Indexology^® Blog

The S&P 500^® Momentum Index tracks the top 20% of S&P 500 stocks by 12-month risk-adjusted price momentum.¹ Backed by persistent market trends, the index has outperformed significantly relative to the broader market in recent years (see Exhibit 1).

The S&P 500 Momentum Index rebalances semiannually after the close of the third Friday of March and September, using the final business day of February and August as reference dates, respectively. This blog examines the recent September rebalance, detailing constituent changes, sector and industry group weights, and pre- and post-rebalance factor characteristics.

During the September rebalance, the index added and removed 54 constituents; Exhibit 2 highlights the five largest additions and removals. Notably, Apple entered the index with a weight of 9.23%, while Nvidia and Broadcom were removed (which were previously weighted at 8.99% and 6.12%, respectively). Following the rebalance, the index included two Magnificent 7 companies: Apple (9.23%) and Alphabet (8.95% between the combined share classes).

Sector Breakdown

Information Technology remained the largest sector in the S&P 500 Momentum Index following the September rebalance, accounting for 52.91% of the weight. Health Care rose to become the second-largest sector, replacing Industrials, while the weights of all other sectors remained relatively unchanged.

Industry Group Breakdown

While overall weight of the Information Technology sector remained stable, its underlying industry weightings shifted significantly: the Semiconductor & Semiconductor Equipment industry group fell by 13.0%, while Technology Hardware & Equipment rose 12.1%, driven largely by Apple.

This rebalance reduced the index’s large overweight in semiconductors. Furthermore, Apple’s inclusion introduced potential diversification within AI-related themes, as its revenue is less directly tied to AI capital expenditures than that of major semiconductor firms.

Factor Tilts

Exhibit 5 highlights the S&P 500 Momentum Index’s pre- and post-rebalance factor tilts relative to the S&P 500 using Northfield Risk Model Z-scores. As expected, the index exhibited a stronger momentum tilt following the rebalance, alongside a smaller growth tilt and an increased value tilt.

¹ Please refer to the S&P Momentum Indices Methodology for more details.

Indices are constructed from components brought together by methodology and the market. Unlike stocks in an equity index, the constituents in the S&P USD Select Leveraged Loan Index are retired or reweighed as new loans are issued and existing loans are paid down. As a result, loan vintages from different years are mixed within the index and its composition evolves over time to reflect changes in the underlying credit market.

To illustrate how a loan benchmark evolves, we will examine the markedly different economic environments of December 2020 and June 2026 through the lens of the index and see how it responded to such changes.

A helpful starting point is to assess industry concentration to see what types of companies are receiving public leveraged loans. Over this period, the S&P USD Select Leveraged Loan Index observed the largest relative shifts of weight into Financial Services and Capital Goods (see Exhibit 1). Both of these industries can be relatively capital intensive, so it is not surprising to see more loan volume flowing in to support these businesses.

Another metric to review is how the loans’ maturities have changed over time. In the 2020 data, the final legal maturity follows a normal, bell-shaped distribution, which could have been the result of borrowers choosing not to aggressively refinance and instead allowing loans to mature in a low interest rate environment (see Exhibit 2). In contrast, the current maturity wall of the index has been pushed further out (see Exhibit 3).

These shifts in maturity may indicate a market that is pushing refinancing and loan repayment out over a longer time horizon. This suggests market participants may be reflecting concerns that, in the short term, the U.S. may see additional rate hikes from the Federal Funds current target of 3.50%-3.75% to combat inflation and that borrowers may seek to avoid refinancing in this environment.

Despite differences in maturity and industry mix as well as the changing rate environment, spreads have not changed meaningfully over the period examined, which may be relevant to market participants seeking to deploy capital consistently and may help contextualize concerns about spread compression across the whole asset class (see Exhibit 4).

Lastly, while the distribution of index weight across industries is changing, the deviation in loan sizes across companies in the index can also be assessed to determine whether concentration risk is changing over time. In certain categories such as Software & Services, for example, there was a much higher standard deviation in June 2026 than in December 2020 (see Exhibit 5).

What can be derived from these exhibits is that while some characteristics of the index may change, others remained stable, showing how the asset class has evolved in response to changing economic conditions. Accordingly, the S&P USD Select Leveraged Loan Index continued to serve as a gauge of lending conditions and demonstrated stability across multiple dimensions.

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

In Homer’s Odyssey, the title character, Odysseus, spends years away from home fighting at Troy before making the challenging journey home to Ithaca. Sirens tempt him off course, lotus flowers cause his sailors to lose sight of their objective and storms repeatedly delay the voyage. The clean energy industry has faced its own odyssey: a long transition shaped by changing priorities, policy turns and geopolitical disruption.

