16-month and the 24-month periods

leading up to an election. These new estimates indicate that the pre-election effect on the stock

market cycle is largest in the two-year period before an election, controlling for interest rates and

political control for the Congress. Specifically, the estimates suggest that an enduring bear

market is 3.13 (𝑒𝑥𝑝 (1.14)) times more likely to end in any given month during the two-year

period before an election than at other time if the incumbent’s party did not control the Congress

for the entire sample. This likelihood of the end of a bear market in the next month by the virtue

of a proximate election rise to 5.87 (𝑒𝑥𝑝 (1.77)) and 6.43 (𝑒𝑥𝑝 (1.86)) when the sample is

constrained to the post-World War I era and the post-World War II era respectively.

The negative and significant coefficients for the interaction term, Election*Congress,

however, suggest that political control of the Congress weakens this pre-election surge in the

hazard for a bear market.1213 The magnitude of the coefficients shows a remarkable difference in

the pre-election hazard for a bear market between an incumbent with political control and one

without such control. For instance, going from no political control to complete political control,

there is a 97 percent reduction in the pre-election surge in the hazard for a bear market in the 24-

month period prior to an election for the post-World War II period. Moreover, the positive and

significant coefficients on the level effect of Congress imply that bear markets are more likely to

end when the White House and the Congress are controlled by the same party than at other times.

Estimates presented in Table 9 are largely parallel to the ones presented in Table 8.14

After the inclusion of political control, the estimates on the pre-election covariates become more

significant both economically and statistically. Estimates on the period dummies are all of a

positive sign with the coefficients on covariates representing a Democratic incumbent are most

significant in the full sample period and the coefficients on covariates representing a Republican

incumbent are most significant in the subsamples. These results suggest that, for both Republican

and Democratic presidents, the probability of ending an ongoing bear market before an election

is greater than at other times when the incumbents’ parties do not have the control of the

Congress.

Like the results in Table 8, the positive and significant coefficients on the political

control dummy imply that party dominance in the Congress shortens the duration of bear

12 There are insufficient observations for estimating the coefficients on interaction term, Election*Congress, for the

8-month time frame for the post-World War II period. 13 One possible interpretation for the cause of the reduction in the hazard for a bear market before an election is that

the range of policy tools available to the government to win support from voters may increase when the incumbent

has the complete control of the Congress. The president could choose policies that benefit voters more directly, such

as by increasing transfer payments, and lowering taxes prior to an election rather than trying to manipulate the stock

market. 14 There are insufficient observations for estimating the coefficients on the interaction term, Republican * Congress

for the post-World War II sample. And there are insufficient observations for estimating the coefficients on both

interaction terms when the sample is constrained to the 8-month time frame.

markets. Nevertheless, the negative coefficients on the interaction terms, Republican * Congress

and Democrat * Congress, indicate that political control of the Congress dilutes the pre-election

surge in the hazard for a bear market. Particularly, this dilution is more apparent for Democratic

incumbents. For instance, the estimates in the 16-month time frame suggest that going from no

control of the Congress to complete control of the Congress, the likelihood ending a bear market

reduces by 95 percent when the incumbent is a Democrat or cuts by 28 percent when the

incumbent is a Republican for the full sample.

In contrast to the results in Table 6, the negative coefficients on the covariates for the

post-election dummies in Table 10 suggest market expansions are actually less likely to end in

the period following an election when the newly elected president does not have the full support

from the Congress. Within any one sample period, the coefficient on the 24-month covariate is

larger than the coefficient on either the 8-month or the 16-month covariate and it is significant at

the 5 percent level for the full sample. The point estimate indicates the difference in the hazard

for a bull market between the 24-month period after an election and other periods is largest. In

the full sample period, given its survival up to that time and the absence of political control, the

likelihood of the end of a market expansion is less than 20 (𝑒𝑥𝑝 (−1.63)) percent as likely to

occur within two years following an election as at other time. The larger point estimates for the

post-World War I and the post-World War II subsamples are even more striking; the likelihood

of a market peak to occur within two years after an election is just 15 (𝑒𝑥𝑝 (−1.93)) percent as

likely as in other periods in the post-World War I period and is 13 (𝑒𝑥𝑝 (−2.02)) percent as

likely as in other periods in the post-World War II period. This suggests that the post-election

reduction in the hazard for a bull market has become more pronounced over time.

The significant and negative coefficients on the political control itself indicating that

political control of the Congress enables politicians to substitute a longer bull market when a

president has the political control for the Congress for a shorter one when the political control is

absent. Across samples and specifications, the estimated coefficients for the interaction term,

Election * Congress, remain positive and their economic and statistical significance increase as

the post-election time frame expands from 8 months to 16 months and to 24 months after an

election and as the sample is restricted from the full sample to the post-World War I subsample

to the post-World War II subsample. To give an indication of the economic significance of the

political control effect in the post-election period, the coefficient for the interaction term for the

24-month time frame for the post-World War II period is 3.91, which implies that a market peak

marking the end of a market expansion is almost 50 (𝑒𝑥𝑝(3.91)) time as likely to occur within

two years after an election if the president elected has the control of the Congress as the one

lacks of such control. Furthermore, the significant and negative coefficient on the interaction

term, Election * Congress, implies that the early finding that a bull market is more likely to end

in the post-election period can be largely explained by the period when there is no political

control for the new administration.

