Indexology^® Blog

News of impending tariffs and their subsequent pause have sparked jitters throughout the market, with an intraday decline of nearly 2% for the S&P 500^® on Feb. 3, 2025. In an environment of tightening trade conditions, one would expect sectors and industries with predominantly domestic customers to offer greater safety than those highly connected to international markets. But how do we determine how exposed companies are to tariffs? Rather than solely considering country of domicile, an important way to assess the economic exposure of a company is through the geographic breakdown of its revenues.

Looking across the U.S. capitalization spectrum, Exhibit 1 shows that The 500™ makes up more than 80% of the revenues across S&P Composite 1500^® companies. The index is comprised of 500 companies that are all domiciled in the U.S., but only 71% of S&P 500 revenues comes from the U.S. The remainder comes from the rest of the world, including 10% from Europe and more than 10% from Asia. This is not surprising, as many large-cap companies are multinationals with an increasingly global presence.

We can understand how geographic revenue exposure to domestic versus foreign markets has affected market performance through the S&P Global Revenue Exposure Indices, which measure the performance of companies exceeding a targeted revenue exposure to certain regions or countries.

Focusing on the S&P 500, Exhibit 2 illustrates that U.S. companies with greater foreign revenue exposure have outperformed their domestic counterparts since the start of 2017. The S&P 500 Foreign Revenue Exposure and S&P 500 Emerging Markets Revenue Exposure outperformed their U.S. counterparts by 6% and 9%, respectively, over the past five years. This outperformance is notable, considering the strengthening of the U.S. dollar over the same period, which is a typical headwind for companies with high foreign exposure who earn a greater share of revenues in foreign currencies.

Sector tilts may be key to understanding these historical performance differentials. S&P 500 U.S. Revenue Exposure held a significant underweight to Information Technology relative to the benchmark. Meanwhile, S&P 500 Foreign Revenue Exposure and S&P 500 Emerging Markets Revenue Exposure have benefited from big tech dominance, with sizeable overweights to the sector.

Confirming our intuition, Exhibit 4 shows that among large-, mid- and small-cap sectors, Information Technology had the lowest percentage of domestic sales. Utilities consistently had the highest domestic exposure. There were some variations across the cap range; for example, large- and mid-cap Financials had a greater domestic exposure compared to small caps, while mid-cap Energy and Materials had relatively greater domestic exposure.

As markets continue to digest the evolving tariff plans, geographic revenue analysis across sectors may continue to offer insightful perspectives. The S&P 500 U.S. Revenue Exposure, S&P 500 Foreign Revenue Exposure and S&P 500 Emerging Markets Revenue Exposure indices offer a convenient way to observe price impact at a diversified level, while sector (and industry) approaches to risk management may prove more powerful than usual in balancing the desired exposures to sources of revenue globally.

What’s the potential impact of tariffs on U.S. equities across sectors and industries? S&P DJI’s Benedek Vörös takes a quick look at the S&P Revenue Exposure Indices and the importance of granular, industry level analysis in this installment of The Market Measure.

Following the close of 2024, the S&P GSCI continued its strong performance into the new year, ending January 2025 up 3.3%. As we move deeper into Q1, we dig into the reasons behind the S&P GSCI’s leaders and laggards in 2024 and the seasonality inherent to commodity futures performance.

In 2024, the top three performers were cocoa, coffee and gold, up 341%, 87% and 27%, respectively. Cocoa futures’ outstanding performance, driven by a perfect storm of poor weather and black pod disease, exceeded even bitcoin, up 122%, and the S&P 500^®, up 25% for 2024. Despite this, the world’s top cocoa-growing countries are scaling back cocoa production due to farmers’ inability to fully reap the benefits of global price increases. Further depressed supply, as farmers shift their focus to more profitable crops, could lead to a continued cocoa rally well into 2025 and beyond. Coffee faces a similar future, with persistent drought conditions in Brazil.

Meanwhile, gold, up 27% in 2024, has proven to be the best-performing asset in the 21^st century, with an annualized return of 8.5%, compared to the S&P 500 annualized return of 7.7%. Gold continued to reign as a favorite for investors seeking safety during economic and political uncertainty.

After Trump was elected in November, concern over wide-reaching tariffs has pushed gold traders to fly gold from London to New York. Fearing potential gold liquidity shortages in London, the primary spot market for gold, traders are driving gold futures prices to a premium. The friction inherent in the market for physical gold, including the difference in gold bar size for settlement in New York and London, indicate the premium in the futures market is not likely to be eliminated through arbitrage. The S&P GSCI Gold reflects this premium. Alternatively, the S&P GSCI Gold Covered Call offers a view into a strategy that could allow for income to be generated from an otherwise “unproductive” asset.

