Market-cap-weighted indices like the S&P 500^® that offer a broad measure of the market have long served as the foundation of passive investing. With valuations at elevated levels and sector concentration—particularly in technology—near historic highs, we examine alternative weighting methods that may provide broader and complementary views.

Revenue weighting offers a complementary approach: by weighting companies proportionally to their top-line sales, the S&P 500 Revenue-Weighted Index, S&P MidCap 400^® Revenue-Weighted Index and S&P SmallCap 600^® Revenue-Weighted Index¹ anchor weights to economic activity rather than market value. These indices may exhibit broader sector diversification and lower valuation multiples, while maintaining the characteristics of passive investing.

In this blog, we review the historical performance, risk-adjusted returns, valuation characteristics and diversification effects of revenue-weighted index construction.

Long-Term Outperformance versus Benchmarks

The S&P 500 Revenue-Weighted Index has outperformed the S&P 500 as well as the S&P 500 Equal Weight Index across both short- and long-term periods. This trend extends to mid- and small-cap equities; the S&P MidCap 400 Revenue-Weighted Index and S&P SmallCap 600 Revenue-Weighted Index have also outperformed their respective equal- and market-cap-weighted benchmarks (see Exhibit 1).

Enhanced Historical Risk-Adjusted Performance

As illustrated in Exhibit 2, the revenue-weighted indices also showed superior risk-adjusted performance compared to their equal- and market-cap-weighted counterparts, across both short- and long-term horizons.

Lower Valuations Relative to Benchmark Universes

Exhibit 3 illustrates that, as of June 30, 2026, the S&P 500 Revenue-Weighted Index was trading at lower valuation ratios compared to both the S&P 500 and the S&P 500 Equal Weight Index. This trend has also been observed historically over the long term, as shown in Exhibit 4. Additionally, the mid-cap and small-cap revenue-weighted versions consistently demonstrated lower price multiples relative to their respective benchmarks.

Sector Diversification

As illustrated in Exhibit 5, the Information Technology sector comprised 38.03% of the S&P 500 as of May 31, 2026—representing an all-time high. In comparison, the S&P 500 Revenue-Weighted Index demonstrated greater sector diversification, with less dispersion across sector and individual stock weights, and a higher effective number of sectors and stocks. While sector weights tend to be more balanced in mid- and small-cap indices, revenue weighting still provides a differentiated view relative to traditional benchmarks.

Conclusion

Revenue-weighted indices can be complementary to traditional market-cap-weighted indices. By anchoring company weights to revenue, these indices have historically preserved a broad equity view while reducing concentration and valuation risk. Over the back-tested history, the S&P 500 Revenue-Weighted Index, S&P MidCap 400 Revenue-Weighted Index and S&P SmallCap 600 Revenue-Weighted Index have exhibited strong total returns and risk-adjusted outperformance, along with a more pronounced value tilt and higher diversification.

¹ Please refer to the S&P Revenue-Weighted Index Series Methodology for more details.

² Effective number of sectors is the inverse of the Herfindahl-Hirschman Index (HHI), which is the sum of squared sector weights for each index.

³ Effective number of stocks is the inverse of the Herfindahl-Hirschman Index (HHI), which is the sum of squared stock weights for each index.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

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The S&P 500^® gained 15% in Q2 2026, posting its best quarter since Q2 2020. The steady drumbeat of AI-related enthusiasm propelled the market upward despite numerous obstacles, including the war with Iran, rising inflation and fears of Fed rate hikes. However, the start of Q3 has been rocky, with a sharp sell-off in chipmakers, followed by a bounce back today, as investors struggle to assess the sustainability of the AI trade. Are these market oscillations ephemeral in nature or a sign of a regime shift?

Reflecting on the past year, the recipients of the rewards of investment in AI infrastructure have no longer been confined to the mega-cap adopters, but they are also moving toward rapidly growing memory chip suppliers housed in the semiconductors industry.¹ These leaders include Sandisk Corporation, Micron Technology and stalwart Intel, which were the three top-performing stocks in The 500^® YTD through June 30.