Estimates in Table 11 largely resemble the results reported in Table 6.15 Although the

coefficients on covariate representing the 8-month period following an election of a Republican

remain positive after controlling for political control of the Congress, there is no coefficient that

is significantly different from zero. A closer examining on the interaction term shows that,

except for the 8-month time frame for the full sample, the coefficient on the interaction term,

Republican * Congress, are positive across specifications and across sample periods. The

magnitude of estimates suggests that there are striking differences in the hazard between the

post-election period with a Republican political control and the corresponding period without

such political control. For example, the likelihood of the end of a continuing bull market is 7.54

(𝑒𝑥𝑝 (2.02)) times as high in the 16-month post-election period when a Republican president

has the political control as in the same post-election period when the president does not have

such control. Furthermore, consistent with the results in Table 10, the negative coefficient on

Congress seems to suggest that politicians may prolong the duration of a bull market when they

have control over the nation’s executive and legislative branches.

Finally, after the inclusion of political control, results presented in Table 12 reveal an

even superior evidence that market troughs are less likely to happen after the election of a

Republican president.16 Compared to the results in Table 7, the new results display a substantial

improvement in both economic and statistical significance for the estimates on the coefficients

on the post-election covariates representing a Republican election victory. The positive and

15 There are insufficient observations for estimating the coefficient on the interaction item, Democratic*Congress. 16 There are insufficient observations for estimating the coefficients on the Republican dummy and its interaction

term, Republican*Congress, for the 8-month time frame, and there are not enough observations for estimating the

coefficient on the interaction item, Democrat*Congress.

significant estimates on the interaction term, Republican*Congress, imply that political control

of the Congress diminishes the post-election reduction in the hazard for bear markets following

an election of a Republican. The point estimates show that the differences in the hazard between

the post-election periods with Republican-controlled Whitehouse and Congress and the periods

without such control are striking. For example, the point estimate for the 24-month Republican

covariate for the post-World War II sample, controlling for interest rates and for time

dependence, suggests that a market trough, marking the end of a bear market, is about 29

(𝑒𝑥𝑝 (3.37)) times as likely to occur within two years following the election of a Republican

president when Republican party holds the majority seats of the Congress as the corresponding

period when there is no political control for the president.

6. Robustness Analysis

Given our data sample spans nearly century and a half, it is possible that drift in nominal

prices does not have the same interpretation during periods of low and high inflation. To deal

with effects arising from this, we also consider real stock prices as a proxy for the general market

for our robustness check.

Like Table 1, in Table 13 we report the dates of the turning points of the market cycle

identified by using real stock prices and the duration of each of the new bears and bulls and

whether an election was held during that phase of the cycle. Again, we can see that 24 of the 36

elections held over the complete sample occurred during bull markets. This is in line with the

prediction that incumbents are likely to cause a market expansion prior to an election in order to

boost his chance to be re-elected. Similarly, Table 14 provides some simple statistics on the

timing of new peaks and troughs relative to presidential elections. Confirming with the results in

Table 2, it can be seen from Table 14, apart from the Democratic administrations in the post-

World War II period, the average number of months between the last election and a market peak

is consistently lesser than the average number of months between the last election and a market

trough across samples and across parties. This is consistent with the prediction that bull markets

tend to end soon after an election while bear markets end to end before an election. Additionally,

the second and third panels of the table display a clear pattern that, across samples, troughs

occur, on average, later after the election of a Republican than after the election of a Democrat.

And, on average, peaks occur sooner in Republican administrations than in Democratic

administrations. The standard deviations for all these statistics, however, are quite large relative

to the averages. The histograms in Figures 3 and 4 show us alike patterns in the distribution of

the number of months between market cycle turning points and election as in Figures 1 and 2.

The histograms of troughs show that, except for the Democratic presidents for the subsamples,

there are more troughs in the pre-election period than in the post-election period. And the

histograms of peaks show that there are more peaks in the pre-election period instead of in the

post-election period. Compared to Democratic presidents, peaks are more likely to occur in the

period immediately after an election of a Republican president.