Looking ahead to Q1 2025, seasonal impacts and demand imbalances on certain commodities, such as heating fuels and agricultural goods, continue to draw attention. According to the U.S. Census, about 47% of U.S. households heat their homes with gas.¹ Given the polar vortex sweeping through the U.S., heating oil futures prices are being bid up. In January 2025, the S&P GSCI Heating Oil TR was up 4.9%.

Strong winds and an increasing number of storms mean severe temperatures may hit areas in the U.S. South that are ill-equipped to handle extreme weather. Local supply shortages from supply chain disruptions, aging infrastructure or lack of sufficient inventory can all increase spot prices and spur commodity traders to hedge against them.

Livestock, particularly live cattle, also typically perform well during the winter months, as heartier meals and traditional holiday fare become popular. The S&P GSCI Live Cattle TR was up 5.2% in January 2025. Freezing temperatures in the Midwest and Central Plains have kept cows lean; meanwhile, the USDA has unexpectedly continued its suspension of live cattle imports from Mexico due to parasites. Despite this strain on supply, consumers have responded to increased prices with only modest levels of substitution. Per capita beef consumption in Q1 2025 is expected to maintain its level at 14.9 pounds per year, according to the USDA.²

While the S&P GSCI measures the performance of the world’s largest commodities, roll yield dynamics can have a significant impact on returns. This is particularly important for commodities that exhibit seasonal performance trends. The S&P GSCI holds the front month contract and rolls into the next month’s contract upon expiry. When the next month’s contract price exceeds that of the front month contract—a situation known as contango—this results in negative roll yield (buying high and selling low). The S&P GSCI Dynamic Roll takes a different approach, rolling into contracts along the futures curve based on implied roll yield. Variants of the S&P GSCI Dynamic Roll include the S&P GSCI Dynamic Roll Equal Weight Select, which equally weights the most liquid 14 commodities of the S&P GSCI, and the S&P GSCI Dynamic Roll Risk Weight Index, which applies a risk parity concept to each commodity sector. Exhibit 4 shows how these indices compared over the past 20 years, including some periods of back-tested performance.

¹ United States Census Bureau. “Why We Ask Questions About Home Heating Fuel.” Accessed January 2025.

² Knight, Russell, Hannah Taylor, William Hahn, Adriana Valcu-Lisman, Angel Terán, Mildred Haley, Grace Grossen and Brian Bourquard. “Livestock, Dairy, and Poultry Outlook: January 2025.” USDA. Jan. 16, 2025.

Climate resilience refers to the ability of a system to anticipate, prepare for and respond to the impacts of climate change.¹ As the world grapples with the adverse effects of a changing climate, climate resilience stands front and center in collective efforts from governments, corporations and the investment community² alike. This blog is the first of a two-part series exploring a forward-looking framework to assess companies’ climate action across different dimensions. Our next blog will examine how this framework can be used to create index strategies in a rules-based, transparent way.

Measuring Companies’ Readiness for the Transition to a Low Carbon Economy

The S&P Global Sustainable1 Climate Action Framework is an innovative dataset that assesses companies’ ability to manage the risks of transitioning to a low-carbon economy through the lens of three key dimensions:

• Climate Governance and Strategy;
• Physical Risk Adaptation Strategy; and
• Climate Risk Mitigation and Alignment.

The assessment leverages raw data collected from S&P Global’s Corporate Sustainability Assessment (CSA), which underpins the S&P Global ESG Scores. Additionally, it integrates established metrics such as implied temperature rise, revenue exposure from business activities and various environmental indicators to provide a comprehensive evaluation of a company’s risk management capabilities, adaptability to physical risks and strategies for mitigating future climate challenges.

The framework categorizes companies’ performance across each of the three key pillars, as well as on an aggregate-level assessment. Companies can be classified as having “Advanced,” “Basic” or “Poor” performance across the pillars. Combined, these classifications result in a five-tier aggregate assessment (see Exhibit 2) ranging from “Transition Limited,” where companies lack basic governance structures, climate risk management processes and target-setting, to “Transition Strategic,” in which companies demonstrate robust climate strategies, comprehensive risk management plans and a long-term commitment to achieve net zero emissions.

We examined the sectoral breakdown of each of the pillars and the final Climate Action Framework assessment within the S&P World Index (see Exhibit 3). Across sectors, we see a wide distribution of outcomes for each of the categories.

In general, we observe a considerable portion of companies across sectors that were assessed as Poor and Advanced for the Climate Governance and Strategy and Climate Risk Mitigation Pillars. However, most companies have a Basic physical risk adaptation strategy, and very few can be considered Advanced, suggesting that generally, companies lack context-specific adaptation plans. Aggregating the pillars, we see most companies classified at the bottom two tiers as either Transition Limited or Transition Initiating, reflecting the increasing climate action ambition required by the top tiers.