The S&P Global Clean Energy Transition Index has served as a compass throughout this journey. Launched in 2007, almost 20 years ago, it measures the performance of companies involved in clean energy-related businesses, spanning power generation and enabling technologies. Its history covers periods of market enthusiasm and retrenchment; it peaked in 2008, then declined over an extended period before rising again during the COVID-19 pandemic. Since 2021, the index has been rewired for greater transparency, expanded emerging markets coverage and stricter carbon reduction requirements.

Exhibit 1 illustrates its ongoing, choppy journey since then. Over the five-year period ending Aug. 31, 2026, the S&P Global Clean Energy Transition Index declined 4.1%, compared with a 12.8% gain for the S&P 500^®. Higher interest rates created storms; shifting policy priorities acted like lotus flowers, pulling focus away from renewables back to fossil fuels; wars and geopolitical tensions posed obstacles; and the rise of artificial intelligence (AI) emerged as a new siren, commanding investor attention while also creating fresh opportunities for clean energy.

The one-year performance as seen in Exhibit 2 reflects the latter part of the tale. The S&P Global Clean Energy Transition Index gained 22.65% in the one-year period ending Aug. 31, 2026, outperforming the S&P 500. The war in the Middle East reinforced the importance of diversified energy sources and reduced dependence on geopolitically sensitive regions. In the U.S., the accelerated phaseout of key clean energy incentives compressed project timelines, prompting developers to rush to secure eligibility for their projects rather than causing an immediate slowdown in deployment. At the same time, clean energy is becoming a cornerstone in meeting AI’s growing hunger for power. Solar and energy storage are increasingly at the center of that buildout, with hyperscalers signing gigawatt-scale power agreements to secure the electricity needed for expanding data center infrastructure.

The maturity in the theme and industry is also reflected in S&P Global Energy’s Tier 1 Cleantech Companies List, bringing the focus back to the need for resilient infrastructure. Covering photovoltaic (PV) modules, PV inverters, wind turbines, energy storage systems and battery cells, the list identifies companies that meet rigorous criteria spanning market presence, scale, global diversification, financial performance, sustainability and credit risk.

While the two universes serve different purposes—with the S&P Global Clean Energy Transition Index encompassing a broad range of clean energy activities and the Tier 1 Cleantech Companies List focusing on leading equipment suppliers across both public and private markets—there is notable overlap between them (see Exhibit 3). As the energy transition matures, supplier quality, operational resilience and long-term durability are becoming important components of clean energy system readiness.

The challenge is no longer simply adding renewable capacity; clean energy investment now exceeds fossil fuel equivalent by nearly 2 to 1, a gap that has widened over the past decade.¹ Increasingly, what matters is converting generation into reliable, deliverable power through grid connections, permitting, storage, supportive regulation and suppliers capable of servicing equipment over an asset’s life. The clean energy investment case is expanding beyond clean generation to encompass the infrastructure nexus and need to produce, transmit, store and manage electricity.

Odysseus eventually reached home, but only after navigating Poseidon’s high seas. Unlike our hero, the clean energy industry does not have the luxury of divine guidance. Its next course will depend on resilience beyond power generation alone. Climate variability, including the potential for a strong El Niño, may increase the risk of heat, drought, flooding and wildfire, placing pressure on grids, water systems and supply chains. What the weather gods have in store remains uncertain; the S&P Global Clean Energy Transition Index and S&P Global Energy Tier 1 Cleantech Companies List offer a window into the companies helping build the raft for the journey ahead.

¹ See Forbes, “Clean Energy Is Outspending Fossil Fuels Nearly Two To One,” June 7, 2026.

We recently published the blog Indexing Autocalls, where we highlighted the continued investor demand for solutions that facilitate income generation—in particular, autocalls.

S&P Dow Jones Indices recently launched the S&P 500 Futures 35% Volatility Compass Autocall Index, which takes a unique approach to incorporating autocall features within an index framework. The index measures the performance of a continuously refreshing portfolio of hypothetical weekly issued put-barrier instruments on the S&P 500 Futures 35% Volatility Compass TCA 6% Decrement Index. Each instrument includes an autocall feature that allows for early redemption on a scheduled observation date if the index has recovered to, or exceeded, its level at issuance. In this way, the index seeks to generate hypothetical income through the premiums received from the issuance of new barrier instruments with an autocall feature, as opposed to fully replicating a hypothetical portfolio of autocall instruments.

Because an index is not an investment product, one cannot invest directly in an index but rather an investment product based on an index. As a result, descriptions of the index’s instruments and autocall features, for example, are hypothetical in nature.

The S&P 500 Futures 35% Volatility Compass Autocall Index incorporates a laddered put-barrier structure designed to generate hypothetical income from option premiums. The put barrier is constructed using a short put struck at 65% of the initial index level and a long put struck at 63% of the initial index level to replicate the desired barrier payoff. By laddering issuances over time, the index seeks to reduce timing risk across varying market conditions. Overall, the structure seeks to provide limited downside and premium buffer protection, helping to mitigate moderate losses before the put-barrier level is reached.