Finally, the new estimates from the Cox regressions strengthen our early findings.17

Political alignment between the Whitehouse and Congress remains to be critical in the timing of

turning points relative to the elections. The predicted increase in the hazard for a bear market

prior to an election is found to be significant when the incumbent’s party does not have the

control of the Congress. We do observe, however, a significant increase in the likelihood of the

end of a bear market when the incumbent is a Republican even without control for political

alignment between the Whitehouse and the Congress. Although the new estimates on the pre-

election dummies in the hazard functions for bull markets are all of the expected positive sign,

none of the estimates significantly differs from zero. In fact, after controlling for political

control, the estimates still indicate a smaller hazard for a bull in the period immediately after an

election. A further examination of the post-election effects by disaggregating post-election

periods according to the come out of the elections provides evidence that is consistent with

Hypothesis Two. There are no instances of a statistically significant coefficient on the

Democratic covariates. Alternatively, estimates on the coefficients on the Republican covariates

indicate that a market contraction is less likely to end in the wake of a Republican presidential

victory than at other times and political control lessens this post-Republican effect. Lastly,

compared to the initial results, the positive estimates on the coefficients on covariates

representing the period following an election of a Republican are consistent with the implied

post-Republican surge in the hazard for a bull market and the coefficients on the covariates

representing the 8-month period after a Republican election victory are statistically different

17 To save the space, we did not report the new estimates in the paper. The new estimates are available upon request.

from zero. Political control, however, still is found to exacerbate the post-Republican effect in

hazard for a bull market by using the new data.

7. Conclusion

This paper provides a more direct test of the timing of stock market cycle turning points

relative to the elections than previous research which considers the amplitude of returns and

volatilities before and after presidential elections. Results from the duration analysis show that

political alignment between the White House and the Congress (political control) holds a crucial

role in the timing of peaks and troughs of the U.S. stock market cycles relative to the elections.

There is significant evidence supporting the prediction of our Hypothesis One that there is an

increased likelihood of the end of a bear market in the two-year period before an election when

the incumbents have political control of the Congress or when the incumbent is a Republican.

The prediction that there is a post-election surge in the hazard for a bull market in the period

immediately after an election, however, cannot be found in our data. In fact, our estimates

indicate a smaller probability for a market peak to occur in the post-election period than at other

times after controlling for political control. Further examination of the post-election results

provides evidence that is consistent with our Hypothesis Two that there is no difference in the

likelihood of a peak or trough after the election of a Democratic president as compared to other

times. Bear markets are less likely to end after an election of a Republican than at other times

and political control seems to diminish this post-Republican effect. Lastly, although the implied

post-Republican surge in the hazard for a bull market is not found in our data, political control

seems to intensify the hazard for a bull market after an election of a Republican.

The results presented in this paper do not provide a complete test of the election-cycle effects

in the stock market as there are other implications that cannot be addressed by using duration

analysis. The findings presented in this paper, however, undoubtedly complement the existing

literature and extend our knowledge of how presidential elections can affect the U.S. financial

markets. A better understanding of the relationship between the timing of market turning points

and political events is not only central to our understanding of the empirical relevance of

political business cycle theories in financial markets but also it could help investors to make

better investment decisions when combined with other information.

TABLE 1

DATES OF US STOCK MARKET TURNING POINTS

Trough Peak Bear Bull Bear Bull

5/1872

11/1873 4/1875 18 17 YES NO

6/1877 6/1881 26 48 YES YES

1/1885 5/1887 43 28 YES NO

6/1888 5/1890 13 23 NO YES

12/1890 8/1892 7 20 NO NO

8/1893 4/1894 8 8 YES NO

3/1895 9/1895 11 6 NO NO

8/1896 9/1897 11 13 NO YES

4/1898 4/1899 7 12 NO NO

9/1900 9/1902 17 24 NO YES

10/1903 9/1906 13 35 NO YES

11/1907 12/1909 14 25 NO YES

7/1910 9/1912 7 26 NO NO

12/1914 11/1916 24 23 YES YES

12/1917 7/1919 12 19 NO NO

8/1921 3/1923 25 19 YES NO

10/1923 9/1929 7 71 NO

6/1932 2/1934 33 20 NO YES

3/1935 2/1937 13 23 NO YES

4/1938 11/1938 14 7 NO NO

4/1942 5/1946 41 49 YES YES

2/1948 6/1948 21 4 NO NO

6/1949 1/1953 12 43 YES YES

9/1953 7/1956 8 34 NO NO

12/1957 7/1959 12 19 YES NO

10/1960 12/1961 15 14 NO YES

6/1962 1/1966 6 43 NO YES

10/1966 12/1968 11 26 NO YES

6/1970 4/1971 18 10 NO NO

11/1971 1/1973 7 14 NO YES

12/1974 9/1976 23 21 NO NO

3/1978 9/1978 15 6 YES NO

4/1980 11/1980 19 7 NO YES

7/1982 10/1983 19 15 NO NO

7/1984 8/1987 9 37 NO YES

12/1987 8/2000 4 152 NO

2/2003 10/2007 26 56 YES YES

3/2009 5/2011 17 26 YES NO

9/2011 5/2015 4 44 NO YES

2/2016 9 NO

Notes: Along a row, Bear market refers to period from peak in pervious row to trough in the next row.