Taking the Energy sector as an example, we see that:

• Roughly 50% of companies lack adequate climate governance practices, classifying them as Poor within Pillar 1;
• The vast majority have sufficient overall physical risk adaptation plans and conducted scenario analysis, classifying them as Basic within Pillar 2; and
• Approximately 80% of companies are classified as Poor within Pillar 3, most likely due to their higher implied temperature alignment and the lack of net zero targets covering Scope 3 emissions.

On an aggregate level, we observe that 97% of energy companies are ranked as Transition Limited, suggesting that there is still much room for improvement on the climate front for most companies in the sector.

From a regional perspective, we observe a similar pattern in which there is a varied distribution of categories across regions (see Exhibit 4). Exploring the U.S., which comprises around 70% of the S&P World Index by market capitalization, we see most companies classified as either Transition Limited or Transition Initiating (i.e., the bottom two categories), and only 2% achieved the highest rank of Transition Strategic.

Analyzing the interplay between the Climate Action Framework assessment and other climate data points reveals interesting insights (see Exhibit 5).

• There was a positive pattern between carbon efficiency and climate action, in which companies with enhanced climate governance and risk management structures also tend to be relatively more carbon efficient.
• There was a relationship between forward-looking temperature rise and climate action practices—we see that Transition Strategic companies were under their 1.5°C carbon budget, indicating forward-looking alignment with the Paris Agreement goals.
• There was not a strong pattern regarding physical risk, suggesting that physical risk may need to be addressed separately in an index that incorporates climate action assessments, to mitigate tail risk.
• It is worth noting that Transition Strategic companies displayed the highest revenue alignment with climate impact solutions, such as renewable energy, sustainable transportation and battery technology.

In the second part of this blog series, we will explore the recently launched S&P World Climate Resilience Tilted Index, which incorporates elements of the S&P Climate Action Framework and additional climate datapoints to tilt toward companies that are relatively more climate resilient and carbon efficient, and that have higher exposure to climate impact solutions.

¹ Intergovernmental Panel on Climate Change. “Climate Change 2022: Impacts, Adaptation and Vulnerability.” 2022.

² Vijayakumar, C. “Collective action is the key to drive urgency in building climate resilience.” World Economic Forum. Jan. 19, 2025.

Active managers sometimes tout their ability to select stocks in markets that are considered less informationally efficient and those that offer larger rewards to successful stock pickers. Smaller companies and those in emerging markets are typically presented as examples. What are the grounds for debate, and what do over 20 years of SPIVA^® Scorecards tell us about the historical record?

First, consider the efficiency argument. It is true that research coverage is broader and deeper in some markets than others, and it is intuitive to suppose that the likelihood of misvaluations is higher among more obscure companies. However, there is no reason to assume that the likelihood of undervaluation is higher than the likelihood of overvaluation; determining which is which may be no easier in well-researched markets than in less-researched ones.

Second, some markets do indeed offer larger rewards for successful active choices than other markets. One way to understand the magnitude of the opportunity set in a given market is through dispersion, which measures the degree of variation in the returns of an index’s components over a specific period of time and at a specific level of granularity. When stock returns are more similar, dispersion is lower and the value of stock selection skill is accordingly lower. Conversely, when dispersion is high, opportunities may be greater.

In Exhibit 1, we plot monthly dispersion for the S&P SmallCap 600^®, the S&P Emerging BMI and the S&P 500^®. Over the past 23 years, dispersion was consistently higher in the first two indices compared to the third.

Drilling down, Exhibit 2 groups U.S.-based small-cap and emerging market active funds by the average dispersion registered in the category benchmark. We defined “low dispersion” as values falling below the 25th percentile, “high dispersion” as those above the 75th percentile and a third grouping encompassing all dispersion environments. In low dispersion environments, performance proved to be more challenging for large-cap and small-cap managers, with 67% and 73% of funds underperforming on average, respectively. However, even in high dispersion regimes, more than half of funds still underperformed in all three categories.

Exhibit 3 shows that only two years—2012 and 2019—saw the majority of managers in the Emerging Markets Equity category outperform, both of which coincided with relatively low dispersion environments. In contrast, there were only three years of majority outperformance for large-cap managers and six years for small-cap managers.¹

All told, the rare success of active funds confirms that while there may be greater potential for outperformance in some markets, greater opportunity for outperformance is no guarantee of actual outperformance.

Over the long term, the statistics become even clearer. As summarized in Exhibit 4, regardless of the level of dispersion and whether managers are seeking alpha in widely researched markets like large-cap equities or more specialized areas, outperforming the benchmark over longer horizons remained particularly challenging.

