The U.S. congressional midterm elections roll around every four years, inviting plenty of speculation about how the outcome will affect markets — possibly delighting or spooking investors.

Rather than play along with pundits’ political guts, we prefer to take a look at historical data and see what, if anything, we can glean from them. One should do so with a larger than usual grain of salt, considering the midterm elections happen only every four years, the data set is small in general and also relatively small compared to the non-midterm election years.

The annual comparison

Using data from Ibbotson Associates, we can examine total returns for the S&P 500 going back to 1926. That’s 92 years of data — but only 23 years when a midterm election happened.

Average annual total returns for calendar years: For midterm election years, it’s 9.17% (23 observations) versus 13.02% for non-midterm years (69 observations).

Volatility*: It is higher for midterm years: 20.95% standard deviation versus 19.46% for non-midterm years.

Takeaway: Midterm election years provide less return and higher risk — posing more trick than treat so far.

The forward-looking comparison

What do we see when we examine the 12 months immediately after midterm elections (November to November)? The story flips.

Average November to November total return (post November midterm elections): 17.05% return in the 12 months following midterm elections versus 10.25% for non-midterm years.

Volatility*: This time it is lower for midterm years: 17.61% versus 19.87% for non-midterm years.

Takeaway: More return and less risk — a treat, indeed.

OK, so what is it? Trick or treat?

Yes, we have a mixed bag here. Perhaps it is the power of reversion to the mean — after a lackluster performance during midterm election years, the market sees above-average performance afterwards. The table below shows how the overall average return and standard deviation for the market for every calendar year since 1926 sits right between the midterm election years and non-midterm election years. Is this proof of reversion to the mean? Perhaps, or perhaps it is just a coincidence in a non-linear data set.

The real lesson? Of the 92 calendar years observed, the stock market finished up for the year 74% of time (68 years up versus 24 years down). This is the type of powerful, long-term perspective successful investors maintain.

However, as investors, we also experience the market in real-time and can lose sight of the long-term view. Looking at the monthly returns of the same 92 years of data, stocks finish up on a monthly basis only 62% of the time versus 74% on an annual basis. So, if you’re looking at your performance daily, keep in mind those returns are essentially a coin-flip for finishing up or down.**

Elections come and go, and investors can be distracted by all the noise. Maintaining a perspective that is longer than election cycles may prove to be a better way to make your investment votes count.


*Definition of Volatility / Standard Deviation: Measures the historical dispersion of a security, fund or index around an average. Investors use standard deviation to measure expected risk or volatility, and a higher standard deviation means the security has tended to show higher volatility or price swings in the past.

**Daily returns analysis used S&P 500 Price Index daily returns going back to 1950.


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