Bears market refers to period from trough in that raw to prak in that row.

Date of

YES(2 ELECTIONS)

YES(3 ELECTIONS)

Duration (in months) Was an Election Held during the

TABLE 2

STATISTICS ON TIMING OF PEAKS AND TROUGHS RELATIVE TO ELECTIONS

Months Since Elections

Peaks Troughs

Av'g (s.d.)

Min. Max. Obs. Av'g (s.d.)

Min. Max. Obs.

Full Sample 23.28(14.21) 0 46 39 25.30(13.28) 2 47 40

Post WW1 23.08(15.06) 0 46 24 25.96(12.84) 4 47 25

Post WW2 25.33(16.15) 0 46 18 26.32(13.18) 4 47 19

Republican Administrations


Peaks Troughs

Av'g (s.d.)


Min. Max. Obs.

Full Sample 23.39(15.37) 0 46 23 25.80(12.51) 7 46 20

Post WW1 22.85(17.23) 0 46 13 26.50(12.48) 9 44 12

Post WW2 23.55(18.35) 0 46 11 25.67(11.49) 10 44 9

Democrat

Administrations


Peaks Troughs

Av'g (s.d.)


Min. Max. Obs.

Full Sample 23.13(12.83) 0 45 16 24.80(14.32) 2 47 20

Post WW1 23.36(12.86) 3 45 11 25.46(13.64) 4 47 13

Post WW2 28.14(12.77) 13 45 7 26.90(15.14) 4 47 10

TABLE 3

ESTIMATES OF HAZARD FUNCTION FOR BEAR MARKETS

1. Full Sample

Equation Variable 24 months 16 months 8 months

A. Election 0.298 0.189 0.189

(0.32) (0.27) (0.40)

B. Election 0.295 0.189 0.0916

(0.33) (0.28) (0.41)

Interest rates 0.035 0.010 0.072

(0.07) (0.07) (0.06)

Interest Rate Changes -0.557 -0.079 -1.068 **

(0.84) (0.66) (0.44)

2. Post-World War I


A. Election 0.407 0.395 0.183

(0.37) (0.28) (0.49)

B. Election 0.417 0.411 0.009

(0.39) (0.30) (0.46)


(0.07) (0.07) (0.07)

Interest Rate Changes -0.675 -0.234 -1.147 ***

(0.69) (0.58) (0.41)

3. Post-World War II


A. Election 0.547 0.706 * 0.726

(0.47) (0.40) (0.59)

B. Election 0.483 0.684 0.544

(0.50) (0.47) (0.66)

Interest rates -0.019 -0.041 -0.006

(0.07) (0.08) (0.06)

Interest Rate Changes -0.489 0.220 -0.654

(0.66) (0.77) (0.44)

* Significant at 90 percent level of confidence

** Significant at 95 percent level of confidence

*** Significant at 99 percent level of confidence

Dummy Variables: Months Before an Election



TABLE 4

ESTIMATES OF HAZARD FUNCTION FOR BEAR MARKETS BY PARTY

1. Full Sample


A. Republican 0.313 0.280 0.066

(0.37) (0.37) (0.47)

Democrat 0.276 0.042 0.364

(0.42) (0.43) (0.60)

B. Republican 0.302 0.028 -0.030

(0.38) (0.37) (0.48)

Democrat 0.285 0.044 0.284

(0.43) (0.43) (0.55)

Interest Rates 0.035 0.007 0.073

(0.07) (0.07) (0.06)

Interest Rate Changes -0.554 -0.060 -1.044 **

(0.85) (0.63) (0.43)

2. Post-World War I


A. Republican 0.799 * 0.893 ** 0.653

(0.47) (0.39) (0.49)

Democrat -0.113 -0.233 -0.523

(0.53) (0.58) (1.12)

B. Republican 0.786 * 0.883 ** 0.434

(0.49) (0.39) (0.50)

Democrat -0.089 -0.209 -0.846

(0.53) (0.58) (0.75)

Interest Rates 0.045 0.024 0.096 *

(0.06) (0.05) (0.06)

Interest Rate Changes -0.544 -0.157 -1.292 ***

(0.64) (0.49) (0.45)

3.Post-World War II


A. Republican 1.117 ** 1.033 * 0.458

(0.56) (0.55) (0.62)

Democrat 0.024 0.342 1.644 *

(0.59) (0.64) (0.92)

B. Republican 1.071 * 1.036 * 0.402

(0.58) (0.58) (0.69)

Democrat -0.098 0.254 1.344

(0.62) (0.70) (1.16)

Interest Rates -0.042 -0.056 -0.019

(0.05) (0.06) (0.07)


(0.63) (0.72) (0.55)

Notes: Numbers in paranthesis are robust standard errors.




