Indexology^® Blog

Every election season brings a familiar ritual: wall-to-wall media coverage, confident predictions and no shortage of opinions about what a given outcome will mean for markets. But does the noise translate into measurably significant market movement? And if it does, does it matter equally everywhere?

To find out, we examined equity index performance around election dates across seven countries, spanning a selection of developed and emerging markets—and what we found challenges some common assumptions. Market reactions to elections are far from uniform, and not always as extreme as pundits predict.

How We Measured Election Effects

We analyzed performance of local benchmarks in the U.S. (S&P 500^®), Mexico, Brazil, Chile, Japan, the U.K. and Germany (single-country indices from the S&P Global BMI) from April 2016 to April 2026. All indices are expressed in their local currencies.

Performance of local indices indicate some seemingly significant fluctuations in performance around election dates, as shown in a sample of our observed countries in Exhibits 1-4, but similar bouts of volatility outside of election cycles suggest other factors may drive market changes even more.

To standardize analyses of short-term election effects, we measured the absolute value of performance over the five-day period following federal election dates for new leaders in each selected country and compared them to a baseline of non-election periods across the same time frame.

The clearest pattern in the data indicated that short-term election effects varied significantly, as shown in Exhibit 5.

Looking beyond the averages and examining periods with the highest absolute index movement, we find that many election periods rank highly, but they are far from the most volatile periods encountered in these markets, as shown through the top 500 ranked five-day periods in the U.S. as shown in Exhibit 6.

Among our seven observed countries, five-day post-election market performance ranked in the top half of observed periods slightly more than half the time, suggesting national elections indeed are associated with above-average short-term volatility. However, there are plenty of volatile periods of more extreme market performance that underscore the impact of unexpected non-election events as well.

The implication is clear; election effects are real, but difficult to predict in direction, magnitude and timing. Investor reactions to expected election outcomes may occur well before or even well after election days, as polling and other news is taken into account. Markets may move for a variety of reasons, including elections, but drivers may be more nuanced. Analyzing which stocks, industries and sectors are most affected by local market events can paint a clearer picture of how investors are responding to all types of news, whether it’s related to the ballot box or not.

What’s driving the continued growth of ETF adoption among institutional investors? Explore the expanded range of ETF applications across portfolio types and objectives. 

S&P Dow Jones Indices is pleased to introduce the new S&P 500^® Dividend Drivers Index, which offers a holistic approach to identifying dividend-paying companies within the S&P 500. Unlike traditional approaches that emphasize a single metric—such as high yield or dividend growth—the index focuses on the key drivers of dividend strength. It combines historical and forward-looking dividend growth, current dividend yield, and profitability to deliver a three-dimensional assessment that encompasses past, present and future potential.

In this first blog post, we’ll explore its methodology and compare its performance, dividend characteristics and profitability profile with those of its underlying universe, the S&P 500.

Methodology

To be eligible, companies must have increased their dividends for at least 10 consecutive years. They must also have an expected dividend increase for the upcoming year, based on S&P Global Market Intelligence’s Dividend Forecasting dataset.

Eligible companies are then selected using a composite score that combines three fundamental measures: five-year dividend growth, 12-month forecasted dividend yield and return on invested capital (ROIC). Final index weights are then determined based on each constituent’s 12-month forecasted dividend yield.

Performance Overview

Based on the back-tested period from April 30, 2010, to July 31, 2026, the S&P 500 Dividend Drivers Index outpaced the S&P 500 by approximately 41 bps on an annualized basis. This result is notable given that dividend-oriented stocks generally lagged during the long bull market over this period, which was largely driven by lower-yielding growth and technology companies. While the S&P 500 Dividend Drivers Index exhibited slightly higher volatility than the S&P 500, its defensive characteristics were reflected in its lower capture ratios, particularly its 88.15 downside capture ratio over the period.

Dividend Characteristics

Across the full back-tested period, the S&P 500 Dividend Drivers Index had an average dividend yield of 3.06%, significantly higher than the S&P 500’s 1.76%. With the S&P 500’s current yield at 1.10% and well below its historical average, the S&P 500 Dividend Drivers Index’s current yield of 2.99% stands out in today’s low-yield equity market environment.

The back-tested results also indicated stronger dividend growth. Over the same period, the S&P 500 Dividend Drivers Index posted an annualized dividend growth rate of 10.7%, outpacing both the S&P 500 (8.5%) and the CPI inflation rate (2.6%). The gap between dividend growth and CPI inflation—about 8 percentage points—corresponded to a 3.2-fold increase in purchasing power since April 2011, after accounting for inflation.