S&P DJI recently launched a new family of indices known as the S&P Quality FCF Aristocrats which includes the S&P 500^® Quality FCF Aristocrats^® Index and the S&P Developed Quality FCF Aristocrats Index. A more comprehensive introduction to this family of indices can be found in this blog post.

Gaining insights into the historical performance of factor strategies across various macroeconomic environments is essential for risk mitigation and informed investment decisions.  In this blog, we will begin by analyzing the performance of these two newly launched indices across different economic regimes. Following that, we will compare the performance of the S&P 500 Quality FCF Aristocrats Index with that of another Aristocrats-branded index, the S&P High Yield Dividend Aristocrats, across the same four economic scenarios.

Macroeconomic Framework¹

To assess performance across different economic environments, we use a framework that defines four distinct regimes based on whether growth² and inflation³ are rising or falling. These regimes are organizing into four quadrants which are illustrated in Exhibit 1.

Considering the longer back-tested history available for the U.S. market compared to other developed markets, we present two distinct time horizons in our analysis (see Exhibit 2). The first time horizon spans 282 calendar months from May 31, 2001, to Oct. 31, 2024 for U.S. markets, while the second covers 222 calendar months from May 31, 2006, to Oct. 31, 2024, for developed markets. Exhibit 2 displays the number of months and relative frequency across each regime.

Performance Across Growth and Inflation Regimes

The historical risk/return characteristics of the S&P Quality FCF Aristocrats Indices and their respective benchmarks across the four economic regimes are illustrated in Exhibit 3. Historically, all the indices presented demonstrated highest absolute returns and risk-adjusted returns in the Rising Growth and Falling Inflation regime, followed by the Rising Growth and Rising Inflation regime. Conversely, these indices experienced much lower returns in the Falling Growth and Falling Inflation regime, with the worst returns—often negative—occurring in the Falling Growth and Rising Inflation regime.

Excess Returns⁴ in Four Economic Regimes

In this section, we analyze the macroeconomic performance of the S&P Quality FCF Aristocrats Indices in terms of their excess returns (ER) relative to their benchmarks (see Exhibit 4).

The S&P 500 Quality FCF Aristocrats Index consistently outperformed the S&P 500 in a Falling Growth environment, regardless of inflation trends. In the Rising Growth and Falling Inflation regime, its performance was comparable to that of the S&P 500. However, in the Rising Growth and Rising Inflation regime, it underperformed. This behavior indicates that the S&P 500 Quality FCF Aristocrats Index exhibits strong defensive characteristics whilst still meaningfully participating in market upside.

The S&P Developed Quality FCF Aristocrats Index consistently outperformed the S&P Developed LargeMidCap index by a wide margin in a Falling Growth environment, regardless of inflation trends. In the Rising Growth regime, its performance was slightly better than its benchmark. The results indicate that the S&P Developed Quality FCF Aristocrats index outperformed S&P Developed LargeMidCap in all economic regimes, meaning it was defensive in down markets while keeping pace strongly in up markets.

Comparison with the S&P High Yield Dividend Aristocrats

In a previous blog, we compared the S&P 500 Quality FCF Aristocrats Index with the S&P High Yield Dividend Aristocrats, demonstrating that these two indices provide differentiated exposure and track companies with distinct profiles. Now, let’s examine how they perform across the defined macroeconomic regimes.

Overall, the indices have differentiated exposure across these regimes. The S&P High Yield Dividend Aristocrats achieved its highest excess returns during the Falling Growth and Rising Inflation environment. In contrast, the S&P 500 Quality FCF Aristocrats led the way during both Falling Growth regimes, regardless of the inflation regime. However, both indices underperformed relative to the broad market during the Rising Growth and Rising Inflation regime.

In conclusion, the S&P Quality FCF Aristocrats Indices have historically outperformed during periods of falling economic growth, regardless of the inflation regime. In times of rising growth, both indices performed in line with the benchmark during falling inflation; however, the S&P 500 Quality FCF Aristocrats lagged when inflation was rising. Furthermore, our analysis shows that the S&P 500 Quality FCF Aristocrats offer differentiated exposure compared to the S&P High Yield Dividend Aristocrats, highlighting their potential as complementary tools.

¹ Hao, Wenli Bill and Rupert Watts, “A Historical Perspective on Factor Index Performance across Macroeconomic Cycles,” S&P Dow Jones Indices LLC, Nov. 14, 2024.

² Rising growth is defined as a positive monthly change in the U.S. Composite Leading Indicator (CLI) compared to the previous month, while falling growth is defined as a negative monthly change.

³ Rising inflation occurs when the three-month average of U.S. Consumer Price Index (CPI) exceeds that of three-year moving average, while falling inflation occurs when falling below.

⁴ Excess return measures how much the average monthly total return of each index exceeds that of its corresponding benchmark in each regime.