Dummy Variables: Months Before an Election, By Party



TABLE 5

ESTIMATES OF HAZARD FUNCTION FOR BULL MARKETS

1. Full Sample


A. Election -0.142 -0.173 -0.096

(0.47) (0.34) (0.34)

B. Election -0.100 -0.130 -0.091

(0.48) (0.35) (0.34)

Interest rates 0.020 0.003 -0.018

(0.07) (0.09) (0.10)

Interest Rate Changes -0.829 -0.748 -0.538

(0.56) (0.68) (1.16)

2. Post-World War I


A. Election 0.311 0.100 -0.010

(0.55) (0.42) (0.48)

B. Election 0.386 0.174 -0.001

(0.56) (0.44) (0.49)


(0.07) (0.08) (0.10)


(0.63) (0.71) (1.17)



A. Election 0.323 0.137 -0.395

(0.56) (0.46) (0.51)

B. Election 0.364 0.300 -0.355

(0.56) (0.49) (0.54)


(0.06) (0.08) (0.10)

Interest Rate Changes -0.877 -1.187 0.515

(0.76) (0.74) (1.31)




Dummy Variables: Months Since an Election



TABLE 6

ESTIMATES OF HAZARD FUNCTION FOR BULL MARKETS BY PARTY

1. Full Sample


A. Republican -0.016 -0.154 -0.232

(0.48) (0.38) (0.37)

Democrat -0.533 -0.211 0.114

(1.04) (0.51) (0.44)

B. Republican 0.024 -0.120 -0.246

(0.48) (0.38) (0.38)

Democrat -0.486 -0.141 0.149

(1.06) (0.53) (0.46)

Interest Rates 0.014 0.003 -0.001

(.0.2) (0.09) (0.11)


(0.56) (0.68) (1.17)

2. Post-World War I


A. Republican 0.640 0.100 -0.381

(0.56) (0.55) (0.63)

Democrat -0.313 0.100 0.279

(1.10) (0.50) (0.48)

B. Republican 0.659 0.093 -0.488

(0.57) (0.57) (0.67)

Democrat -0.179 0.262 0.429

(1.15) (0.54) (0.53)


(0.07) (0.09) (0.11)


(0.64) (0.70) (1.15)

3.Post-World War II


A. Republican 0.914 * 0.213 0.562

(0.51) (0.64) (0.70)

Democrat 0.036 -0.198

(0.55) (0.59)

B. Republican 0.886 * 0.317 -0.602

(0.51) (0.66) (0.76)

Democrat 0.269 -0.057

(0.58) (0.67)


(0.07) (0.08) (0.12)


(0.79) (0.74) (1.32)





Dummy Variables: Months Since an Election, By Party



TABLE 7

ESTIMATES OF HAZARD FUNCTION FOR BEAR MARKETS BY PARTY

1. Full Sample


A. Republican -1.044 ** -0.757 **

(0.48) (0.38)

Democrat -0.424 -0.439 -0.161

(0.71) (0.43) (0.40)

B. Republican -0.944 * -0.813 *

(0.51) (0.45)

Democrat -0.454 -0.477 -0.166

(0.69) (0.42) (0.41)


(0.08) (0.07) (0.07)


(1.14) (0.89) (0.87)

2. Post-World War I


A. Republican -0.841 -0.811 *

(0.53) (0.48)

Democrat 0.122 -0.333 0.115

(0.66) (0.51) (0.38)

B. Republican -0.687 -0.986 *

(0.54) (0.61)

Democrat 0.043 -0.430 0.160

(0.67) (0.52) (0.41)


(0.07) (0.07) (0.07)


(0.92) (0.91) (0.87)

3.Post-World War II


A. Republican -1.012 -1.116 *

(0.75) (0.61)

Democrat 0.484 0.218 0.331

(0.60) (0.48) (0.48)

B. Republican -0.706 -1.279 *

(0.75) (0.78)

Democrat 0.308 -0.063 0.463

(0.64) (0.48) (0.50)

Interest Rates -0.018 -0.094 -0.027

(0.08) (0.10) (0.10)


(1.12) (1.53) (1.14)








TABLE 8

1. Full Sample


A. Election 0.979 * 1.064 ** 0.710

(0.54) (0.48) (0.52)

Congress 1.231 ** 1.288 *** 0.843 **

(0.51) (0.45) (0.40)

Election*Congress -0.941 -1.283 * -0.847

(0.70) (0.76) (0.88)

B. Election 1.144 * 1.089 ** 0.724

(0.67) (0.50) (0.53)

Congress 1.412 ** 1.307 *** 0.909 **

(0.65) (0.47) (0.41)

Election*Congress -1.107 -1.277 * -0.888

(0.82) (0.80) (0.79)


(0.07) (0.08) (0.07)


(1.81) (1.69) (1.19)

2. Post-World War I


A. Election 1.410 *** 1.349 *** 0.704

(0.55) (0.39) (0.57)

Congress 1.452 *** 1.283 *** 0.604

(0.54) (0.46) (0.44)

Election*Congress -1.937 ** -2.079 ** -1.309

(0.80) (1.05) (1.52)