Naturally, the performance of mega caps versus chipmakers has diverged over the past year, with the S&P Semiconductors Select Industry Index's gain of 144% trouncing the 20% gain for the S&P 500 Top 10 Index.² Exhibit 1 shows that three-month performance correlations between the two indices fell steadily over the one-year period.

In a reversal from recent years characterized by large-cap strength, one of the consequences of the shifting performance among participants across the AI value chain has been the broadening of the rally toward smaller caps, with the S&P MidCap 400^® and S&P SmallCap 600^® up 14% and 20%, respectively, in Q2.

The rally expanded within large caps alone, with the S&P 500 Ex-S&P 100 Index, which not coincidentally includes Sandisk and other leading semiconductor companies like Western Digital, outperforming the S&P 100 by 2% YTD. But the path to outperformance was not linear, as illustrated in Exhibit 2, with the bottom 400 outperforming in Q1, followed by sharp underperformance as mega caps returned to favor and resuming outperformance in June as investors sought refuge among smaller, domestically oriented and defensive stocks.

Despite these fluctuations, Exhibit 3 shows that index volatility has remained moderate, with a realized volatility of 17% for both the S&P 500 and S&P 600^® for June 2026.³ Meanwhile, cross-sectional volatility—or dispersion, which measures how differently stocks are performing relative to each other—has risen to extreme levels. S&P 600 21-day dispersion reached a peak of 60% in April 2026, outpacing the prior high from November 2025 and the 55% level observed for the S&P 500.

Offering a more granular view is Exhibit 4, which shows that the Technology Select Sector index's calendar-month stock-level dispersion rose to 80% in April 2026. This level doubled to 161% for the S&P Semiconductors Select Industry Index. The lackluster reaction to Broadcom's earnings beat and guidance, enthusiastic response to Micron's blockbuster results, and most recently, the plunge in Samsung's stock in spite of its earnings beat are prime examples of the increased scrutiny faced by these firms. The value of stock-selection skill rises when dispersion is high, which can mean fruitful conditions for skillful stock pickers to outperform.

The impact of the AI boom has reverberated globally, most notably in emerging markets. We observe in Exhibit 5 that the S&P Emerging Plus AllCap Information Technology outperformed the S&P Emerging Plus AllCap Index⁴ by 116% since June 2025.

But the rewards have not been distributed equally across regions. Dispersion, which can also be measured at the country level, widened for the S&P Emerging Plus Index to a high of 58% in early June 2026. Countries with greater sensitivity to semiconductors like South Korea and Taiwan outperformed, although not without their share of jitters, just as we have witnessed in the U.S.

No one knows if the performance gyrations in semiconductors are a temporary blip or the sign of a new regime, but understanding the drivers of these reversals in performance and risk from a size, sector, industry and global lens may provide a nuanced perspective for market participants as they navigate H2.

 

¹ See Ganti, Anu, "Cashing in the Chips?, S&P Dow Jones Indices LLC, June 2, 2026.

² Performance from June 30, 2025, to June 30, 2026.

³ See Dispersion, Volatility & Correlation Dashboard, S&P Dow Jones Indices LLC, June 30, 2026.

⁴ Includes securities in emerging markets, plus South Korea.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

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In this blog, we introduce the Dow Jones Commodity Index 3 Month Forward - Quarterly Reweight (DJCI 3MQT). Launched in August 2025, the DJCI 3MQT is a variant of the Dow Jones Commodity Index (DJCI). The DJCI 3MQT has historically outperformed the S&P GSCI and the Bloomberg Commodity Index (BCOM): over the 10-year period ending June 30, 2026, the DJCI 3MQT outperformed the S&P GSCI by 175 bps and the BCOM by 330 bps.

As of its January 2026 reconstitution, the DJCI 3MQT includes 29 commodity futures contracts, representing global commodities across three sectors: agriculture and livestock; energy; and metals. Like the S&P GSCI and BCOM, the DJCI 3MQT holds the front-month futures contract, rolls monthly and rebalances annually in January.