Profitability Comparison

A distinctive feature of the S&P 500 Dividend Drivers Index as a dividend strategy is its emphasis on profitability. Exhibit 5 shows that, as of June 30, 2026, the S&P 500 Dividend Driver Index’s ROIC was broadly in line with that of the S&P 500, while its return on equity (ROE) of 26.0% was significantly higher. High profitability is a defining characteristic of the index, as it has historically been associated with earnings growth, a key factor in supporting long-term dividend growth potential.

Conclusion

The S&P 500 Dividend Drivers Index provides a more comprehensive view of dividend drivers across multiple characteristics and time horizons. The index modestly outperformed the S&P 500 over the back-tested period and exhibited significantly higher dividend yield, dividend growth and profitability. Overall, these results suggest that incorporating multiple drivers in the selection process led to both differentiated performance outcomes and distinct index characteristics relative to the benchmark.

How does an index framework built with diverse constituents from 48 global markets help address concentration concerns in an efficient, simplified way? 

Whether you call it soccer or football, there’s no denying the World Cup was a blast for North Americans and visitors alike. Off the field, one of the most enjoyable spectator sports was watching camaraderie emerge from road trips and cultural mashups. Whether it was the Tartan Army firing up the Miami Marlins, Samurai Blue fans discovering Buc-ee’s brisket, or Lawrence, Kansas embracing all-things Algeria, unexpected combinations often bring the greatest results.

From a U.S. equities perspective, the first seven months of 2026 combined to produce sound results, but with strong headline index performance masking underlying macroeconomic uncertainty and broadening market leadership. A defining indicator of this current regime is the Cboe S&P 500^® Dispersion Index (DSPX). As of July 21, 2026, the DSPX reached 47.5, its highest level since March 2020, as shown in Exhibit 1. Elevated dispersion indicates significant variance in constituent performance, potentially creating a more favorable environment for factor-based strategies.

Among the multiple factors that have benefitted from a high-dispersion environment, the S&P 500 Momentum Index stands out, rising 20.2% YTD (see Exhibit 2).

While the S&P 500 Momentum Index’s outperformance so far in 2026 has owed much to its current selection of semiconductors stocks, further down in Exhibit 2 sits a less discussed factor that has fared relatively well YTD despite completely eschewing the Semiconductor & Semiconductor Equipment industry group—the S&P 500 Low Volatility Index.

As the AI narrative cooled in July and the S&P 500 Momentum Index pulled back, the S&P 500 Low Volatility Index generated outperformance, a short-term result that points to a longer-term pattern of low, and even negative, correlation with the S&P 500 Momentum Index. As of July 2026, the one-year rolling correlation coefficient between the excess performance of the S&P 500 Low Volatility Index and the S&P 500 Momentum Index stood strongly negative, at -0.52 (see Exhibit 3).

In Exhibit 4, we take a closer look at these two factors through the lens of trailing one-year performance, underscoring how the S&P 500 Low Volatility Index and S&P 500 Momentum Index have behaved quite differently depending on the market regime.

We’ve previously discussed the S&P 500 Momentum Index’s historical pattern of outperformance in up-cycles and the S&P 500 Low Volatility Index’s resilience in market downturns. Indeed, both factors have historically reflected slightly more upside than downside, yet remained uncorrelated, suggesting a possibility for performance improvement and diversification through combination.

To investigate this thesis, we created a hypothetical index blend consisting of a 50% weight in the S&P 500 Low Volatility Index and a 50% weight in the S&P 500 Momentum Index, then measured its performance relative to the S&P 500 over a 30-year time horizon as well as the YTD 2026 period.

Exhibit 5 illustrates the 2026 YTD performance of the unrebalanced hypothetical blend, which outperformed the S&P 500 benchmark by 4.5% and outperformed for most of the period.

Perhaps owing to the S&P 500 Low Volatility Index’s track record of asymmetric upside/downside capture (i.e., reflecting less downside than upside) combined with the S&P 500 Momentum Index’s demonstrated tendency to outperform in rising markets, the hypothetical blend exhibited a mix of the two factors’ traits, on average reflecting 87.8% of upside during the 12-month periods in which the S&P 500 rose and 61.0% of downside when the benchmark fell over the 30-year back-tested period. It should be no surprise that compounding this hypothetical differential through the ups and downs generated cumulative performance exceeding that of The 500^® while also producing less volatility, as illustrated in Exhibit 6.

Individually, factor indices each tell interesting stories about behavioral and economic forces driving global markets. Like travelers of the world, they each come with their own unique histories full of ups and downs. They each evolve and reflect underlying trends, and their differences point toward the intriguing possibilities of new and diverse combinations waiting to be explored.

The author thanks Luke Twum-barima for his research contributions to this blog.