B. Election 1.765 *** 1.466 *** 0.700

(0.65) (0.42) (0.59)

Congress 1.877 ** 1.345 *** 0.674

(0.74) (0.51) (0.45)

Election*Congress -2.397 *** -2.186 ** -1.431

(0.92) (1.08) (1.31)

Interest rates 0.103 * 0.089 0.041

(0.06) (0.07) (0.06)


(1.76) (1.57) -1.175

3.Post-World War II


A. Election 1.602 ** 1.613 *** 0.985 *

(0.68) (0.62) (0.56)

Congress 2.000 *** 1.769 *** 0.906 *

(0.66) (0.60) (0.50)

Election*Congress -2.941 *** -2.362 ***

(0.80) (0.86)

B. Election 1.862 ** 1.687 *** 0.994

(0.73) (0.64) (0.65)

Congress 2.386 *** 1.785 ** 0.929 **

(0.90) (0.79) (0.47)

Election*Congress -3.400 *** -2.518 ***

(0.96) (0.91)

Interest rates 0.053 0.029 -0.056

(0.08) (0.08) (0.07)


(2.06) (2.08) (0.93)





ESTIMATES OF HAZARD FUNCTION FOR BEAR MARKETS WITH POLITICAL CONTROL

Dummy Variables: Months Beefore an Election


TABEL 9

1. Full Sample


A. Republican 0.874 0.956 0.525

(0.67) (0.65) (0.64)

Democrat 1.178 ** 1.335 *** 1.098 *

(0.54) (0.47) (0.65)

Congress 1.235 ** 1.324 *** 0.855 **

(0.52) (0.47) (0.40)

Republican*Congres -0.573 -0.425 -0.367

(0.78) (0.84) (0.69)

Democrat*Congress -1.425 * -2.698 *** -1.504

(0.85) (0.99) (1.47)

B. Republican 1.045 0.100 0.520

(0.75) (0.64) (0.65)

Democrat 1.530 ** 1.554 *** 1.168 *

(0.71) (0.54) (0.68)

Congress 1.479 ** 1.426 *** 0.930 **

(0,68) (0.50) (0.41)

Repuglician*Congress -0.654 -0.328 -0.321

(0.85) (0.83) (0.68)

Democrat*Congress -1.856 * -2.978 *** -1.710

(1.05) (0.93) (1.30)


(0.08) (0.07) (0.07)


(1.86) (1.71) (1.39)

2. Post-World War I


A. Republican 1.679 *** 1.843 *** 1.056 **

(0.62) (0.54) (0.52)

Democrat 0.904 0.904 -0.834

(0.71) (0.63) (1.14)

Congress 1.518 *** 1.496 *** 0.662

(0.58) (0.51) (0.43)

Republican*Congres -1.375 ** 0.371

(0.68) (0.90)

Democrat*Congress -1.930 * -2.557 **

(1.04) (1.04)

B. Republican 1.935 *** 1.846 *** 1.020 *

(0.68) (0.55) (0.54)

Democrat 1.366 1.166 * -0.939

(0.87) (0.68) (0.85)

Congress 1.898 ** 1.561 *** 0.719 *

(0.75) (0.56) (0.44)

Repuglician*Congress -0.161 ** 0.495

(0.81) (0.87)

Democrat*Congress -2.501 ** -2.776 ***

(1.22) (0.99)


(0.07) (0.07) (0.06)


(1.79) (1.61) (1.11)



A. Republican 2.369 *** 2.331 *** 0.838

(0.78) (0.79) (0.66)

Democrat 0.862 0.945 1.460 *

(1.01) (1.03) (0.82)

Congress 2.288 *** 2.076 *** 0.854

(0.83) (0.75) (0.54)

Democrat*Congress -2.386 ** -2.023 **

(1.03) (0.98)

Republican 2.756 ** 2.357 *** 0.878

(0.90) (0.87) (0.69)

B. Democrat 0.775 0.873 1.506

(1.16) (1.13) (1.18)

Congress 2.754 *** 2.125 ** 0.880 *

(0.99) (0.93) (0.49)

Democrat*Congress -2.270 * -1.960 *

(1.30) (1.10)

Interest Rates -0.027 -0.016 -0.058

(0.08) (0.07) (0.07)


(2.13) (2.19) (1.08)






ESTIMATES OF HAZARD FUNCTION FOR BEAR MARKETS BY PARTY WITH POLITICAL

CONTROL



TABLE 10

1. Full Sample


A. Election -0.176 -1.015 -1.598 **

(0.65) (0.72) (0.79)

Congress -0.232 -0.552 -1.333 **

(0.38) (0.42) (0.58)

Election*Congress 0.083 1.344 2.676 ***

(0.94) (0.85) (0.97)

B. Election -0.175 -0.993 -1.634 **

(0.66) (0.72) (0.82)

Congress -0.232 -0.493 -1.310 **

(0.40) (0.44) (0.60)