Because the S&P 500 Futures 35% Volatility Compass Autocall Index features an autocall mechanism, when the underlying index recovers to its issuance level, the relevant instrument can be redeemed early at fair value, allowing the portfolio to refresh rather than remain locked into the same position until final maturity. Additionally, new put-barrier instruments are issued on a recurring basis, creating a different yield profile compared to static option strategies.

As investor demand for income strategies remains strong, S&P DJI is committed to bring to market indices that reflect varied approaches to hypothetical income generation to a broader set of market participants.

For more than two decades, the SPIVA^® Scorecards have contributed to the active versus passive debate by measuring the performance of active funds against market benchmarks. Since the publication of the first SPIVA U.S. Scorecard in 2002, the methodology has been applied consistently across regions, asset classes and market cycles.¹

Performance measurement can be approached from different perspectives. Before interpreting the results, it is therefore important to understand the question an analysis is designed to answer. SPIVA is designed to answer a specific question.

Of the actively managed funds available to an investor at the beginning of a period, what proportion survived and outperformed an appropriate market benchmark by the end of that period?

The methodology is designed around this objective and is applied consistently across markets and through time.

Different Questions Require Different Metrics

Not all investment strategies seek the same outcome. Active funds seek to outperform a benchmark, while passive funds seek to track a benchmark as closely as possible. The appropriate evaluation metrics therefore differ.

For active funds, a key question is whether the fund outperformed a relevant benchmark. For passive funds, the focus is typically on tracking difference and tracking error, which measure how closely a fund follows its benchmark. A passive fund that follows benchmark performance, less fees, would generally be considered to have fulfilled its objective. Applying an analytical framework designed for active funds to passive funds would therefore not address the objective that passive funds are designed to achieve.

Different approaches to evaluating active management can produce different perspectives. For example, one could focus on the average fund, the average invested dollar, surviving funds only or performance relative to a collection of investment products. Each approach may be informative, but each addresses a different question.

SPIVA focuses on active funds’ ability to outperform relative to benchmarks and applies that framework consistently across time periods and fund categories.

Benchmarks Matter

Benchmark selection is a critical part of performance measurement. A useful benchmark should represent the market opportunity set that a fund category intends to access and provide a consistent reference point for comparison across funds.

SPIVA begins with independently defined fund categories supplied by external fund-data vendors and then selects representative market benchmarks based on the characteristics of the category, the historical performance characteristics of its funds as a group and relevant market practices.

For example, the SPIVA New Zealand Scorecard uses the S&P World Index in NZD total return terms² as the benchmark for Global Equity funds. As shown in Exhibit 1, the S&P World Index exhibited correlations of 0.99 to 1.00 with two widely used benchmarks in the category and a correlation of 0.97 with the category’s asset-weighted average return over the three years ending June 30, 2026. Longer-term correlations are in a similar range. These results support its use as a closely aligned and consistently applicable category benchmark.

Why SPIVA Starts with the Original Opportunity Set

Survivorship is an important consideration in long-term fund performance analysis. When investors select funds, they cannot know which will survive, merge or liquidate over the intended investment horizon. All funds available at the outset therefore form part of the investor’s opportunity set.

SPIVA evaluates performance using the original fund universe rather than limiting the analysis to funds that survive until the end of the period. This helps address survivorship bias and prevents the analysis from benefiting from hindsight. Excluding non-surviving funds would remove part of the opportunity set investors actually began with and could present an incomplete picture of their eventual outcomes.

Exhibit 2 illustrates this effect using New Zealand Equity funds. Over the 15-year period ending June 30, 2026, 46% of the original fund universe did not survive, and only 8% both survived and outperformed. Among surviving funds alone, approximately 86% underperformed, compared with an overall underperformance rate of 92% when the original opportunity set was retained.

More than One Headline Number

SPIVA’s underperformance rate is often its most cited statistic, but it is only one part of the scorecard. SPIVA also reports equal-weighted and asset-weighted performance, survivorship statistics and quartile performance.

Exhibit 3 shows the range of outcomes among surviving funds over the five-year period ending June 30, 2026. In the Global Equity fund category, top- and bottom-quartile breakpoints were 13.5% and 8.0%, respectively, compared to 16.6% for the S&P World Index. For Global Equity (Hedged) funds, the corresponding breakpoints were 10.8% and 5.4%, compared with 12.2% for the S&P World NZD Hedged Index. The comparison illustrates both the dispersion of active fund outcomes and the potential influence of currency treatment on performance.

Conclusion

Different methodologies may arrive at different conclusions because they are designed to answer different questions. SPIVA provides a transparent and consistent framework for examining how frequently active funds have survived and outperformed an appropriate market benchmark. Understanding the question being asked is the first step in interpreting the answer.

¹ For more information and background on the SPIVA Scorecards, please see SPIVA By the Numbers: A Global Perspective and What is SPIVA?

² The S&P World Index was launched on Feb. 13, 2009, while its NZD-denominated versions were launched on Oct. 25, 2024.

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