Unlike the S&P GSCI and BCOM, the DJCI 3MQT is liquidity weighted and reweights quarterly. Additionally, the DJCI 3MQT caps the maximum weight of any commodity component at 32%, with any remaining commodity components capped at 17%, and equally weights between commodity sectors. These weighting constraints are applied iteratively until all requirements are met.

Exhibit 1 shows a methodology comparison between the DJCI 3MQT, S&P GSCI and BCOM.¹

Let's explore how the DJCI 3MQT's three unique methodology components—emphasis on liquidity, equal weighting between sectors and quarterly rebalancing—have historically enhanced performance and reduced volatility.

Emphasis on Liquidity

By emphasizing liquidity, the DJCI 3MQT offers a unique measurement of the commodities market. Liquidity, which is proxied by the total dollar value traded for constituent commodities, determines the weight and, therefore, the importance of the constituents within the index.

As commodities are real assets, it's difficult for commodity producers to quickly change production or storage capacity to meet changes in demand. In contrast, financial market participants, such as hedgers and speculators, can quickly change their trading behavior to meet changes in demand. As such, the liquidity of commodities contracts, rather than their production data, more accurately mirrors the real-time importance of individual commodities.

The historical effect of liquidity on index performance is clear. In Exhibit 2, we compare the Dow Jones Commodity Index 3 Month Forward (DJCI 3M) against the S&P GSCI 3 Month Forward Capped Sector Equal Weight Composite.² These two indices are methodologically the same, other than the choice between liquidity or production. As of June 2026, the DJCI 3M had outperformed the S&P GSCI 3 Month Capped Sector Equal Weight Composite by 69 bps on a 10-year basis.

Equal Weighting between Sectors

Next, we turn to the second characteristic of the DJCI 3MQT—enhanced diversification. Compared to the S&P GSCI and BCOM, the DJCI 3MQT has historically had higher diversification through its overall constituent count (29 versus 24 and 25, respectively),³ as well as through its unique equal-weighted approach to commodity sectors and concentration limits on individual commodities.

The effect of being highly diversified is demonstrated in Exhibit 3, which graphs the annualized performance against the annualized volatility of the DJCI 3M and its constituent commodities over the past 10 years.⁴ The DJCI 3M achieved higher annualized performance while exhibiting lower annualized volatility compared to its constituent commodities.

As of June 2026, the 10-year weighted average annualized performance of the DJCI 3M constituent commodities was 7.1%, and the 10-year annualized performance of the DJCI 3M was 9.0%. The 10-year weighted average annualized volatility of DJCI 3M constituent commodities was 23.9%, and the 10-year annualized volatility of the DJCI 3M was 12.9%. This demonstrates the essence of modern portfolio theory—that diversification may be the only "free lunch" in investing—as the DJCI 3M has both increased annualized performance and decreased annualized volatility compared to its individual constituents.

More Frequent Reweighting

Finally, we turn to the third characteristic of the DJCI 3MQT's methodology: more frequent reweighting. The DJCI 3MQT reweights quarterly to its annual January rebalance weights. This reweighting enables the index to adhere to its intended, liquidity-based weights.

Without the quarterly reweight, the effective U.S. dollar weights of the constituent commodities float based on price changes; this unintentionally adds a momentum component to the index. However, commodities are often mean reverting, such that a momentum strategy can underperform.

A potential positive effect of a more-frequent reweighting strategy is shown as a comparison in Exhibit 4, which outlines the performance of hypothetical compositions of the DJCI 3M with different reweighting schedules: monthly, quarterly, semiannually and annually. As of June 2026, the quarterly reweight version of the DJCI 3M outperformed the annual reweight (i.e., no reweight) version by 55 bps over the 10-year period.

For further reading, please see Why DJCI? and Dow Jones Commodity Index 3 Month Forward: A Simple Strategy to Measure Enhanced Roll Yield.

 

¹ For more information, please see the Dow Jones Commodity Index Methodology.

