Figure 1 – E-mini S&P 500 volatility term structure

Figure 1 – E-mini S&P 500 volatility term structure
Source: QuikStrike
The at-the-money (50 delta) futures implied volatility as of 9/25.

The market’s current pricing of the uncertainty surrounding the U.S. presidential is presented above in Figure 1, as of September 25 . A spike in the implied volatility is clearly visible between the E1AX4 contract expiring on November 4 and the E1DX4 contract expiring on November 7 from 11.92% to 14.32%. With the Presidential election on November 5, the market is pricing many unknowns.


For historical implied volatility, the data presented is the at-the-money daily average implied volatility for December expiry E-mini S&P 500 options. December expiry options with post-election expiry provide insight on election-oriented risk management.  The many option expiries allow investors to place such trades throughout the year, or even in years prior when accounting for December quarterly options (Figure 2). Isolating December option contracts allows for a deep analysis to gauge a potential future evolution of election-adjacent implied volatility dynamics.

Figure 2 –E-mini S&P 500 option listing periods

Figure 2 –E-mini S&P 500 option listing periods
Source: CME Group
December 2024 quarterly options are listed for over three years, having allowed traders to trade around the 2024 presidential election on a wide time horizon.

Looking at the historical implied volatility time series for December expiry options, a useful focus for analysis is the decomposition of the series into its components. One factor of interest is seasonality, which uncovers repeating patterns during the calendar year. Consequently, the time series is segmented into trend, seasonal and random components according to the formula:

Yt = Tt + St + et

Variables: 

  • Yt – Time Series (observed)
  • Tt – Trend
  • St – Seasonal Component
  • et – Random Noise

Figure 3 – Additive time series decomposition

Figure 3 – Additive time series decomposition
The top section is the original time series, while the other three sections represent the three components that this time series was decomposed into.

The seasonal component of the time series (refer to panel 3 of Figure 3 for a visual) demonstrates both high amplitude and recurrence. The peaks of the seasonal component are 3.42 percentage points of implied volatility, are consistently found in the second week of November, starting in late September and subside by the end of the year.

A concern with this analysis is that a massive outlier year, such as 2008, may cause a perceived seasonal pattern, which would skew the distribution unfairly. Such an outlier is 2008, which had high volatility, exacerbated by the onset of the Great Recession. A t-test that shows that the 3-month average IV, averaged for all years 2008-2024, series that  which includes 2008, can be confidently identified as having a higher mean than that of the 3-month IV average from 2009 to 2024, excluding 2008, with the p-value ≈2-56 confirming this.

Excluding 2008 as an outlier, data still shows that the seasonality of our series peaks around early November, at 3.62 percentage points of IV, demonstrating that the observed November-oriented seasonal trend isn't caused by such an outlier but is rather muffled by the interference of the unique environment of 2008.

Creating a continuous time series of the average implied volatility including only election years changes the shape of the seasonal component significantly. Near-election peaks are higher, with the absolute maximums reaching 6.65 percentage points of implied volatility. The underlying seasonal pattern of elevated implied volatility during election season is clearly visible. Implied volatility around November is pushed higher above the trend during election years than it is for non-election years, with the seasonal peak being lower at 3.42 percentage points as stated earlier, meaning investors are using these contracts with the event risk of the election in mind. 

Figure 4 – Election years: Seasonal component of the average IV times series for December expiry E-mini S&P 500

Figure 4 – Election years: Seasonal component of the average IV times series for December expiry E-mini S&P 500

Risk management with options

With implied volatility tending to rise above trend for December contracts around the elections, can we expect a further increase in the implied volatility as the election nears and what tools can investors use for risk management?

E-mini Equity Index options are at investors’ disposal to help mitigate the increased risk of the electoral season. A wide range of temporal depth, with weekly options expiring Monday, Tuesday, Wednesday, Thursday, and Friday; monthly options expiring end-of-month;quarterly options expiring March, June, September and December synergize with the ability to use the request-for-quote (RFQ) process to synthesize bespoke user-defined spreads (UDS). UDS option strategies are staged without disclosing size or direction or a commitment to trade. This functionality is available for electronic execution through the Globex trading platform. Figure 5 shows how one can quickly see a straddle run on CME Direct to easily see the ATM volatility market in real-time.

Figure 5 – Straddle on CME Direct showing ATM volatility market

Figure 5 – Straddle on CME Direct showing ATM volatility market

Overall, investors are currently pricing higher risk around the presidential election into Equity Index-derived contracts. Seasonally and around elections, implied volatility has tended to rise above trend. Consequently, investors can use broad and deep options on Equity Index futures to manage this volatility regime.


Eric Leininger
Eric Leininger

is Executive Director of Research and New Product Development for Interest Rates and Equities. The Research and Product Development team develops new risk management products as well as ensuring the continued relevance of our current suite of key benchmarks. The team also produces original research into derivatives and their underlying markets across asset classes and around the world.

Dmitriy Stepanyan
Dmitriy Stepanyan

is the Financial Research and Product Development intern, currently a final-term MSc Financial Engineering student at Stevens Institute of Technology.

All examples in this report are hypothetical interpretations of situations and are used for explanation purposes only. The views in this report reflect solely those of the author and not necessarily those of CME Group or its affiliated institutions. This report and the information herein should not be considered investment advice or the results of actual market experience.

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