Election*Congress 0.128 1.338 2.727 ***

(0.07) (0.85) (0.99)

Interest rates -0.001 0.001 0.006

(0.07) (0.09) (0.10)


(0.83) (0.66) (1.22)

2. Post-World War I


A. Election -0.359 -1.264 -1.842

(1.03) (1.11) (1.17)

Congress -0.592 -1.002 * -1.794 **

(0.46) (0.54) (0.81)

Election*Congress 1.105 2.172 * 3.325 **

(1.16) (1.26) (1.47)

B. Election -0.317 -1.227 -1.929

(1.03) (1.12) (1.21)

Congress -0.550 -0.850 -1.729 **

(0.52) (0.60) (0.87)


(1.16) (1.26) (1.47)


(0.07) (0.08) (0.11)


(0.78) (0.69) -1.39

3.Post-World War II


A. Election -0.241 -1.165 -1.795

(0.98) (1.10) (1.16)

Congress -0.721 -1.400 -1.916 *

(0.63) (0.91) (1.16)

Election*Congress 1.193 2.721 * 3.321 *

(1.37) (1.59) (1.79)

B. Election -0.221 -1.076 -2.022

(0.96) (1.10) (1.29)

Congress -0.611 -1.135 -1.972 **

(0.69) (0.94) (0.82)


(1.33) (1.44) (1.61)


(0.07) (0.07) (0.10)


(1.02) (0.84) (1.70)




ESTIMATES OF HAZARD FUNCTION FOR BULL MARKETS WITH POLITICAL CONTROL




TABEL 11

1. Full Sample


A. Republican 0.188 -0.504 -0.964

(0.60) (0.67) (0.74)

Democrat -0.514 -0.154 0.227

(1.04) (0.53) (0.48)

Congress -0.181 -0.317 -0.506

(0.37) (0.38) (0.41)

Republican*Congres -0.351 0.595 1.214

(1.01) (0.87) (0.85)

B. Republican 0.184 -0.504 -1.155

(0.60) (0.67) (0.88)

Democrat -0.512 -0.128 0.319

(1.06) (0.54) (0.50)

Congress -0.192 -0.258 -0.455

(0.39) (0.41) (0.42)

Repuglician*Congress -0.280 0.622 1.424

(0.08) (0.86) (0.95)

Interest Rates -0.007 0.004 0.059

(0.08) (0.09) (0.12)


(0.63) (0.68) (1.20)

2. Post-World War I


A. Republican 0.348 -0.612 -1.111

(1.00) (1.13) (1.19)

Democrat -0.273 0.259 0.503

(1.12) (0.54) (0.55)

Congress -0.471 -0.608 -0.715

(0.46) (0.47) (0.53)

Republican*Congres 0.519 1.208 1.319

(1.20) (1.27) (1.38)

B. Republican 0.353 -0.729 -1.557

(1.06) (1.12) (1.37)

Democrat -0.227 0.362 0.716

(1.15) (0.56) (0.60)

Congress -0.469 -0.464 -0.609

(0.52) (0.51) (0.57)

Repuglician*Congress 0.571 1.368 1.854

(1.25) (1.34) (1.53)

Interest Rates -0.001 0.030 0.107

(0.08) (0.09) (0.13)


(0.78) (0.68) (1.29)



A. Republican 0.149 -0.602 -1.201

(0.97) (0.09) (1.16)

Democrat 0.330 0.078

(0.73) (0.74)

Congress -0.770 -0.858 -0.790

(0.60) (0.63) (0.65)

Republican*Congres 1.780 1.313 1.536

(1.29) (1.31) (1.59)

B. Republican 0.116 -0.667 -1.511

(0.99) (1.16) (1.29)

Democrat 0.547 0.290

(0.69) (0.79)

Congress -0.684 -0.652 -0.720

(0.68) (0.65) (0.64)

Repuglician*Congress 1.710 2.016 1.982

(1.29) (1.37) (1.69)


(0.07) (0.08) (0.12)


(1.04) (0.75) (1.47)





ESTIMATES OF HAZARD FUNCTION FOR BULL MARKETS BY PARTY WITH POLITICAL

CONTROL




TABEL 12

1. Full Sample


A. Republican -1.996 ** -1.401 ***

(0.97) (0.53)

Democrat -0.636 -0.596 -0.256

(0.71) (0.40) (0.43)

Congress 0.677 ** 0.383 0.213

(0.35) (0.36) (0.41)

Republican*Congres 2.045 * 1.577 **

(0.36) (0.72)

B. Republican -2.054 ** -1.640 ***

(1.02) (0.64)

Democrat -0.714 -0.593 -0.234

(0.71) (0.42) (0.45)

Congress 0.753 ** 0.431 0.221

(0.37) (0.35) (0.41)

Repuglician*Congress 2.062 * 1.785 **

(1.13) (0.77)