² There is no exact S&P GSCI corollary for the DJCI 3MQT, therefore the DJCI 3M is used as a proxy to isolate the impacts of liquidity weighting.

³ As of the indices' respective January 2026 reconstitution

⁴ DJCI 3MQT single constituent commodities are not readily available. Therefore, the analysis in this exhibit is proxied with the DJCI 3M.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

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From Efficiency to Security

Over the past few months, two themes have dominated market attention, artificial intelligence (AI) and energy supply. Each is driven by different forces, yet both are increasingly pushing governments in a similar direction—toward supply security and reduced external dependence.

Recent developments help illustrate this shift. Reports of Anthropic restricting access to its latest AI models have raised concerns in Europe about reliance on external providers for critical AI technologies.¹ At the same time, ongoing tensions around the Strait of Hormuz have highlighted the fragility of global oil and commodity supply routes.² Earlier disruptions, particularly the world's heavy dependence on China for rare earth elements (REEs), had already exposed similar vulnerabilities³ and prompted policy responses such as the EU Critical Raw Materials Act.⁴

These developments point to a meaningful shift. Access to key inputs is no longer guaranteed, and policy is moving from just-in-time efficiency toward just-in-case resilience.

Infrastructure Driving Critical Minerals Demand

One area where this shift is becoming visible is in demand for critical minerals.⁵ The buildout of digital infrastructure is driving demand, while concerns around supply concentration and security are bringing the supply side into sharper focus.

The S&P Global Essential Metals Producers Index, launched in August 2023, tracks companies involved in the extraction or ownership of reserves of essential metals, a subset of the broader critical minerals universe. These metals are central to two major transformations over the next decade: the expansion of AI and digital infrastructure, and the acceleration of the energy expansion.

The index goes beyond current production by incorporating both company revenues and estimates of underlying reserves, helping reflect future alongside present supply. Strong Performance Driven by Key Sub-Industries

Following its launch in August 2023, the S&P Global Essential Metals Producers Index underperformed its starting level for an extended period, reflecting limited early attention to the theme. This changed in August 2025, when the index broke out of its range and rallied sharply. It nearly doubled by February 2026, outperforming the S&P Global BMI Materials (Sector) by 71%.

This performance was largely driven by companies within the Diversified Metals & Mining, Precious Metals & Minerals, Silver and Copper GICS^® sub-industries. At the constituent level, Southern Copper Corporation and Boliden were the primary contributors.

More recently, geopolitical developments have tempered this momentum. The onset of the Iran conflict led to a period of consolidation, with the index moving within a narrower range since early March 2026. The index was up approximately 2% QTD as of June 24, 2026, broadly in line with the global materials benchmark. What stands out is the change in performance drivers. Earlier gains were broad-based, led by strong contributions from multiple GICS sub-industry groups. In contrast, recent performance has become far more concentrated, with only modest positive contributions from Diversified Metals & Mining (2%) and Copper (1%), while several previously supportive segments have turned into slight drags.

Structural Demand Meets Supply Constraints

The AI buildout is already underway, driving investment in data centers, power infrastructure and networks, and creating immediate demand for critical materials. This demand is structural, as it is tied to long-term infrastructure rather than economic cycles. Policy is reinforcing this, with governments prioritizing supply security and reducing reliance on concentrated supply chains.

At the same time, supply remains slow to respond, as new mining capacity can take years to develop. This combination of structural demand, supportive policy and constrained supply underpins a more durable outlook for the sector.⁶

The S&P Global Essential Metals Producers Index provides a barometer to track demand for critical materials and the evolving supply landscape. Its focus on companies involved in both demand growth and resource ownership helps illustrate how this segment evolves over time. Importantly, it reflects demand that is structural and tied to infrastructure buildout, rather than technology adoption cycles.

 

¹ "EU Commission looking at practical consequences of Anthropic decision, spokesperson says," Reuters, June 14, 2026.

² Bazilian, Morgan and Jamie Webster, "How China Turned the Strait of Hormuz Crisis into an Advantage," The National Interest, June 23, 2026.