Interest Rates -0.036 0.051 0.086

(0.11) (0.08) (0.07)

Interest Rate Changes 1.285 -0.141 -0.591

(1.63) (1.11) (1.90)

2. Post-World War I


A. Republican -1.806 * 1.276 **

(0.95) (0.55)

Democrat -0.011 -0.356 2.652

(0.65) (0.49) (0.44)

Congress 0.373 0.012 -0.254

(0.43) (0.47) (0.58)

Republican*Congres 2.533 ** 1.594 *

(1.13) (0.98)

B. Republican -1.851 * -1.580 **

(1.00) (0.62)

Democrat -0.007 -0.363 0.346

(0.68) (0.51) (0.49)

Congress 0.433 0.075 -0.287

(0.44) (0.43) (0.60)

Repuglician*Congress 2.581 ** 1.987 *

(1.19) (1.02)


(0.08) (0.07) (0.07)

Interest Rate Changes 0.222 0.089 -0.209

(1.13) (1.13) (1.73)



A. Republican -1.565 -1.493 **

(1.03) (0.67)

Democrat 0.123 0.039 0.571

(0.58) (0.54) (0.49)

Congress 0.746 * 0.277 -0.328

(0.43) (0.49) (0.52)

Republican*Congres 2.530 ** 3.027 ***

(1.05) (0.88)

B. Republican -1.461 -1.657 **

(1.07) (0.69)

Democrat -0.061 0.102 0.664

(0.57) (0.49) (0.65)

Congress 0.821 0.433 -0.408

(0.51) (0.54) (0.79)

Repuglician*Congress 2.169 * 3.370 ***

(1.16) (1.23)

Interest Rates -0.078 -0.067 0.046

(0.12) (0.10) (0.09)

Interest Rate Changes 0.584 -1.329 -0.393

(1.69) (1.32) (2.13)






ESTIMATES OF HAZARD FUNCTION FOR BEAR MARKETS BY PARTY WITH POLITICAL

CONTROL



TABLE 13

DATES OF US STOCK MARKET TURNING POINTS (REAL PRICES)

Trough Peak Bear Bull Bear Bull

7/1872

11/1873 2/1876 16 27 YES NO

6/1877 6/1881 16 48 YES YES

6/1882 7/1883 12 13 NO NO

6/1884 11/1886 11 29 NO YES

3/1888 5/1890 16 26 NO YES

12/1890 5/1892 7 17 NO NO

7/1893 4/1894 14 9 YES NO

4/1895 9/1895 12 5 NO NO

8/1896 9/1897 11 13 NO YES

5/1898 3/1899 8 10 NO NO

9/1900 6/1901 18 9 NO YES

10/1903 9/1906 28 35 NO YES

11/1907 8/1909 14 9 NO YES

7/1910 6/1911 11 11 NO NO

12/1914 12/1915 42 12 YES NO

1/1919 7/1919 37 6 NO NO

12/1920 3/1923 17 27 YES NO

10/1923 9/1929 7 71 NO YES(2 ELECTIONS)

6/1932 7/1933 33 13 NO YES

3/1935 2/1937 20 23 NO YES

4/1938 11/1938 14 7 NO NO

5/1942 4/1946 42 47 YES YES

2/1948 6/1948 22 4 NO NO

6/1949 1/1953 12 43 YES YES

9/1953 4/1956 8 31 NO NO

12/1957 7/1959 20 19 YES NO

10/1960 12/1961 15 14 NO YES

6/1962 1/1966 6 43 NO YES

10/1966 12/1968 9 26 NO YES

7/1970 4/1971 19 9 NO NO

11/1971 1/1973 7 14 NO YES

12/1974 9/1976 23 21 NO NO

3/1978 8/1978 18 5 YES NO

4/1980 11/1980 20 7 NO YES

7/1982 6/1983 20 11 NO NO

7/1984 8/1987 13 37 NO YES

12/1987 8/1989 4 20 NO YES

10/1990 1/1992 14 15 NO NO

10/1992 8/2000 9 94 NO YES(2 ELECTIONS)

2/2003 12/2004 30 22 YES YES

10/2005 10/2007 10 24 YES NO

3/2009 2/2011 17 23 YES NO

9/2011 5/2015 7 44 NO YES

2/2016 9 NO

Notes: Along a row, Bear market refers to period from peak in pervious row to trough in the next row.

Bears market refers to period from trough in that raw to prak in that row.

Date of Duration (in months) Was an Election Held during the

FIGURE 1

Timing of Peaks and Troughs Relative to Election

FIGURE 2


By Political Party

FIGURE 2, continued

FIGURE 3

Timing of Peaks and Troughs Relative to Election (Real Prices)

FIGURE 4


By Political Party (Real Prices)

FIGURE 4, continued

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Elections, Political Control and Duration of Stock Market ...kuwpaper/2018Papers/201810.pdf · presidential elections can affect the timing of turning points of the U.S. stock market