³ Baskaran, Gracelin and Meredith Schwartz, "Rare Earth Export Restrictions One Year Later," CSIS, April 27, 2026.

⁴ Critical Raw Materials Act - European Commission

⁵ What Are Critical Minerals and Materials? - U.S. Department of Energy

⁶ "Critical minerals outlook: surging demand, expanding supply chains," JPMorgan Chase, Feb. 23, 2026.

 

 

The posts on this blog are opinions, not advice. Please read our Disclaimers.

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Few economies are as deeply embedded in the global technology supply chain as Taiwan. Its highly sophisticated chip manufacturing network benefits from demand across a broad range of high-value end markets, from AI infrastructure and data centers to smartphones and electric vehicles. This positioning has propelled the S&P Taiwan BMI to an average annualized gain of 23.4% in Taiwanese dollar terms (23.7% in U.S. dollar terms) over the past 10 years, significantly outperforming global equities, as measured by the S&P Global BMI, and U.S. equities, as measured by the S&P 500^®.

When markets are rising, strong performance can grab the headlines and risks can often be overlooked. One of the primary risks in Taiwanese equities is concentration. The market's reliance on the semiconductor industry is evidenced by the fact that the Taiwan Semiconductor Manufacturing Company (TSMC) alone represented a 44% weight in S&P Taiwan BMI, as of June 15, 2026. As illustrated in Exhibit 2, at the GICS^® industry level, Semiconductors & Semiconductor Equipment accounted for roughly two-thirds of the S&P Taiwan BMI's gains in 2025 and 2026 YTD.

Valuation has also risen to a more stretched level. As of May 29, 2026, the one-year forward price/earnings (P/E) ratio of the S&P Taiwan BMI had risen to 23.67, at premiums of 9% and 23% to the S&P 500 and S&P Global BMI, respectively. While valuations are not indicators of market direction, high valuations may provide context for assessing sensitivity to changes in market sentiment.

Given the concentration risk and elevated valuation of Taiwanese equities, global diversification may be a relevant consideration when evaluating Taiwan-based strategies. For a Taiwan-based equity strategy, a globally diversified index offers three things:

• Diversified sector profile that balances technology and other sectors;
• Diversified regional profile; and
• Reduced valuation.

The S&P TIP Global AllCap Index targets 90% of the float-adjusted market capitalization of the S&P Global BMI and represents a broader global equity universe than a Taiwan-focused strategy.¹ The index included 2,272 constituents across 48 markets as of June 15, 2026. Exhibit 4 highlights a more balanced sector profile of the S&P TIP Global AllCap Index compared with the S&P Taiwan BMI's 83% weight in Information Technology. Lastly, the S&P TIP Global AllCap Index has traded at a more moderate valuation, with a one-year forward P/E ratio of 18.96, compared with 23.67 for the S&P Taiwan BMI as of May 29, 2026.

Over the past decade, the S&P Taiwan BMI has outperformed the S&P TIP Global AllCap Index on both an absolute and risk-adjusted basis. However, diversification coincided with an improved balance between performance and risk. For example, a hypothetical blend of 60% S&P Taiwan BMI and 40% S&P TIP Global AllCap Index would have delivered stronger risk-adjusted performance than either individual index over the period studied (see Exhibit 5). This hypothetical back-tested analysis shows the historical effects of combining a Taiwan equity-focused index with a more globally diversified index: lower volatility while preserving much of the performance. The hypothetical 60/40 blend's smaller pullbacks during recent market downturns in 2021-2022 and 2025 further highlight the diversification effects.

To learn more, check out our recent piece, "TalkingPoints: Measuring Global Equity Beta with the S&P TIP Global AllCap Index."

¹ The index is owned by S&P Dow Jones Indices, with the Taiwan Index Plus Corporation (TIP) serving as the local partner in the Taiwanese market. See the S&P TIP Global All Cap Index Methodology for more details on the index construction.

This content may be AI-assisted and is composed, reviewed, edited, and approved by S&P Global.

The posts on this blog are opinions, not advice. Please read our Disclaimers.